Current Issues in Bilingualism: Cognitive and Socio-linguistic Perspectives

Current Issues in Bilingualism LITERACY STUDIES VOLUME 5 Series Editor: R. Malatesha Joshi, Texas A&M University, US...

Author: Mark Leikin | Mila Schwartz | Yishai Tobin

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Current Issues in Bilingualism

LITERACY STUDIES

VOLUME 5

Series Editor: R. Malatesha Joshi, Texas A&M University, USA Editorial Board: Linnea Ehri, CUNY Graduate School, USA George Hynd, Purdue University, USA Richard Olson, University of Colorado, USA Pieter Reitsma, Vrije University Amsterdam, the Netherlands Rebecca Treiman, Washington University in St. Louis, USA Usha Goswami, University of Cambridge, UK Jane Oakhill, University of Sussex, Brighton, UK Philip Seymour, University of Dundee, UK Guinevere Eden, Georgetown University Medical Center, USA Catherine McBride Chang, Chinese University of Hong Kong, China

While language defines humanity, literacy defines civilization. Understandably, illiteracy or difficulties in acquiring literacy skills have become a major concern of our technological society. A conservative estimate of the prevalence of literacy problems would put the figure at more than a billion people in the world. Because of the seriousness of the problem, research in literacy acquisition and its breakdown is pursued with enormous vigor and persistence by experts from diverse backgrounds such as cognitive psychology, neuroscience, linguistics and education. This, of course, has resulted in a plethora of data, and consequently it has become difficult to integrate this abundance of information into a coherent body because of the artificial barriers that exist among different professional specialties. The purpose of the proposed series is to bring together the available research studies into a coherent body of knowledge. Publications in this series are intended for use by educators, clinicians and research scientists in the above-mentioned specialties. Some of the titles suitable for the Series are: fMRI, brain imaging techniques and reading skills, orthography and literacy; and research based techniques for improving decoding, vocabulary, spelling, and comprehension skills.

A complete list of titles published in this series can be viewed by going to the following URL: http://www.springer.com/series/7206

Mark Leikin Mila Schwartz Yishai Tobin Editors

Current Issues in Bilingualism Cognitive and Socio-linguistic Perspectives

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Editors Mark Leikin University of Haifa Faculty of Education Department of Learning Disabilities Haifa Israel [email protected]

Mila Schwartz Research and Evaluation Authority Oranim Academic College of Education Kiryat Tivon Israel Edmond J. Safra Brain Research Center for the Study of Learning Disabilities University of Haifa Haifa Israel [email protected]

Yishai Tobin Ben-Gurion University of the Negev Department of Foreign Literatures & Linguistics Be’er Sheva Israel [email protected]

ISBN 978-94-007-2326-9 e-ISBN 978-94-007-2327-6 DOI 10.1007/978-94-007-2327-6 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2011938585 # Springer Science+Business Media B.V. 2012 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper Springer is part of Springer ScienceþBusiness Media (www.springer.com)

Abstract

Current Issues in Bilingualism addresses important cognitive and socio-linguistic issues related to the field of bilingualism and multilingualism. The motivation for this anthology has risen from two general phenomena: (1) the growing interest in bilingualism and multicultural societies due to rising worldwide immigration and an increasing interest in ethnic minorities and their language problems, particularly in the field of literacy and education; (2) the unique language situation in Israel, that represents one of the more complex cases of a multilingual and multicultural society, which includes the coexistence of two official languages, Hebrew and Arabic, English that is widely used in numerous contexts, and the native languages of large groups of immigrants such as Russian, Amharic and other languages. Therefore we view Israel as a mosaic of multilingualism and multiculturalism and thus a natural laboratory for studies dealing with these complex topics. This volume discusses such themes as the education of immigrant children and adolescents, the development of bilinguals with specific language and reading impairment, bi-literacy and triliteracy acquisition in the context of a complex multilingual and multicultural society, and neuro-cognitive aspects of bilingual language processing, in particular in the field of reading and reading disabilities.

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Contents

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Current Issues in Bilingualism: A Complex Approach to a Multidimensional Phenomenon . . . . . . . . . . . . . . . . . . . . . . . . . . . Mark Leikin, Mila Schwartz, and Yishai Tobin

Part I 2

Language and Literacy in Multilingual Society

Relevance of the Linguistic Coding Difference Hypothesis to English as an Additional Language of Literacy in Israel. . . . . . . . . . . . . . . . . . Janina Kahn-Horwitz, Richard L. Sparks, and Zahava Goldstein

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Literacy Reflexes of Arabic Diglossia . . . . . . . . . . . . . . . . . . . . . . . . . Elinor Saiegh-Haddad

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Multilingualism Among Israeli Arabs, and the Neuropsychology of Reading in Different Languages. . . . . . . . . . . . . . . . . . . . . . . . . . . . Zohar Eviatar and Raphiq Ibrahim

Part II

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Academic Achievement of Children Coming from Immigrant Families

Cognitive, Language, and Literacy Development in Socio-culturally Vulnerable School Children – The Case of Ethiopian Israeli Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michal Shany and Esther Geva Second Generation Immigrants: A Socio-Linguistic Approach of Linguistic Development Within the Framework of Family Language Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mila Schwartz Understanding Language Achievement of Immigrants in Schools: The Role of Multiple Academic Languages . . . . . . . . . . . . . . . . . . . . . Tamar Levin and Elana Shohamy

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Part III 8

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Multilingual Acquisition and Processing

Adjective Inflection in Hebrew: A Psychollinguistic Study of Speakers of Russian, English and Arabic Compared with Native Hebrew Speakers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Iris Alfi-Shabtay and Dorit Ravid Verb Inflections as Indicators of Bilingual SLI: Qualitative Vs. Quantitative Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sharon Armon-Lotem, Galit Adam, Anat Blass, Jonathan Fine, Efrat Harel, Elinor Saiegh-Haddad, and Joel Walters Procedural and Declarative Memory in the Acquisition of Morphological Knowledge: A Model for Second Language Acquisition in Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sara Ferman and Avi Karni

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Reading in L1 and L2: Behavioral and Electrophysiological Evidence: A Comparison Between Regular and Dyslexic Readers . . . . . . . . . . . 217 Zvia Breznitz and Liat Fabian

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Identification of Grammatical Functions in Two Languages . . . . . . . Mark Leikin and Elina Ritvas

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Contributors

Galit Adam The Open University, Milton Keynes, England, [email protected] Iris Alfi-Shabtay Tel Aviv University, Tel Aviv, Israel, [email protected] Sharon Armon-Lotem Bar-Ilan University, Ramat-Gan, Israel, [email protected] Anat Blass Bar-Ilan University, Ramat-Gan, Israel, [email protected] Zvia Breznitz Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, University of Haifa, Haifa, Israel, [email protected] Zohar Eviatar Department of Psychology, University of Haifa, Haifa, Israel, [email protected] Liat Fabian Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, University of Haifa, Israel, [email protected] Sara Ferman Department of Communication Disorders, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel, [email protected] Jonathan Fine Bar-Ilan University, Ramat-Gan, Israel, [email protected] Esther Geva University of Toronto, Toronto, ON, Canada, [email protected] Zahava Goldstein Faculty of Education, University of Haifa, Haifa, Israel, [email protected] Efrat Harel Bar-Ilan University, Ramat-Gan, Israel, [email protected] Raphiq Ibrahim Department of Learning Disabilities, University of Haifa, Haifa, Israel, [email protected] Janina Kahn-Horwitz Oranim Academic College of Education, Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, University of Haifa, Haifa, Israel, [email protected]

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Contributors

Avi Karni Laboratory for Functional Brain Imaging and Learning Research, Faculties of Science and Education, University of Haifa, Haifa, Israel, [email protected] Mark Leikin Laboratory for Neurocognitive Research of Giftedness, Department of Learning Disabilities, Faculty of Education, University of Haifa, Haifa, Israel, [email protected] Tamar Levin Tel Aviv University, Tel Aviv, Israel, [email protected] Dorit Ravid Tel Aviv University, Tel Aviv, Israel, [email protected] Elina Ritvas Department of Learning Disabilities, Faculty of Education, University of Haifa, Haifa, Israel, [email protected] Elinor Saiegh-Haddad Department of English Linguistics, Bar-Ilan University, Ramat-Gan, Israel, [email protected] Mila Schwartz Research and Evaluation Authority, Oranim Academic College of Education, Kiryat Tivon, Israel; Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, University of Haifa, Haifa, Israel, [email protected] Michal Shany Department of Learning Disabilities, Faculty of Education, University of Haifa, Haifa, Israel, [email protected] Elana Shohamy Tel Aviv University, Tel Aviv, Israel, [email protected] Richard L. Sparks College of Mount St. Joseph, Delhi Township, OH, USA, [email protected] Yishai Tobin Department of Foreign Literatures & Linguistics, Ben-Gurion University, Be’er Sheva, Israel, [email protected] Joel Walters Bar-Ilan University, Ramat-Gan, Israel, [email protected]

Part I

Language and Literacy in Multilingual Society

Chapter 1

Current Issues in Bilingualism: A Complex Approach to a Multidimensional Phenomenon Mark Leikin, Mila Schwartz, and Yishai Tobin

1.1 Introduction The past 20 years have seen an unprecedented upsurge of interest in bilingualism and multilingualism. A major reason for this is no doubt the acknowledgement by a growing number of researchers that the use of two or more languages is far more common than was previously thought, and may perhaps even be the norm. There are no exact data on the number of bilinguals throughout the world.1 However, some researchers claim that over 50% of the world’s population is bilingual (Fabbro, 1999). Bilingualism prevails at the societal level as well. With an estimated 6000 languages at this time being spoken in the world (Grimes, 2000), and with only some 200 countries, simple mathematics demonstrates that many countries must, in one way or another, be bi- or multilingual (Dewaele, Housen, & Wei, 2003). An investigation of the phenomenon of bilingualism and second language acquisition, therefore, has not only great theoretical significance, but will also be of great practical importance. In this context, we considered that it would be both interesting and useful to present a volume containing a number of experimental studies focusing on some major aspects of bilingualism and multilingualism from diverse theoretical and methodological points of view which have been carried out recently in Israel. The motivation for this anthology has risen from two general reasons: (1) The growing interest in multicultural societies due to rising worldwide immigration and an increase in attention given to ethnic minorities and their language problems, particularly in the field of literacy and education from cognitive and socio-linguistic points of view; 1 Hereinafter the term ‘‘bilingual’’ is used in the wider sense of the word: people who know more than one language.

M. Leikin (*) Laboratory for Neurocognitive Research of Giftedness, Department of Learning Disabilities, Faculty of Education, University of Haifa, Haifa, Israel e-mail: [email protected] M. Leikin et al. (eds.), Current Issues in Bilingualism, Literacy Studies 5, DOI 10.1007/978-94-007-2327-6_1, Ó Springer ScienceþBusiness Media B.V. 2012

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(2) The unique language situation in Israel, which represents one of the more complex cases of a multilingual and multicultural society, including the coexistence of two official languages, Hebrew and Arabic (the language of the largest ethnic minority in Israel), English as semi-official language that is widely used in numerous contexts (especially in ‘‘academia’’, economics and politics), and the native languages of large groups of immigrants (e.g., Russian, Amharic, Spanish, French and scores of others). Note, however, that the above described linguistic and cultural situation is not only interesting in itself but also promotes scientific study in the multilingual domain and permits the generalization and possible projection of data to other countries and societies.

1.2 Bilingualism and Multilingualism: Research Directions The growing interest in bilingualism and multilingualism is rooted in globalization and increased immigration on the one hand, and in the strong needs of ethnic minorities to maintain their language and culture on the other. Both of these tendencies are characteristic of Israel as a country, which provides natural conditions for diverse and complex language interactions. These interactions are created by the meeting of typologically different languages and scripts, and such dyads and triads as, for example, Hebrew-Arabic and Hebrew-ArabicEnglish or Russian-Hebrew and Russian-Hebrew-English become more common and thus create a multilingual and multicultural mosaic which typifies Israel today. Current research on multilingualism highlights it as a phenomenon whose nature is to be investigated on its own terms apart from bilingualism (Aronin & Hufeisen, 2010). Recently both the awareness of multilingualism and research in this area have become increasingly relevant and useful in light of above noted tendencies of globalization and increasing immigration rates. A significant amount of research that probes more deeply into various aspects of contemporary multilingualism has appeared along with the continuation of intensive study of different aspects of bilingualism (Aronin & Hufeisen, 2010; Bhatia & Ritchie, 2006; Haznedar & Gavruseva, 2008; Kroll & de Groot, 2005). Accordingly, this volume also addresses not only practical topics in the field of bilingualism but additionally deals with such important issues of multilingualism as, language typology, and multilingual education, with its main focus on multilingual and multicultural societies such as Israel. In this context, Israel may be considered as an example of a natural laboratory of multilingualism. In this anthology we have aimed to address some of the most frequently discussed contemporary questions relating to the nature of bilingualism and multilingualism in the world by focusing on language and literacy in the multilingual mosaic of Israel as a research laboratory. It is important to note that even a cursory examination of these issues reveals the complexity and ambiguity

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of the phenomenon of bi- and multilingualism. Not surprisingly, bilingualism (as well as multilingualism) appears as the center of interest of various scientific disciplines including linguistics, psycho- and neurolinguistics, sociolinguistics, cognitive psychology, and education. This anthology therefore presents a variety of language pairs, research approaches and scientific fields. However, before we introduce the studies included in the volume, we would like to briefly characterize the linguistic situation in Israel as a multilingual mosaic.

1.3 The Multilingual Mosaic: The Case of Israel In this section we will relate to the unique language situation in Israel historically and from the perspective of language policy. Our focus will be on Arabic as the language of the largest ethnic minority in Israel, English as a semi-official language (mostly second or even third language) and the native languages of the largest groups of new immigrants (Russian and Amharic).

1.3.1 The Arabic Language As previously mentioned, Arabic (together with Hebrew) is one of the two official national languages in Israel. Arabic is used intensively in diverse social and practical contexts (including academic and civil contexts). The native Palestinian Arabic-speaking population of Israel uses Standard Arabic in its schools. As in other Arabic-speaking countries, the ‘‘purity’’ of the Standard Arabic language was preserved by the rigorous separation of the written and spoken varieties, a phenomenon that Ferguson (1959) labeled diglossia. Ferguson (1959) proposed the classical definition of diglossia as being a stable linguistic state that includes different spoken local dialects (ammia) and a very dissimilar literary standard language [version] (fus: h: a), which is usually more grammatically complex, distinct from the different spoken dialects, and includes a respectable written tradition and standard. The literary language is the language officially taught and studied in school and is usually not acquired naturally but formally. Therefore, Standard Arabic (i.e., the standard literary language) is first encountered in school and can be viewed almost as a second language (Ibrahim & Eviatar, 2007). This diglossic situation of the Arabic language hinders children’s acquisition of literacy in Arabic (Ayari, 1996; Saiegh-Haddad, 2003).

1.3.2 The Languages of Immigrants Historically, Israel may be viewed as a classical case of a country of migration that has absorbed a large immigrant population of multiple and diverse origins. However, until recently, the dominant language policy in Israel was to strongly

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and exclusively support only one language: Hebrew (the revived national language of the Jewish people), and there was a purposeful and tendentious lack of interest displayed for the languages spoken by the Jewish immigrants (except, perhaps, for English, because of its international character). As a result, the active use of languages such as German, Polish, Yiddish, Spanish and French was discouraged and ignored, and they were basically overshadowed and/or lost. However, in the last two decades there have been significant changes in language policy and in the attitudes to languages other than Hebrew (Spolsky & Shohamy, 1999). There are two major groups of immigrants that have clearly influenced these changes in the linguistic policy in Israel. The first is the massive arrival of immigrants from the Former Soviet Union (FSU) to Israel (over 835,000 people between the years 1990 and 1999). A comparison of this intensive wave of migration with other migrations to a single country in such a short period as the decade of the 1990s shows that in absolute numbers, it was among the largest; and relative to the size of the receiving population, it far exceeded all other countries that absorbed migrant populations. This mass migration has often been compared to the proportionally equivalent immigration of the entire population of France to the United States. These immigrants from the FSU are currently the largest ethnic immigrant group in Israel, comprising approximately one million Russian-speakers. The influx of immigrants from the FSU in the 1990s occurred against the background of a general decline in the original Hebrew monolingual nationbuilding ideology (Glinert, 1995a), as well as a national identity crisis of the ‘‘post-Zionist’’ Israeli society (e.g., Ben-Rafael, 1994). This wave of massive immigration was one of the major factors that encouraged Israeli society towards multilingualism (Spolsky & Shohamy, 1999); challenged the ‘‘melting pot’’ policy towards ethnic minority groups as well as the dominance of Hebrew as the realization of monolingual ideology in Israel (Leshem & Lissak, 1999; Nudelman, 2000; Kotik-Friedgut, 2000; Shuval, 1999). The large-scale character of this immigration group may explain the avowed policy of this community to retain its language of origin: Russian. This strong commitment to the heritage language can be regarded as an application of Fishmann’s Reversing Language Shift theory (RLS) (1991, 2001), which seeks to serve as a directive for worldwide attempts to support minority languages (such as Russian in Israel). The Russian language has attained the status of one of Israel’s main languages (Olstein, 1995), after Hebrew (the official language) and English. A state-sponsored Russian-language radio network and TV channel, and the publication of some 50 Russian-language newspapers and magazines attest to its importance. Another factor strongly associated with Fishmann’s RLS theory (1991, 2001) is the Russian Jewish (RJ) immigrants’ tendency to appreciate their original culture, which encouraged them to maintain their language of origin and promote its acquisition by their children, including those who were born in Israel (Ben-Rafael, Olshtain, & Geijst, 1997; Donitsa-Schmidt, 1999; Leshem & Lissak, 1999). The assertion of RJ immigrants’ original cultural identity

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underlies one of the stated aims of language policy at the community level: the promotion of a supplementary private Russian-language education system (non-formal education) designed to preserve the cultural heritage and the mother tongue in its standard written form among Israeli-born RussianHebrew speaking (RHS) children. The second new large immigrant group are the more than 75,000 immigrants from Ethiopia, mainly speakers of Amharic and Tigrinya, with some literacy in Amharic and Ge’ez. The background of these immigrants is from the Ethiopian rural community, and their culture is predominantly oral. The literacy rate in this community is no more than 40% (Spolsky & Shohamy, 1999). Most Ethiopian immigrants are unskilled workers, and the unemployment rate among this community is higher than in the general population (Svirsky & Svirsky, 2002). It should be further noted that the status of Amharic in Israel is low (Spolsky & Shohamy, 1999). In contrast to the Russian-speaking immigrant community, immigrants from Ethiopia relinquished the maintenance of their first language, its culture and traditions in favor of a second language unrelated to their native ethnic and cultural values. As a result, the second-generation Ethiopian immigrants actually grow up as Hebrew-speaking monolinguals with a rather limited link with a heritage language, traditions and culture. Concerning the mastering of Hebrew (L2), recent reports indicate that about 60% of more recent immigrants from Ethiopia claim that they have only a minimal command of Hebrew. In addition, 55% of the male adults cannot read or write Hebrew, and this percentage is even higher among women (70%) (King, Effrati, & Netzer, 2003). Even so, these two large waves of immigration together with the wide spread of English not only caused significant changes in Israeli society from the viewpoint of its relation to bilingualism, but also presented two radically diverse as well as equally interesting cases of bilingualism.

1.3.3 The Place of English in Israel English has spread throughout the word inevitably capturing the status of the primary word language. Thus, Israel has not been exempt from this massive use of English as a universal lingua franca. English, which does not have the status of an official language of the country (as do Hebrew and Arabic), is still widely used in higher education and in many other fields of life and generally is taught early in elementary school. Historically, the role of English grew after the conquest of Palestine by British troops under General Allenby and the subsequent award of a Mandate for Palestine to the British government (Spolsky & Cooper, 1991). As well as serving as a language for access to business, science, education, and travel, English is a language of major Jewish Diasporas in the US and elsewhere and the language of the large number of English-speaking immigrants (Spolsky,

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1996). De facto English has become the second language of academic life as well. For that reason, the importance ascribed to English in schools is in a large measure a reflection of the salience of the fact that all Israeli universities require entering students to have a minimum level of competence in the language (Spolsky & Shohamy, 1999) and maintain an obligatory series of English as a Foreign language (EFL) courses to an advanced level to ensure the students’ ability to read academic texts in English. It is important to note also that the demand for earlier English teaching in the elementary schools has continued to increase and resulted in exposure to English in the second and even in the first grade. Thus, national educational policy supports English as the major language of wider communication for Israelis, and it is taught as a major subject in both elementary and secondary schools. Thus, we hope that the picture of the unique ‘‘language mosaic’’ presented above supports our claim that Israel may be viewed as something like a ‘‘natural laboratory’’ of multilingualism and therefore provides a fitting example for discussing contemporary issues in bilingualism and multilingualism. Accordingly, the aim of our volume is not to review the unique language situation in Israel, but to present experimental research on major aspects of bi- and multilingualism from diverse theoretical and methodological points of view. For that reason, we have chosen not to group the chapters of this volume according to specific languages or language communities but rather by their research approaches to the aforementioned issues in different scientific fields. Therefore this anthology is divided into three sections: Part I deals with subjects related to language and literacy in a multilingual society; Part II addresses issues of the academic performance of children coming from immigrant families, and Part III focuses on multilingual acquisition and processing.

1.4 Part I: Language and Literacy in Multilingual Society There is no doubt that bilingualism presents a highly attractive topic for linguists and psycholinguists who study language acquisition and use (e.g., De Bot & Kroll, 2002; Grosjean, 1998). Recent psycholinguistic research in the bilingual and multilingual domain has focused on a wide range of topics including the following which are within the scope of this volume: (1) crosslinguistic transfer and L2 literacy acquisition and processing; (2) language typology and literacy acquisition. Psycholinguistic research in the last two decades has dealt with the potential educational consequences of bilingualism, and, particularly, has attended to literacy acquisition in L1 and L2 (for a detailed review, see August & Shanahan, 2006). There are currently two very broad areas of research in the domain of literacy acquisition. The first concerns the question of whether the process of acquiring literacy skills is different for bilingual children as compared to monolinguals specifically because they are bilingual: i.e. is there

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an effect on L2 literacy acquisition that comes from having oral proficiency in L1 (L1 linguistic background) and/or literacy in L1 (L1 orthographic background) among typical readers (see, for example, Deacon & Cain, 2011). Accordingly, the second direction of the above-mentioned research is linked closely with the first and tries to determine the factors which could account for the difficulty in literacy acquisition in L2, such as specific language impairment and specific reading disability in L1 (e.g., Sparks & Ganschow, 1993b). Therefore, L2 learning difficulties are likely to be based in L1 learning and that faculty with one’s language ‘‘code’’ (e.g., linguistic, orthographic) is likely to play an important causal role in learning L2. In addition, both these research domains address the factor of language typology, more specifically linguistic and orthographic proximity between the languages within the dyads or triads in the process of literacy acquisition (Kahn-Horwitz, Schwartz, & Share, 2011). Evidence for the cross-linguistic transfer of phonological awareness and word identification skills from Hebrew (L1) to English as an additional language was supported by the longitudinal study of Kahn-Horwitz, Sparks and Goldstein (Chapter 2). They focus on the extent to which first language (Hebrew) and additional language (English) linguistic and literary abilities measured 6 years earlier (at 4th Grade) could predict word recognition and reading comprehension in English (in the 9th Grade). This paper broadens and enriches our understanding of the cross-linguistic transfer of phonological and word recognition skills by focusing on both opaque and deep orthographies, using Hebrew unpointed script – a consonant-based syllabary – and the English alphabet, each with different degrees and characteristics of opacity. It was found that underlying L1 abilities still predict English word accuracy 6 years after the beginning of English acquisition. Moreover, the knowledge of Hebrew vocabulary together with Hebrew spelling ability measured in fourth grade accounted for a significant amount of variance of English reading comprehension bearing evidence for a simple model of reading (Koda, 2005). The data were discussed with respect to one of the main hypotheses concerning the interaction between literacy development in L1 and L2, namely, the Linguistic Coding Differences Hypothesis (Sparks & Ganschow, 1993a). The authors underscore the educational implications from their findings raising critical issues concerning the education policy used in teaching English in Israel. The focus on linguistic proximity between the literary and spoken forms of the Arabic language is presented in Haddad’s article (Chapter 3) on diglossia in the Arabic language and its link to the acquisition of basic reading skills. This paper examines the classical issue of diglossia dealing not only with the definition of this complex concept but also with the considerable differences between Standard Arabic and the spoken vernacular that significantly challenge reading acquisition. Accordingly, Haddad’s contribution presents a detailed comparative description of the literary and spoken forms of the Arabic language by stressing the great discrepancies between the two in almost all

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language domains: lexical, morphological, syntactic, and phonotactic. Then, the author reviews the research focusing on the effect of the phonological distance between Standard Arabic and the spoken dialect on the acquisition of the basic reading process. In one of the studies reported by the researcher, kindergarten and first grade pupils were tested for their performance on phonemic awareness tasks that manipulated the status of syllabic structure (Standard Arabic CVCC versus spoken vernacular CVCVC) of pseudo-word stimuli. The results show that for both groups of children, the isolation of both the initial and final consonants in the Standard form of Arabic was harder than in the spoken form. The author concludes that novel Standard Arabic linguistic structures that are not available in the children’s spoken language pose a particular challenge in the acquisition of phonological processing and in word decoding for standard language phonological structures. This finding was defined as the linguistic affiliation constraint. In terms of the specific socio-cultural context in which the acquisition of literacy in Arabic is embedded (the diglossic situation), Haddad maintains, ‘‘the complex linguistic reality results in poor language skills in the written code and, in turn, in linguistic insecurity.’’ Eviatar and Ibrahim (Chapter 4) present a scientific review of their recent studies of bilingual reading processing in the context of the theoretical interpretation of the data found in the professional literature. It focuses on the linguistic features of specific languages and their influence on reading acquisition and reading processing in different languages from the neuropsychological point of view. Eviatar and Ibrahim’s study summarizes findings (many of which have been obtained by the authors themselves) with regard to Arabic/Hebrew bilingualism. In particular, the authors concentrate on two major topics. The first examines the complex linguistic situation in the Arabic-speaking population of Israel and has implications for reading acquisition. Israeli Arabs present a complicated case of bilingualism since in addition to the necessity of learning the language of the majority (i.e., Hebrew) and English, they encounter the specific problem of diglossia in the process of literacy acquisition. In this context, the authors propose a comprehensive review of the phenomenon of diglossia, which is a phenomenon similar to bilingualism in spite of the fact that in this case we do not deal with two different languages but with spoken and written forms of the same language (Ayari, 1996, see also above for details). The second topic focuses on the functional architecture of reading in Hebrew (as L1 and L2) and in Arabic (as L1) from the neuropsychological perspective. The review underscores the orthographic and morphological properties of Semitic languages influencing reading acquisition and processing in both target languages. For example, Eviatar and Ibrahim discuss the problems that are caused by the fact that in Arabic and Hebrew orthography, vowels are not a part of the orthography and are not presented in script and appear only in poetry, children’s books and liturgical texts as diacritical marks above, below or within the body of the word.

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1.5 Part II: Academic Achievement of Children Coming from Immigrant Families Two of the most discussed educational issues during the past 50 years in the countries receiving immigration have concerned (1) the education of immigrant children and (2) the most effective ways of teaching literacy in L2. Recent research points to a necessity to address these concerns from a socio-cultural perspective. More specifically, it is important to address the heterogeneity of immigrant children with respect to their socio-cultural background, language dominance and preference, the sequence of exposure to both languages, and the type of educational system in which they are enrolled. In a recent meta-analysis, Lesaux and Geva (2006) conclude that a number of variables at the contextual level (e.g., parental education, home literacy, demographics) affect immigrant children and the children of immigrants’ academic progress in such areas as reading comprehension. Parent-related factors (parental education, level of L2 mastery, home literacy, the role that parents undertake in the ‘‘education enterprise’’ of their children, the cultural capital resources, the parents’ ability to support academic progress) have also been consistently shown to be related to these children’s academic success (Lesaux, Koda, Siegel, & Shanahan, 2006). In this section, we extend our understanding of issues related to academic achievements of children coming from immigrant families by stressing the complexity of the sociolinguistic context regarding the acquisition of literacy, lexical knowledge and the proficiency in multiple academic languages. Shany and Geva (Chapter 5) present a thorough analysis of language development and the acquisition of literacy skills in Hebrew among second-generation immigrants from Ethiopia in Israel. The chapter addresses critical questions concerning specific components of language and literacy skills from a developmental perspective (in Grades 1, 2, 4, and 6). The authors provide a comprehensive overview of the main hypotheses concerning the acquisition of basic literacy and reading comprehension skills as a theoretical framework for their study as well as an in-depth description of the socio-cultural context in which Ethiopian Israeli children progress in their schooling. Their approach underscores the fact that in general the Ethiopian community in Israel does not possess the cultural capital resources that can be transmitted to their children’s education within Westernized culture, e.g., traditions of home literacy and learning strategic skills. In this case, the authors argue that the school policy makers and teachers are supposed to adapt their instruction to relevant aspects of the children’s home culture. The comparison between low socio-economic status (SES) Ethiopian and Non-Ethiopian groups on cultural, cognitive, linguistic and literacy dimensions revealed that while in underlying reading skills (e.g., phonemic awareness, word identification) no gaps have been found, the gaps persisted across grades on non-verbal ability, cultural knowledge, and grammatical skills. These findings are discussed in terms of their relevance to other groups migrating from non-literate to ‘‘developed’’ societies and their educational implications.

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In her contribution, Schwartz (Chapter 6) claims the necessity to take account of the socio-cultural background of second-generation immigrants while coming to conclusions concerning their developmental trends in vocabulary acquisition in L1 and L2. To support this claim, sound empirical evidence from recent studies conducted in Canada, the Netherlands, the United States and Israel is presented. Regarding the data concerning the socio-cultural profile of immigrant families, Schwartz argues that the traditional description of parental background is limited to reports on income and occupation, without reference to education as a separate factor. Accordingly, it may be misleading to relate only to SES of immigrant families in approaching the educational challenges of second-generation children. This is due to the possible discrepancy between the relatively high socio-cultural level obtained in the country of origin and the relatively low SES characterizing the first years of adaptation in the host country. Regarding L1 development in the context of immigration, this chapter attests to the crucial role of teaching literate L1 in both family and informal educational settings. In addition, this chapter underscores the importance of the children’s positive approach toward home language acquisition. It can be concluded, therefore, that Schwartz’s study moves beyond the traditional approach in sociolinguistic research by extending our knowledge to a range of sociolinguistic factors related to the second-generation immigrants’ progress in L1 and L2. If the two previous chapters (Chapters 5 and 6) concentrate on second generation (Israeli-born elementary school children) of immigrants from Ethiopia and the FSU, the contribution of Levin and Shohamy (Chapter 7) focuses on immigrant children from the same socio-cultural backgrounds previously mentioned but with different periods of residence in Israel and at a more advanced age. Levin and Shohamy explore the link between academic language and the educational achievements of the immigrant students from the FSU and Ethiopia as compared to native-Hebrew speakers in three grade levels (Grades 5, 9, and 11). The authors raise major unresolved questions concerning the education of students with diverse cultural backgrounds within a nonadditive Hebrew-speaking context such as: how do these students progress academically in different subject domains, which domains are characterized not only by specific concepts but also by particular language functions? The authors argue that learning a school subject requires the immigrant children to acquire a new language in addition to Hebrew (L2), because each subject area has a specific register, a specialized lexicon and a diverse set of discourse that are culturally related. Having based their claim, the authors present an in-depth analysis of the multiple meanings of academic language and explore the notion of content domain competence. Their findings point out a significant variability between the students born in Israel and in the FSU and Ethiopia by specific content domains focusing primarily on mathematics. The data also support the link between the socio-cultural dimension of the language of mathematics and the relatively low achievements of the students who have had no Western-based experiences in these domains. However, the results show that even students who

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immigrated from the FSU, with a rich tradition in mathematics and science instruction, face difficulties in their exposure to the different dimensions of the new academic language. The data found in response to these basic questions suggest that learning a content domain cannot be considered as a scaffolding strategy for L2 acquisition by immigrant students. This paper provides a significant contribution to the examination of the educational achievements of different ethnic immigrant groups within the non-additive context by adopting a quantitative approach to evaluate students’ performance in diverse academic languages.

1.6 Part III: Multilingual Acquisition and Processing Similar to the psycholinguistic research on language and literacy presented above, in this [chapter]/section we address the question of how language typology may affect second language acquisition specifically with regard to linguistic interference in the case of typologically different languages. What happens when the morphological structures of two typologically different languages are in contact is the topic of Alfi-Shabtay and Ravid’s study (Chapter 8). The authors focus on the four most frequently used languages of Israel (Hebrew, Russian, Arabic and English) distinguishing them in terms of morphological typology and complexity. While Hebrew, Russian and Arabic have a rich synthetic morphology, in which words typically contain more than one morpheme, analytical languages such as English contain a more restricted or limited morphology. [Accordingly]/Therefore, this chapter examines the way the nonnative Hebrew adult speakers with different language backgrounds (i.e., Russian, Arabic and English) process two types of adjectives (attributive vs. predicative) as compared to native speakers of Hebrew. Is the participants’ ability to identify grammatical and ungrammatical attributive and predicative adjectives linked to their language background? It is also of interest whether the participants’ performance on a judgment task, which tested their ability to identify grammatical and ungrammatical attributive and predicative adjectives, may vary in encountering the irregular categories (i.e., in cases of conflict between noun phonology and gender). Stressing similarities and differences between the above-mentioned languages in terms of adjective inflection, this paper contributes to our understanding of the psycholinguistic processes employed by adult bilinguals facing the complexity of Hebrew inflectional morphology. The participants’ achievements in the adjective inflection of L2 Hebrew were interpreted according to the following three forces that affect the performance on adjective inflection: (1) first language constraints; (2) second language constraints; and (3) constraints of processing and memory. In addition, this chapter focuses on two relatively novel research domains in multilingual acquisition and processing: (1) linguistic behavior among bilingual children with impaired language development; (2) neurocognitive research

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on multilingual acquisition and processing. Concerning atypical language acquisition, research in the interface of bilingual development and specific language impairment (SLI) has increased greatly in the past decade and raised a number of unresolved questions concerning the linguistic behavior of this population (Genesee, Paradis, & Crago, 2004; Paradis, 2007). For example, some recent psycholinguistic studies have begun to focus on the problem of whether dual language acquisition becomes an additional complication for children with impaired language development in their L1. In addition, this research has addressed the extent of difference in the trajectory and pace of language development among bilingual children with and without language impairment. An important constituent of this noted tendency includes discussion regarding the assessment and treatment of young bilinguals with SLI compared to monolingual bilinguals (see Paradis, 2007). The authors of Chapter 9 (Armon-Lotem, Adam, Blass, Fine, Harel, SaieghHaddad, and Walters) compare English-Hebrew early sequential bilinguals with specific language impairment (SLI) attending language pre-schools to typically developing bilinguals from regular pre-schools on the use of the verbal system in general and the verb tense system in particular in both target languages. In addition, the findings concerning the SLI bilinguals’ performance is compared with existing data on SLI monolingual acquisition in both languages, as well as studies of typical bilingual development, in order to evaluate the nature of the errors in usage of tense morphemes. As for comparison between typical and atypical SLI bilinguals language development, the data point out a qualitative similarity of the usage of inflections and the type of errors with difference in the quantity of errors. Moreover, the patterns of difficulty acknowledged for monolingual SLI children, either in English or in Hebrew, were also found in the SLI bilinguals, although none were equally manifested in both languages. The authors therefore argue that early childhood bilingualism per se could not be considered an inappropriate developmental choice for children with SLI by disproving a widespread belief that these children’s limited capacity for language would be overtaxed by learning two linguistic systems. Thus it might be suggested that children affected with a language-learning disability can be raised bilingually without any serious detriment to their grammatical development. A somewhat different approach to the issue of L2 acquisition can be seen in Karni and Ferman’s study (Chapter 10) which focuses on internal cognitive mechanisms which are involved in the process of second language learning among adults. There is a widespread notion that adults have reduced and less effective language learning ability than children. At the same time, there is ample evidence suggesting that the acquisition and retention (long-term memory) of procedural skills as well as declarative memory (facts, singular events) of non-linguistic origin are robust in healthy adults. The authors examine these issues by the intensive, multi-session training of adults on an artificial morphological rule, and examined whether key characteristics of non-linguistic skills are recognizable in linguistic rule learning with regard to L2 learning. The

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results showed that adults were highly competent in acquiring and retaining linguistic knowledge, with both memory systems contributing differentially to the learning of distinct aspects of the morphological rule at different stages along the mastering of skilled linguistic performance. Note that this finding agrees with a growing body of evidence suggesting that adults are as competent as, and often better than, children in acquiring and retaining non-linguistic skills. Thus, the results of Karni and Ferman’s study demonstrate the high potential of adult learners in L2 acquisition and accordingly raise a question as to what prevents adults from realizing this potential practically. Thus one may conclude that the cognitive approach to research of bilingualism appears to be very promising because it allows for investigating the basic mechanisms of underlying processes of L2 acquisition and bilingual language use. In this context, it should be noted that in the last two decades there has been an increase of interest in the neuropsychological and neurophysiological aspects of bilingualism and second language learning (Fabbro, 1999; Li & Green, 2007; Paradis, 2004). This interest in the neurocognitive aspects of bilingualism has been inspired by an expanding effort in the cognitive study of bilingualism (e.g., de Groot & Kroll, 1997), on the one hand, and a dramatic growth of language processing research using neuroimaging methods, on the other hand (e.g., Fabbro, 1999, Proverbio, Cok, & Zani, 2002). Historically, this research domain developed from neuropsychological studies of bilingual language impairments which focused on the representation and processing of multiple languages in the brain (Albert & Obler, 1978; Fabbro, 1999; Paradis, 2004; Perani & Abutalebi, 2005). Therefore, the neurocognitive study of bilingualism also mostly concerns cerebral lateralization and localization (Hull & Vaid, 2005; Paradis, 2004; Zhang & Wang, 2007). A number of previous studies have suggested distinct non-overlapping cortical representations of the two languages in bilinguals (Paradis & Goldblum, 1989; Paradis, 2004). In addition, different ERP patterns have been observed in first language processing of bilinguals and monolinguals (Donald, Meuter, & Ardal, 1986). However, a number of other studies have found evidence for overlapping cortical representations in bilinguals (e.g., Sarfarazi & Sedgwick, 1996; Paradis, 2004; Ullman, 2001). Empirical findings (fMRI and other neuroimaging tools) of the locations of activation sources for the two languages have also been contradictory (Briellman et al., 2004; Illes et al., 1999; Wartenburger et al., 2003). Behavioral studies of bilingual language processing have yielded mixed results as well: some have suggested a separate activation of L1 and L2 (Gerard & Scarborough, 1989) and others indicate the simultaneous activation of the two languages (e.g., Dijkstra, 2001). Thus we can see that neurolinguistic studies related to bilingualism have yielded contradictory results resulting in controversy. These controversies have been explained by differences in methodologies and/or subject populations (e.g., Grosjean, 1998). There have been further suggestions to distinguish between different bilingual processing styles for phonetic and syntactic

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information on the one hand, and for lexical-semantic information on the other (e.g., Marian, Spivey, & Hirsch, 2003). Two additional factors may be proposed to account for the above-mentioned contradictions: structural differences between the first and second languages and the variety of bilingualism types (e.g., early vs. late bilingualism). These two factors appear to be very interesting and promising areas for further investigation. Therefore, it is not surprising that in the last decade these two issues have played a key role in the research of bilingualism. For example, there have been a number of studies focusing on different types of bilingual speakers (early versus late bilingualism) and the consequences of these differences for cerebral representation: i.e., how the extent of the reliance on each of the above mechanisms among early vs. late bilinguals may affect language processing in each language (e.g., Birdsong, 2006; Fabbro, 1999). Another issue that has been intensively studied relates to the linguistic properties of different languages and their influence on bilingual language representation and processing (e.g., Fabbro, 1999; Paradis, 2004). Such growing interest was caused not only by developments in linguistics and psycholinguistics but also by the geography of neurolinguistic studies that have dramatically changed in the two past decades. In particular, the studies of bilingualism in Israel that have focused on two Semitic (i.e., Hebrew and Arabic) and a wide range of Indo-European languages (e.g., English and Russian) have provided very interesting data (see for details Breznitz & Lebovitz, 2008; Leikin, 2008) on the relationships between different types of bilingualism and the linguistic properties of different languages. The last two chapters in our volume also represent this direction of research. Reading behavior and brain activity of regular and dyslexic adult bilingual readers within linguistically and orthographically distant dyads, Hebrew (L1) and English (L2), was in the center of Breznitz and Fabian’s study (Chapter 11). More specifically, the focus of this research is on the target groups’ ability to process words in a list and in sentences in their L1 (Hebrew) and L2 (English). This chapter not only exemplifies neurocognitive research of typical and atypical bilingual reading processing, but also attempts to compare the readers’ behavior in light of their exposure to two languages (Semitic and Germanic) which are very distinct both linguistically and orthographically. The authors also provide a comprehensive review of neuropsychological studies in the reading domain and discuss the issues of definitions and theories on bilingualism from the neuropsychological perspective. More specifically, this chapter refers to various aspects of bilingual reading processing in different language domains (i.e., semantics, syntax and orthography), language differences and internal brain mechanisms underlying processes of typical and atypical reading. The findings of Breznitz and Fabian’s study indicate behavioral and electrophysiological differences in the processing profiles of dyslexic and regular bilingual readers in both first and second languages. Leikin and Ritvas (Chapter 12) examine differences in brain activity, specifically in Event-Related Potential (ERP) amplitudes and latencies in bilingual and monolingual (Russian/Hebrew and Hebrew) readers when processing

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the grammatical functions of words during the reading of sentences in two languages (Russian and Hebrew). Two groups of adult university students participated in the study: native speakers of Russian and native speakers of Hebrew. Results indicated significant differences in brain activity and its localization between Russian and Hebrew speakers during processes of the grammatical functions of words in first and second (for bilingual group) languages, as reflected by Event-Related Potential (ERP) measures and LORETA-Key analysis. In both groups of participants, P100, P200, P300, N400, and P600 ERP waves were identified for three grammatical functions (subject, predicate, and direct object) in each sentence, for all reading items and in both languages. Analysis of the results showed that participants used different strategies to identify the grammatical functions of words in their native languages. The results appear to confirm the hypothesis (Leikin, 2002) that Hebrew readers identify the grammatical functions of words at least partly through their lexicalmorphological properties, while simultaneously using word order as well. By contrast, native speakers of Russian use morphologically based, noun-oriented strategies. The findings are consistent with results reported in the recent literature showing that grammatical processing in a second language is fundamentally different from grammatical processing in one’s native language. It is our hope that the contents of this volume will integrate the emerging interdisciplinary field of multilingualism studies in multicultural societies by bringing together such diverse areas as linguistics, sociology, education, and cognitive science in general while concentrating on the context of Israel as a mosaic of multilingualism and a natural laboratory in particular.

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Koda, K. (2005). Insights into second language reading: A cross-linguistic approach. New York: Cambridge University Press. Kotik-Friedgut, B. (2000). Variety of languages and the dynamics of language policy in contemporary Israel. In A. D. Epstein & A. V. Fedorchenko (Eds.), Mass migration and its impact on the Israeli society (pp. 154–192). Moscow: Institute Izucheniya Izrailya i Blizhnego Vostoka [in Russian]. Kroll, J. F., & de Groot, A. M. B. (Eds.). (2005). Handbook of bilingualism. Oxford: University Press. Leikin, M. (2002). Processing words’ syntactic functions in normal and Russian readers. Journal of Psycholinguistic Research, 31(2), 145–163. Leikin, M. (2008). Syntactic processing in two languages by native and bilingual adult readers: An electrophysiological study. Journal of Neurolinguistics, 21, 273–349. Lesaux, N. K., & Geva, E. (2006). Synthesis: Development of literacy in language minority learners. In D. L. August & T. Shanahan (Eds.), Developing literacy in a second language: Report of the national literacy panel. (pp. 53–74). Mahwah, NJ: Lawrence Erlbaum Associates. Lesaux, N. K., with Koda, K., Siegel, L. S., & Shanahan, T. (2006). Development of literacy of language minority learners. In D. L. August & T. Shanahan (Eds.), Developing literacy in a second language: Report of the national literacy panel. (pp. 75–122). Mahwah, NJ: Lawrence Erlbaum Associates. Leshem, E., & Lissak, M. (1999). Development and consolidation of the Russian community in Israel. In S. Weil (Ed.), Roots and routes: Ethnicity and migration in global perspective (pp. 135–171). Jerusalem: The Magnes Press, Hebrew University. Li, P., & Green, D. W. (2007). Neurocognitive approaches to bilingualism: Asian languages. Bilingualism: Language and Cognition, 10, 117–119. Marian, V., Spivey, M., & Hirsch, J. (2003). Shared and separate systems in bilingual language processing: Converging evidence from eye tracking and brain imaging. Brain and Language, 86(1), 70–82. Nudelman, R. (2000). Israeli society and its new search of identity (pp. 221–253). In A. D. Epstein & A. V. Fedorchenko (Eds.), Mass migration and its impact on the Israeli society. Moscow: Institute Izucheniya Izrailya i Blizhnego Vostoka [in Russian]. Olstein, A. (1995). Paper presented at a conference on Ingathering of the exiles? The impact of the 1990s’ wave of immigration on central areas of Israeli life, the Israel Sociological Society Immigrant absorption section, Tel-Aviv University [in Hebrew]. Paradis, M. (2004). Neurolinguistic theory of bilingualism. Amsterdam/Philadelphia: John Benjamins. Paradis, J. (2007). Bilingual children with specific language impairment: Theoretical and applied issues. Applied Psycholinguistics, 28, 512–564. Paradis, M., & Goldblum, M. S. (1989). Selective crossed aphasia in a trilingual aphasic patient followed by reciprocal antagonism. Brain and Language, 36(1), 62–75. Perani, D., & Abutalebi, J. (2005). The neural basis of first and second language processing. Current Opinion in Neurobiology, 15, 202–206. Proverbio, A. M., Cok, B., & Zani, A. (2002). Electrophysiological measures of language processing in bilinguals. Journal of Cognitive Neuroscience, 14, 994–1017. Saiegh-Haddad, E. (2003). Linguistic distance and initial reading acquisition: The case of Arabic diglossia. Applied Psycholinguistics, 24, 115–135. Sarfarazi, M., & Sedgwick, E. M. (1996). Event related potentials (ERP) as a function of language processing in bilinguals. Electroencephalography and Clinical Neurophysiology, 99(4), 347. Shuval, J. T. (1999). Israel in the context of post industrial migration: The mythology of ‘‘Uniqueness’’. In W. Weil (Eds.), Roots and routes: Ethnicity and migration in global perspective (pp. 225–245). Jerusalem: The Magnes Press, Hebrew University.

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Chapter 2

Relevance of the Linguistic Coding Difference Hypothesis to English as an Additional Language of Literacy in Israel Janina Kahn-Horwitz, Richard L. Sparks, and Zahava Goldstein

2.1 Introduction Children studying in Israeli schools, as in most other countries where English is not a first language, begin acquiring English as a second or additional language (EAL) in elementary school. English is considered an important subject of study and a passport to future success in higher education, business and travel (Ministry of Education, 2001). In Israel, the majority of the school-going population is comprised of children for whom Hebrew is their first language (L1). Arabic is the official second language of Israel. The largest minority group in Israel are Arabic L1 speaking children, and alongside this group there are numerous originally immigrant minority groups including Russian, Amharic, French, and Spanish L1 speaking children. For the aforementioned groups, English will be a third or fourth language. In this research, only Hebrew L1 students acquiring EAL literacy were tested. Hebrew L1 speaking children will have, for the most part, acquired at least 2 years of Hebrew literacy before they start acquiring EAL literacy. During the 9 to 12 years of formal EAL studies at school,1 children continue developing their literacy ability so that by the time they complete school and enter tertiary education they are expected to be able to read and comprehend EAL academic articles. The purpose of the present study was to examine processes that contribute to successful reading in an additional language in ninth grade by examining both L1 Hebrew as well as EAL reading components regarding their predictive ability from a longitudinal perspective.

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Although English literacy instruction begins in third or fourth grade in Israel with instruction in letter sound and name knowledge, some local municipal areas and/or schools may begin oral English instruction from first grade. J. Kahn-Horwitz (*) Oranim Academic College of Education, Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, University of Haifa, Haifa, Israel e-mail: [email protected] M. Leikin et al. (eds.), Current Issues in Bilingualism, Literacy Studies 5, DOI 10.1007/978-94-007-2327-6_2, Ó Springer ScienceþBusiness Media B.V. 2012

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Models of word recognition take into account orthographic specific characteristics that influence word recognition (Frost, 2005). Hebrew is a Semitic language and it can be read either with or without vowels, which include diacritical marks inserted above or below the letters. This distinguishes Hebrew vowels both orthographically and phonemically from English vowels. As opposed to Hebrew vowels, English vowels have the same orthographic status as other letters in the alphabet and phonemically Hebrew vowels do not have a short long distinction. The voweled version of the Hebrew orthography, which is acquired and used by elementary school children in their first 2 years of reading acquisition, can be decoded by direct grapheme-phoneme translation making it a relatively transparent or regular alphabetic orthography. It is less transparent for encoding as there are numerous graphemes that represent a number of the phonemes such as tet/taf, kuf/kaf, xaf/xet and aleph/ayin (Frost, 2005; Geva, Wade-Woolley, & Shany, 1993). Without vowels, the Hebrew orthography, which historically is essentially a consonant-based syllabary, is significantly more opaque, and accurate decoding depends on utilizing morphological, semantic and contextual information in order to fill in incomplete phonological information. The English orthography is considered opaque for both decoding and encoding for two central reasons. The first reason is that irregular words do not follow orthographic conventions in terms of their grapheme-phoneme correspondences (e.g., who, one), and the second reason is inconsistency in the resulting phonemes that particular orthographic patterns in different words result in (e.g., ough in through, enough and bought) (Frost, 2005; Seymour, Aro, & Erskine, 2003). Experience with specific L1 word recognition processes may impact on EAL word recognition as well as EAL comprehension (Koda, 1995). According to a simple model of reading (Koda, 2005) reading comprehension in a first language is dependent on accurate and fluent word recognition together with listening comprehension. A limited-capacity theory explains how these two automatic lower level processes free cognitive resources to process higher level reading comprehension processes (Koda, 1992). Similar processes are required for second or foreign language (L2) reading comprehension (Koda, 1996). L2 reading acquisition is largely dependent on underlying linguistic abilities as well as processing speed, which first impacted on first language (L1) reading acquisition (Kahn-Horwitz, Shimron, & Sparks, 2005; Sparks & Ganschow, 1993a, 1993b; Sparks, 1995). Underlying linguistic abilities impacting reading acquisition include phonological awareness, which together with knowledge of letter sounds and names, constitute the alphabetic principle. This is a crucial precursor of reading acquisition in first and additional languages (Muter & Diethelm, 2001). Phonological awareness facilitates reading in that it enables readers to associate phonemes with graphemes and synthesize the phonemes to form words, a process referred to as phonological recoding (Adams, 1990; Hagiliassis, Pratt, & Johnston, 2006; Oloffson & Niedersoe, 1997; Share, 1995). Phonological awareness has been

2

Relevance of the Linguistic Coding Difference Hypothesis to English . . .

23

found to transfer across orthographies (Cisero & Royer, 1995; Comeau, Cormier, Grandmaison, & Lacroix, 1999; Dufva & Voeten, 1999; Durgunoglu, Nagy, & Hancin-Bhatt, 1993; Kahn-Horwitz et al., 2005; Wade-Woolley, Chiappe, & Siegel, 1998). Phonological awareness has been found to be the strongest predictor of word reading for EL1 and EAL first to fourth graders (Jongejan, Verhoeven, & Siegel, 2007) as well as showing longitudinal effects for kindergarten to sixth grade EAL students (together with RAN and oral language measures) (Nakamato, Lindsey, & Manis, 2007). Together with oral Hebrew ability, phonological awareness accounted for L2 Hebrew reading amongst Russian-Hebrew bilinguals (Leikin, Share, & Schwartz, 2005) and when measured in Spanish L1 phonological awareness has also been found to predict reading comprehension in English L2 amongst elementary school Spanish-English bilinguals and biliterates (Carlisle, Beeman, Hull Davis, & Sphraim, 1999). The direct relationship between phonology and comprehension is explained by incoming information being stored temporarily in the phonological loop component of working memory (Baddeley, 2006). If there is a disruption in this temporary storage of information, there will be a faulty flow of information to the long term memory function. The phonological loop component of working memory is thus vital to L1 as well as additional language vocabulary acquisition (Gathercole & Thorn, 1998) and subsequently reading comprehension in the respective languages (Koda, 2005). Together with phonological processing, orthographic processing is a crucial component of word decoding and encoding. Orthographic processing entails using visual-orthographic input from words for the purposes of word recognition (Ehri, 1992; Nassaji & Geva, 1999). Novice readers depend more on phonological processing to decode words and as these words become more frequent for these readers, orthographic processing is used to directly access them from the lexicon (Share, 1995; Share & Stanovich, 1995). Lexical access is the ability to automatically access oral vocabulary from memory and is measured by rapidly naming numbers, letters, pictures or colors. There is a strong connection between this ability and reading for younger EL1 students and for younger and older EAL elementary school students (Gholomain & Geva, 1999; Jongejan et al., 2007; Nakamato et al., 2007). Oral vocabulary is stored phonologically in memory making this task a phonological processing task. However, it measures a qualitatively different dimension of phonological processing from phonological awareness tasks which measure the ability to manipulate phonemes thereby facilitating decoding and encoding (Hagiliassis et al., 2006). Morphological awareness requires sensitivity to the meaningful components of words and can assist in word recognition, lexical access, and reading comprehension for L1 (Oloffson & Niedersoe, 1997) and L2 (Parel, 2004) readers. Morphological awareness measured in Hebrew L1 predicted EAL decoding as well as reading comprehension amongst fourth graders after their first year of EAL literacy acquisition (Kahn-Horwitz et al., 2005).

24


Theories that explain the impact of underlying abilities on additional reading acquisition and development include the Linguistic Coding Differences Hypothesis (LCDH) (Sparks & Ganschow, 1993a), the Central Processing Hypotheses (Geva & Siegel, 2000) and the Interdependence Hypothesis (Cummins, 1984). These theories explain that linguistic codes, or abilities, measured in L1 explain individual differences in additional language literacy acquisition. In the present study, we question whether after numerous years of additional language learning when the language learner is no longer at the initial stage of reading acquisition, linguistic codes measured in L1 still explain differences in EAL reading. Alternatively, do abilities measured in the EAL itself become predictors of the more skilled EAL reader? If so, this finding would show evidence for a threshold hypothesis whereby EAL abilities predict EAL reading comprehension (Leikin et al., 2005; van Gelderen, Schoonen, Stoel, & de Glopper, 2007). Sparks, Patton, Ganschow, Humbach, and Javorsky (2008) found longitudinal evidence for L1 literacy abilities measured in elementary school successfully predicting second language literacy abilities measured in 9th and 10th grade after one and then 2 years of second language study. In another study with L2 learners in high school, they found that L1 skill differences in reading and spelling emerged early in elementary school (Sparks, Ganschow, & Patton, 2008; Sparks, Patton, Ganschow, & Humbach, 2009). Their studies examined English L1 speakers acquiring additional alphabetic languages (German, Spanish and French). The present study reports on ninth grade Hebrew L1 speakers in their sixth year of English as an additional language study. This lengthier formal exposure to English as an additional language may have changed the relationship between L1 literacy related abilities and EAL literacy abilities.

2.1.1 The Present Study The aim of the present study was to address the relevance of the LCDH after almost 6 years of EAL instruction. In other words, do linguistic abilities measured in L1 Hebrew in fourth grade and again in ninth grade still predict EAL word reading and reading comprehension measured at the end of ninth grade? In the case of the present study, we examined students for whom Hebrew is their first spoken and literate language. After having acquired the transparent voweled Hebrew orthography in first and second grades, students in third grade began reading and spelling the more opaque unvoweled Hebrew consonant-based syllabic orthography with less phonological information. In fourth grade these same students began acquiring the more opaque English orthography with its relative inconsistency and irregularity (Frost, 2005). The present study aimed to examine whether long term transfer of L1 literacy abilities would still be observed when long term EAL predictors were included as predictors.

2


25

2.2 Method 2.2.1 Participants Participants were 77 ninth graders from the north of Israel who were part of an original study consisting of 145 children (Kahn-Horwitz et al., 2005; KahnHorwitz, Shimron, & Sparks, 2006) and participated in this study 5 years earlier in fourth grade. The original participants in the study came from schools in three different areas, representing two different socio-economic status backgrounds (SES) (Kahn-Horwitz et al., 2006). At the beginning of seventh grade, participants in the original study started junior high school and participants from two of the schools were dispersed amongst numerous high schools in various areas, making it difficult to locate them towards the end of ninth grade. Most of the participants from one of the three original schools in a middle SES area continued studying at the adjoining junior high school. Of the original 96 participants in this high school, 77 agreed to take part in this follow up study. Their participation was dependent on parental consent. Of the 77 participants in the study, 42 were males and 35 were females. Their mean age was 15 years, 1 month. All participants had been formally studying EAL for 4 weekly hours over a period of 6 years.

2.2.2 Measures The following L1 measures were administered in order to examine whether abilities associated with L1 reading ability will also longitudinally predict EAL reading ability. 2.2.2.1 Independent L1 (Hebrew) Measures 1. Phonological awareness was assessed using a phoneme deletion task (Shany, Zieger, & Ravid, 2001), which is a Hebrew version of the Rosner phoneme deletion task. Participants were required to repeat a word that the tester pronouncedRand then delete an initial, medial or final phoneme from R that word, e.g., / elet/ (Hebrew for ‘‘sign’’) and then delete the phoneme / /. The participant was then required to pronounce the resulting pseudo-word /elet/. The maximum score for this task was 20 (range 0–20). Participants were tested on this task at the beginning and end of fourth grade and at the end of ninth grade. 2. Morphological awareness was assessed using a production task (Ben-Dror, Bentin, & Frost, 1995). The tester pronounced a word root and then participants completed a sentence provided by the tester with the appropriate e.g., lamad (Hebrew for ‘‘studied’’ /masc./sg.) – ‘‘Ha’yeled Rderivation, R eyo ev kan hu ha’_________’’ (Hebrew for ‘‘The boy who is sitting here is the ____’’). The student had to complete the sentence with talmid (Hebrew

26

3.

4.

5.

6.

7.

8.


for ‘‘pupil’’/masc./sg.). The maximum score for this task was 15 (range 0–15). Participants were tested on this task at the beginning and end of fourth grade. A spelling dictation consisting of single Hebrew words (which were pronounced as single words and then in the context of a sentence) and two sentences were dictated to the fourth graders (see Kahn-Horwitz et al., 2005). The maximum score for this task was 25 (range 0–25). Participants were tested on this task at the beginning and end of fourth grade. The scores of the beginning and end of fourth grade spelling tests were combined based on their correlation (r ¼ 0.80, p < 0.001). A spelling dictation that (Shany et al., 2001) consisted of 43 words was dictated to participants. Participants heard each word pronounced, followed by a contextual sentence and again the key word. They thereafter wrote the word, e.g., nikneta (Hebrew for ‘‘was bought’’ /fem./sg.). The maximum score for this task was 43 (range 0–43). Participants were tested on this task at the end of ninth grade. The fourth and ninth grade spelling dictations were combined based on their correlation (r ¼ 0.61, p < 0.001). A word reading cluster was administered at the beginning and end of fourth grade, which consisted of a word recognition task (Balgur, 1977) testing accuracy and speed (beginning of fourth grade correlation between word recognition accuracy and speed r ¼ 0.36, p < 0.01; end of fourth grade correlation between accuracy and speed r ¼ 0.16, ns), and a word attack task measuring phonological recoding (Greenbaum & Lichter, 1996), which were combined based on their Pearson 2-tailed correlation coefficients (beginning of fourth grade word recognition with word attack accuracy r ¼ 0.71, p < 0.01; end of fourth grade word recognition with word attack accuracy r ¼ 0.70, p < 0.01, and beginning of fourth grade word attack and word recognition speed r ¼ 0.21, p < 0.05; and end of fourth grade word attack and word recognition speed r ¼ 0.27, p < 0.05). At the end of ninth grade, the Greenbaum and Lichter (1996) Hebrew Word Attack task measuring phonological recoding which consists of 25 nonwords following the phonotactic conventions of the Hebrew language, e.g., vasug, was again administered. Both speed (in seconds) and accuracy (maximum score ¼ 25) was checked (range 0–25). At the end of ninth grade a task measuring rapid automatic naming of letters in Hebrew was administered (Shany et al., 2001). Each participant was asked to name accurately and rapidly five Hebrew letters. The letters were: ‫ל‬, ‫ג‬, ‫ד‬, ‫א‬, ‫ – ס‬samex, alef, daled, gimel, lamed. A vocabulary cluster (Glantz, 1991) consisting of an antonyms and synonyms task was administered at the beginning and end of fourth grade and a more advanced version was administered at the end of ninth grade (Pearson 2-tailed correlation coefficients between beginning of fourth grade antonym and synonym tasks r ¼ 0.43, p < 0.001; Pearson 2-tailed correlation coefficients between end of fourth grade antonym and synonym tasks r ¼ 0.27, p < 0.001; Pearson 2-tailed correlation coefficients between end of ninth

2


27

grade antonym and synonym tasks r ¼ 0.42, p < 0.001). In the tasks participants saw and heard a key word followed by a series of 4–5 words of which they were required to choose the appropriate synonym or antonym. The maximum score for antonyms and synonyms in fourth grade was 12 (range 0–12). The maximum score for antonyms and synonyms in ninth grade was 20 (range 0–20).

2.2.2.2 Independent EAL (English) Measures 1. An English letter knowledge cluster consisting of a measure of knowledge of English letter names and sounds was administered at the beginning and end of fourth grade. Participants were required to name and pronounce the sound of each of the 26 English letters presented in a random manner (Pearson 2-tailed correlation coefficients between beginning of fourth grade knowledge of sounds and names of English letters r ¼ 0.96, p < 0.01; Pearson 2-tailed correlation coefficients between end of fourth grade knowledge of sounds and names of English letters r ¼ 0.95, p < 0.01). The scores for both sounds of letters and names of letters was 0–26. 2. Word Reading – At the end of fourth grade the following three tasks were administered: a. An informal measure with 20 words that the fourth graders had been exposed to during their first year of EAL studies (e.g., stop, farm, number) was presented to the students (see Kahn-Horwitz et al., 2005). Each student was requested to read all 20 words aloud. The maximum score for this task was 20 (range 0–20). b. The Woodcock Reading Mastery Test-Revised (1987), Form H: Word Recognition sub-test was administered. Students read word after word aloud and stopped reading after six consecutive errors. c. The Woodcock Reading Mastery Test-Revised, Form H: Word Attack sub-test was administered. Students read each of the non-words aloud and stopped reading after six consecutive errors. The above tasks were combined to form a word reading cluster based on their Pearson 2-tailed correlation coefficients, which yielded the following correlations: informal measure and Woodcock Word Recognition (r ¼ 0.87, p < 001), informal measure and Woodcock Word Attack (r ¼ 0.87, p < 001), Woodcock Word Recognition and Woodcock Word Attack (r ¼ 0.85, p < 001). 3. Spelling – At the end of fourth grade, the following two tasks checked basic EAL spelling: a. Students were asked to write graphemes representing eight phonemes. The maximum score was 8 (range 0–8). b. Students were asked to write a short sentence consisting of eight frequent words. The sentence was Look at the black cat in the tree (range 0–8).

28


These two tasks were combined into a spelling cluster based on Pearson 2-tailed correlation coefficients r ¼ 0.59, p < 0.001. c. At the end of ninth grade, three English sentences were dictated to the participants. The sentences consisted of words taken from ninth grade text books (Assis, 2002; Ezra & Kerman, 1998), e.g., Last year he taught computer technology. Participants first heard the entire sentence read twice and then the tester dictated chunks of two to three words at a time. Participants were required to write the sentences. The maximum score for this sub-test was 25 (range 0–25). The overall fourth and ninth grade spelling tasks were combined into a spelling cluster based on Pearson 2-tailed correlation coefficients r ¼ 0.58, p < 0.001. 4. Vocabulary – At the end of fourth grade the following vocabulary tasks were administered: a. A single word vocabulary identification task was completed by the students. They were presented with a page including ten items. The tester read ten target words aloud and the students circled the appropriate picture (out of 4 possible options) that represented the word they heard, e.g., they heard the word horse and had to circle the appropriate picture amongst pictures of man, bag, horse, table. The maximum score for this task was 10 (range 0–10). b. A simple sentence comprehension task was completed by students. They circled the appropriate picture representing the simple sentence they heard, e.g., Three children are playing. The maximum score for this task was 15 (range 0–15). These two tasks then were combined into a vocabulary cluster based on Pearson 2-tailed correlation coefficients r ¼ 0.68, p < 0.001. At the end of ninth grade, three English vocabulary tasks were administered. They were designed using 60 vocabulary items from two ninth grade EAL text books (Assis, 2002; Ezra & Kerman, 1998). Fifteen ninth grade EAL teachers were asked to grade word frequency of these words amongst ninth graders by giving a grade of one to five, whereby one represented a very infrequent word and five represented a very frequent word. Each word was then given a cumulative score and three separate lists were created to be equivalent from a frequency perspective, with the most frequent words being earlier in the lists progressing towards less frequent words. c. The first sub-test was a passive vocabulary recognition task whereby the student heard and saw a key word followed by five possible Hebrew translations. One of the five options was the accurate translation; the second was a Hebrew foil, which was the same part of speech as the key word; the third had the same opening phoneme as the key word; the fourth option’s translation into English had the same opening phoneme as the key word; and the fifth either rhymed with or was morphologically similar to the Hebrew translation of the key word, e.g., bridge (key word) – a. R delet (English – door: same part of speech) b. ne er (English – eagle

2


29

(masc./sg.): morphologically similar to Hebrew translation) c. mevi (English – bringR (masc./sg.): translation has same opening phonemes as key word) d. ge er (English – bridge (masc./sg.): accurate translation) e. brit (fem./sg.)(English – pact: Hebrew foil has same opening phonemes as key word). The maximum score for this measure was 20 (range 0–20). d. The second sub-test was a contextualized vocabulary recognition task. In this sub-test, the student saw and heard a key word followed by a contextual sentence and then heard the key word repeated again. The participant was required to say aloud the Hebrew translation for the English key word e.g., key word: danger, contextual sentence: Fire can be a danger. The maximum score for this sub-test was 20 (range 0–20). e. The third sub-test was a de-contextualized vocabulary recognition task. In this sub-test, the student heard and saw the key word and had to then say aloud the Hebrew translation for the key word, e.g., news, dry, nature. The maximum score for this sub-test was 20 (range 0–20). The three vocabulary measures were combined into a vocabulary cluster. Pearson 2-tailed correlation coefficients between these variables yielded the following results: Passive vocabulary recognition and contextualized vocabulary recognition r ¼ 0.95, p < 0.001; passive vocabulary recognition and de-contextualized vocabulary recognition r ¼ 0.93, p < 0.001; contextualized vocabulary recognition and de-contextualized vocabulary recognition r ¼ 0.96, p < 0.001. 5. Reading Comprehension – at the end of fourth grade, English reading comprehension was tested by two different short narrative texts, each followed by five multiple choice questions presented in Hebrew L1 that checked factual information as well as the overall idea of each text (see Kahn-Horwitz et al., 2005). The maximum score for this task was 10 (range 0–10). 6. Lexical Access – at the end of ninth grade a task measuring rapid automatic naming of letters was administered (Kail & Hall, 1994). Each participant was asked to name as accurately and rapidly as they could five English letters that appeared in ten different sequences. The letters were: a, d, o, p, s. Speed was measured using a stopwatch and accuracy was measured by marking off any letter incorrectly named.

2.2.2.3 Dependent EAL Measures Tested at the End of Ninth Grade 1. Word Reading – The following three tasks were administered: a. A single word recognition task (Stanovich & Siegel, 1994) consisting of 40 frequent one syllable words was presented to students. They read the words aloud. Speed was measured using a stopwatch and accuracy was measured by giving a score of 1 to each correctly read word. Maximum score for accuracy was 40 (range 0–40).

30


b. The Woodcock Reading Mastery Test-Revised, Form H: Word Recognition sub-test was presented to students and they were required to read each word aloud. After six consecutive errors, the task was ended. c. The Woodcock Reading Mastery Test-Revised, Form H: Word Attack sub-test was presented to students and they were required to read each non-word aloud. The task was discontinued after six consecutive errors. A word reading cluster was combined based on the following Pearson 2-tailed correlation coefficients: Woodcock Word Recognition and Woodcock Word Attack (r ¼ 0.70, p < 0.01); Woodcock Word Recognition and the Stanovich and Siegel Word Recognition Task (accuracy) (r ¼ 0.68, p < 0.01); Woodcock Word Recognition and the Stanovich and Siegel Word Recognition Task (speed) (r ¼ –0.49, p < 0.01); Woodcock Word Attack and the Stanovich and Siegel Word Recognition Task (accuracy) (r ¼ 0.54, p < 0.01); Woodcock Word Attack and the Stanovich and Siegel Word Recognition Task (speed) (r ¼ –0.44, p < 0.01); and the Stanovich and Siegel Word Recognition Task (accuracy and speed) (r ¼ –0.67, p < 0.01). 2. At the end of ninth grade, EAL reading comprehension was measured using three progressively graded texts designed for ninth graders by EAL teachers. Comprehension questions presented in English examined word level (semantic) comprehension, text level comprehension (detecting explicit information), global comprehension (finding the main idea), and conceptual comprehension found within the text as well as the application of background knowledge. Maximum score for the overall test was 50 (range 0–50).

2.2.3 Procedure At the beginning as well as the end of their first year of EAL studies, the first author conducted group as well as individual testing on the original fourth grade participants, which lasted a little over 1 h in a quiet room at the elementary school. The first author together with research assistants (who were all qualified English teachers studying Didactic Assessment and who received special training for using the above measures) tested each of the participants individually during the second last month of their ninth grade year. Testing took place in a quiet room in the school and lasted approximately 1 h. The phonological awareness, vocabulary and spelling tasks were measured in Hebrew (L1) at the beginning and end of fourth grade and at the end of ninth grade. Each of these three L1 measures was combined to create a mean score for phonological awareness, vocabulary knowledge and spelling ability, respectively. The morphological awareness task and the word reading cluster measured in Hebrew (L1) at the beginning and end of fourth grade was combined to create a mean score for morphological awareness and word reading, respectively.

2


31

Due to a lack of significant correlations between many of the response time and accuracy measures, a finding that has been supported by the literature whereby speeded as opposed to accuracy tasks are seen as tapping qualitatively different underlying abilities (Hagiliassis et al., 2006), stepwise regression analyses were run separately for 9th grade English word recognition accuracy results and for 9th grade English word recognition accuracy combined with response time results.

2.3 Results Means and standard deviations were calculated for each of the independent and dependent variables (see Tables 2.1 and 2.2). Correlations between the respective variables were calculated (see Table 2.3). Speeded measures often did not correlate significantly with accuracy measures. Correlations were insignificant between lexical access (L1 RAN) and the phoneme deletion measured in Hebrew. Phoneme deletion measured in Hebrew also had a non-significant correlation with the response time for Hebrew word attack. A non-significant correlation was observed between Hebrew spelling and Hebrew word reading.

Table 2.1 Descriptive data for accuracy based tasks: Means (M), standard deviations (SD), minimum (Min. score) and maximum observed scores (Max. score) and observed range of participants on the L1 and EAL measures Min. Max. Measure M SD score score Range Hebrew (L1) Measures L1 Phoneme Deletion* L1 Morphological Awareness* L1 Spelling* L1 Word Reading Cluster* L1 Vocabulary Cluster* English (EAL) Measures EAL Letter Sound and Names* EAL Spelling* EAL Word Reading Cluster – 4th grade* EAL Word Reading Cluster – 9th grade* EAL Vocabulary Cluster* EAL Reading Comprehension 4th grade EAL Reading Comprehension 9th grade * z scores

0.03 0.01 –0.03 –0.01 –0.02

0.83 0.95 0.92 0.62 0.61

–1.57 –2.69 –3.96 –1.43 –1.52

1.82 1.97 1.51 1.05 1.36

3.39 4.66 5.47 2.48 2.88

0.04 0.07 0.23

0.86 0.85 1.00

–2.12 –1.78 –1.22

1.94 1.74 2.83

4.06 3.52 4.05

0.001

0.54

–1.58

1.06

2.63

0.004 4.44

0.82 3.86

–3.15 0

1.58 10

4.73 10

50

50

35.12

12.28

0

32


Table 2.2 Descriptive data for speed based tasks: Mean response time in seconds (M) and standard deviations (SD) of participants on the L1 and EAL measures Measure M SD L1 Word Attack Speed L1 Rapid Automatic Naming EAL Word Reading Cluster – 9th gradea EAL Word Reading Cluster incl. speed – 9th gradea EAL Rapid Automatic Naming a

25.93 22.41 0.001 0.01 21.18

11.56 3.76 0.50 0.51 4.09

z score

Separate stepwise regression analyses were conducted to determine whether and to what extent L1 variables measured in fourth grade and again in ninth grade (separately and then together) predicted EAL word reading and EAL reading comprehension (measured at the end of ninth grade). The results of these analyses would provide an answer regarding the extent that the Linguistic Coding Differences Hypothesis is relevant to students studying EAL for 6 years. Another set of separate analyses were conducted that combined both L1 and EAL measures tested in fourth and ninth grade to determine whether and to what extent L1 measures predicted EAL word reading and reading comprehension when they were entered together with EAL measures.

2.3.1 L1 Measures in Fourth Grade Predicting EAL Word Reading Accuracy in Ninth Grade The stepwise regression analysis yielded a one-variable model whereby phonological awareness measured in fourth grade accounted for 25% of the variance (b ¼ 0.50), F (1, 76) ¼ 24.61, p < 0.001.

2.3.2 L1 Measures in Fourth Grade Predicting EAL Word Reading in Ninth Grade Including the Speeded Reading Measure The stepwise regression analysis yielded a one-variable model whereby morphological awareness measured in fourth grade accounted for 6% of the variance (b ¼ –0.25), F (1, 76) ¼ 5.20, p < 0.05.

2.3.3 L1 Measures in Fourth and Ninth Grade Predicting EAL Word Reading in Ninth Grade Including the Speeded Reading Measure The stepwise regression analysis yielded a one-variable model whereby rapid automatic naming of Hebrew letters measured in ninth grade accounted for 11% of the variance (b ¼ 0.33), F (1, 75) ¼ 9.30, p < 0.01.

0.18

–

–0.27*

–

9

–

10

11

12

13

–0.16

0.14

0.49** –0.02

0.45** 0.37** –0.12

–0.17

0.48** .37**

0.04

0.13

–0.19

–0.17

–0.15

0.27*

0.47** 0.63** 0.37** 0.57** – –

15

–0.36** 0.61** 0.63** 0.42** 0.74** 0.50** –0.15

0.51**

–0.19

14

–

16

17

–0.30** –0.45** 0.44** 0.62** 0.54** 0.52** 0.44** –0.44** 0.40** –

–0.26*

0.33**

0.43** 0.47** –0.28* 0.01

0.41** 0.37** –0.17

–0.25* –0.14

0.40** 0.29*

0.45** 0.51** 0.52** 0.14

0.02

0.60** 0.19

0.51** 0.50** 0.65** 0.26* 0.60** 0.59** –0.20 –0.30** –0.44** 0.74** – 0.51** 0.65** 0.56** 0.22* 0.66** 0.30** –0.03 –0.20 –0.23* 0.56** 0.55** – 0.54** 0.49** 0.56** 0.33** 0.61** 0.56** –0.24* –0.24* –0.39** 0.82** 0.80** 0.55** –

–0.22

–0.17

–0.23* –0.12

8

0.53** 0.53** 0.49** 0.37** 0.59** 0.53** –0.12

0.06

–

7

0.57**

–0.09

6

– 0.66** – 0.43** 0.44** – –0.26* –0.21 –0.18

5

–0.23* 0.15

–0.15

–0.07

– 0.11 0.49** 0.35** –0.16

4

Table 2.3 Intercorrelations between L1 and EAL measures

–0.23* –0.25* –0.23* 0.11

0.59** 0.10 0.47** 0.10 –0.15

0.50** 0.31** 0.49** 0.38** –0.14

3


* p < 0.05; ** p < 0.01

–

1. L1 Phoneme deletion 2. L1 Morphological awareness 3. L1 Spelling 4. L1 Word reading 5. L1 Vocabulary 6. L1 Word attack 7. L1 Word attack speed 8. L1 Rapid automatic naming 9. EAL Rapid automatic naming 10. EAL Letter sounds and names 11. EAL spelling 12. EAL vocabulary 13. EAL word reading 4th grade 14. EAL word reading 9th grade 15. EAL word reading speed 9th grade 16. EAL Reading comprehension 4th grade 17. EAL Reading comprehension 9th grade

2

0.51** –

1

MEASURE

2 33

34


2.3.4 L1 Measures in Fourth and Ninth Grade Predicting EAL Word Reading Accuracy in Ninth Grade The stepwise regression analysis yielded a two-variable model whereby the overall phonological awareness task and the overall Hebrew word reading task together accounted for 42% of the variance. Phonological awareness (b ¼ 0.60), F (1, 75) ¼ 41.23, p < 0.001 explained 35% of the variance and the Hebrew word reading task (b ¼ 0.28) F change (1, 74) ¼ 8.62, p < 0.01 explained an additional 7% of the variance.

2.3.5 L1 Measures in Fourth Grade Predicting EAL Reading Comprehension in Ninth Grade The stepwise regression analysis yielded a two-variable model whereby the Hebrew fourth grade vocabulary cluster and the Hebrew fourth grade spelling cluster together accounted for 25% of the variance. The Hebrew vocabulary cluster (b ¼ 0.44), F (1, 76) ¼ 18.17, p < 0.001 accounted for 19% of the variance and the Hebrew spelling cluster (b ¼ 0.29), F change (1, 75) ¼ 6.32, p < 0.05 accounted for a further 6% of the variance.

2.3.6 L1 Measures in Fourth and Ninth Grade Predicting EAL Reading Comprehension in Ninth Grade The stepwise regression analysis yielded a three-variable model whereby the Hebrew spelling task, the phonological awareness task and the ninth grade rapid automatic naming task of Hebrew letters together accounted for 37% of the variance. The Hebrew spelling task (b ¼ 0.49), F (1, 75) ¼ 23.62, p < 0.001 explained 24% of the variance. The rapid automatic naming task of Hebrew letters (b ¼0.26), F change (1, 74) ¼ 7.12, p < .01 explained an additional 7% of the variance and the phonological awareness task (b ¼ 0.29), F change (1, 73) ¼ 7.14, p < 0.01 explained a further 4% of the variance.

2.3.7 L1 and EAL Measures in Fourth and Ninth Grade Predicting EAL Word Reading Accuracy in Ninth Grade The stepwise regression analysis yielded a six-variable model whereby the overall English spelling measure, the overall Hebrew phonological awareness measure, the ninth grade Hebrew rapid automatic naming task, the ninth grade Hebrew word attack (speed) task, the overall Hebrew fourth grade morphological awareness task and the English fourth grade reading comprehension task

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together accounted for 60% of the variance. The overall English spelling measure (b ¼ 0.62), F (1, 75) ¼ 48.75, p < 0.001 accounted for 39% of the variance, the overall Hebrew phonological awareness measure (b ¼ 0.35), F change (1, 74) ¼ 13.27, p < 0.001 accounted for an additional 9% of the variance. The ninth grade Hebrew rapid automatic naming task (b ¼ 0.22), F change (1, 73) ¼ 4.07, p < 0.05 accounted for an additional 3% of the variance. The ninth grade Hebrew word attack (speed) task (b ¼ –0.18), F change (1, 72) ¼ 4.70, p < 0.05 accounted for a further 3% of the variance. The Hebrew fourth grade morphological awareness measure (b ¼ –0.23), F change (1, 71) ¼ 4.30, p < 0.05 accounted for a further 3% of the variance. Finally, the English fourth grade reading comprehension task (b ¼ 0.23), F change (1, 70) ¼ 4.98, p < 0.05 accounted for an additional 3% of the variance.

2.3.8 L1 and EAL Measures in Fourth and Ninth Grade Predicting EAL Speeded Word Reading in Ninth Grade The stepwise regression analysis yielded a one-variable model whereby rapid automatic naming of English letters measured in ninth grade accounted for 25% of the variance (b ¼ 0.50), F (1, 74) ¼ 25.11, p < 0.001.

2.3.9 L1 and EAL Measures in Fourth and Ninth Grade Predicting EAL Reading Comprehension in Ninth Grade The stepwise regression analysis yielded a three-variable model whereby the overall English vocabulary measure, the ninth grade rapid automatic naming task of English letters and the overall phonological awareness task (measured in Hebrew) together accounted for 62% of the variance. The English vocabulary task (b ¼ 0.54), F (1, 75) ¼ 30.88, p < 0.001 explained 29% of the variance. English word reading speed (b ¼ 0.36), F change (1, 74) ¼ 15.85, p < .001 explained a further 13% of the variance. English word reading accuracy (b ¼ 0.47), F change (1, 73) ¼ 29.00, p < 0.001 explained a further 17% of the variance. Finally, Hebrew word reading (b ¼ 0.19), F change (1, 72) ¼ 6.20, p < 0.01 explained 3% of the variance.

2.4 Discussion The research question in this longitudinal study of ninth grade EAL students examined the extent to which first language (Hebrew) and additional language (English) linguistic and literary abilities measured up to 6 years earlier and concurrently predicted EAL word recognition and reading comprehension.

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2.4.1 The Relevance of the LCDH to EAL Word Recognition from a Longitudinal Perspective Two measures were constructed for measuring EAL word recognition at the end of 9th grade. One measure was a cluster of English word reading measures including speeded reading and the other was the cluster of English word reading independent of speeded reading. A rationale for splitting these two abilities is suggested by Hagiliassis et al. (2006), who provide evidence that supports a separate construct being measured when examining task accuracy as opposed to task response time. Support for this rationale in the present research was provided by insignificant correlations between RAN and phonological awareness as well as word attack speed and phonological awareness. Phonological awareness measured in L1 Hebrew in fourth grade accounted for 25% of the explained variance of EAL word recognition at the end of ninth grade. This finding provides evidence for cross-language transfer of phonological awareness skills as predicting word reading accuracy that has been supported by other research (Comeau et al., 1999; Jongejan et al., 2007; Kahn-Horwitz et al., 2005; Nakamato et al., 2007). In the case of the present study there is a longitudinal dimension of almost 6 years to the transfer. Morphological awareness measured in L1 Hebrew in fourth grade accounted for 6% of the explained variance of EAL speeded word reading. In other words, sensitivity towards the morphological structure of the L1 directly contributed almost 6 years later to the speed of English word reading. When ninth grade L1 predictors were added to the fourth grade L1 Hebrew predictors, a combination of phonological awareness measured in L1 Hebrew together with Hebrew word reading accounted for 42% of the explained variance. These results are remarkably similar to Sparks et al. (2008) findings in their longitudinal study that 43% of the explained variance of word reading in Spanish, German and French was explained by English L1 word reading. The finding in the present study that most of the 42% of explained variance comprised of phonological awareness measured in Hebrew may point to the differences in word recognition strategies in two opaque orthographies with different characteristics; that is, the opaque Hebrew orthography lacks complete phonological information as opposed to the opaque English orthography, which shows a relative degree of inconsistency and irregularity (Frost, 2005). It could be that due to the characteristics of the English orthography the ninth graders use a phonological strategy to decode the EAL words that they used when originally decoding voweled Hebrew words with their diacritics appearing above, below or inside the consonant letters. This use of a phonological strategy may occur despite the phonemic differences between English and Hebrew vowels which may require different processing strategies. When ninth grade L1 predictors were added to the fourth grade L1 predictors, RAN of Hebrew letters accounted for 11% of the explained variance of the English speeded word reading measure. This could be evidence of the direct impact of a speeded naming task on a speeded word reading task from a crosslanguage perspective.

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When English predictors were added to the fourth and ninth grade Hebrew predictors, 60% of the explained variance of English word reading accuracy was explained by the English spelling cluster, which contributed 39% of the 60% explained variance. This finding reflects the strong connection between spelling and reading in the opaque English orthography. In contrast with the lack of correlation found between Hebrew spelling and Hebrew word recognition in the earlier grades, this finding may provide support for Hebrew spelling being more opaque than Hebrew voweled reading (Geva et al., 1993). Spelling is the more productive expression of decoding. Spelling is also strongly associated with meaning and this is particularly salient in an opaque orthography such as English. English spelling is considered an extremely challenging task for additional language learners. Because good reading comprehension is considered one of the primary tasks of EAL acquisition in Israel, spelling instruction is often considered less of a priority. The above mentioned results confirm the interdependence of word reading and spelling and suggest that these skills are two sides of the same coin and may strengthen one another. Phonological awareness measured in Hebrew once again appeared as a significant contributor of a further 9% of the explained variance. The finding that rapid automatic naming of Hebrew letters and speed of non-word reading in Hebrew contributed small but significant amounts (3% each) of the variance suggests cross language transfer of speeded naming and word reading for accurate English word recognition. Morphological awareness measured in Hebrew in fourth grade contributed a further 3% of the variance, which combines with phonological awareness and the two speeded measures in Hebrew to support the relevance of the LCDH, or cross-language transfer of L1 abilities from a longitudinal and concurrent perspective. In other words, underlying L1 abilities still predict English word reading accuracy 6 years after the beginning of English acquisition. These factors might reflect Koda’s (2005) description of transferred L1 competencies continuing to develop and impacting on L2 word recognition processing with its respective orthographic specifications. The final predictor of English word reading accuracy at the end of 9th grade was English reading comprehension measured at the end of 4th grade. This English reading comprehension task could represent the semantic dimension of word recognition in an opaque orthography whereby correct word identification is directly connected to a lexical association. This finding may be seen as evidence of a bootstrapping process whereby fourth grade English reading comprehension predicted ninth grade English word recognition, which subsequently impacts on higher level English reading comprehension. This aforementioned model possibly illustrates the interface of L1 and EAL components underlying EAL word recognition (Koda, 2005). The analysis of English and Hebrew predictors of the speeded English word reading task yielded a one variable model in which rapid automatic naming of English reading accounted for 25% of the explained variance. In this case because English predictors were added into the regression, their predictability increased and they predicted greater variance than when the Hebrew variables

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were entered alone (in that case, rapid automatic naming of Hebrew letters accounted for 11% of the explained variance).

2.4.2 The Relevance of the LCDH to EAL Reading Comprehension from a Longitudinal Perspective Hebrew vocabulary knowledge together with Hebrew spelling ability measured in fourth grade accounted for 25% of the explained variance of EAL reading comprehension. These results show an interesting variation of support for the simple model of reading (Koda, 2005) from a cross language and longitudinal perspective. Hebrew vocabulary knowledge, which accounted for 19 out of the 25% of variance, represents L1 understanding which longitudinally shows transfer effects to the additional language for the purpose of reading comprehension. Hebrew spelling ability, which represents the more opaque dimension of Hebrew literacy (see Geva et al., 1993) may tap a similar cognitive functioning for reading an opaque orthography that is required for automatic English word recognition when reading a text. When ninth grade L1 Hebrew measures were added to the fourth grade L1 Hebrew measures, 37% of the variance was jointly accounted for by Hebrew spelling (24%), phonological awareness (4%) and RAN of Hebrew letters (7%). These results support the relevance of the LCDH in that EAL reading comprehension was predicted by the components that comprise accuracy (phonological awareness), fluency (RAN) and spelling which in Hebrew implicates orthographic, morphological and semantic knowledge, all from a cross linguistic perspective. Sparks et al. (2008) found that reading comprehension in English L1 accounted for 25% of the explained variance of Spanish, German and French reading comprehension. Their model comprised one component whereas the findings in this study comprised various components. When English predictors were added to the fourth and ninth grade Hebrew variables, 62% of the explained variance of EAL reading comprehension was explained by English vocabulary knowledge (29%), English word reading speed (13%), English word reading accuracy (17%) and Hebrew word reading (3%). In other words, when English predictors were added to the original L1 predictors, English vocabulary knowledge together with English word reading (accuracy and speed) were the main predictors of English reading comprehension supporting a simple model of reading (Koda, 2005). The impact of Hebrew remains whereby Hebrew word reading is a significant predictor of EAL reading comprehension. In sum, the present research provides longitudinal support for the Linguistic Coding Differences Hypothesis. Fourth grade Hebrew L1 measures when entered without English measures predicted EAL word recognition or reading comprehension. When entered together with ninth grade Hebrew measures, their prediction value increased.

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2.4.3 The Role of Phonological Awareness in Predicting EAL Word Recognition and Reading Comprehension It is of interest that at this more advanced stage of EAL literacy development, a phoneme deletion task measured in L1 should have still remained a predictor. It may be that because we are looking at Hebrew L1 students whose L1 processing experience involves reading an opaque orthography with incomplete phonological information and are acquiring and developing their abilities in an opaque orthography with irregular and inconsistent features, phonological awareness remains a predictor of EAL literacy abilities. More finely grained studies looking at these cross-orthographic differences comparing EAL readers from varied orthographic backgrounds may shed light on this question.

2.5 Conclusion This research supports the LCDH as a viable hypothesis for predicting EAL literacy from a longitudinal perspective. When coupled with EAL predictor variables, there is greater explained variance for word reading and reading comprehension, which is accounted for by a mixture of L1 and EAL component measures. The simple model of reading is supported by this research whereby EAL reading comprehension is predicted by concurrent EAL vocabulary knowledge, EAL word recognition as well as cross-linguistic transfer of Hebrew word recognition. Regarding the connection between spelling and word recognition, in the present research, the students were not first language English speakers but rather EAL students, which underscores the importance of developing good spelling for efficient word recognition and understanding. An important educational implication from this finding is that more emphasis should be placed on developing English spelling in the EAL classroom. In Israel, this skill is often a neglected pedagogical dimension, particularly because reading is considered more of a priority and English writing is considered secondary, a luxury of the more advanced learner. The results of this research demonstrate the strong interdependence between the two.

References Adams, M. J. (1990). Beginning to read. Cambridge: MIT Press. Assis, E. (2002). Horizons. Raanana, Israel: Eric Cohen Books. Baddeley, A. D. (2006). Working memory: An overview. In S. Pickering (Ed.), Working memory and education (pp. 1–31). New York: Academic Press. Balgur, R. (1977). Mivxan kriya diagnosti letalmidey kitot bet-yud [Diagnostic reading test for pupils in second to tenth grade]. Tel Aviv Israel: Shockan.

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Ben-Dror, I., Bentin, S., & Frost, R. (1995). Semantic, phonologic and morphologic skills in reading disabled and normal children: Evidence from perception and production of spoken Hebrew. Reading Research Quarterly, 30, 876–893. Carlisle, J. F., Beeman, M., Hull Davis, L., & Sphraim, G. (1999). Relationship of metalinguistic capabilities and reading achievement for children who are becoming bilingual. Applied Psycholinguistics, 20, 459–478. Cisero, C. A., & Royer, J. M. (1995). The development and cross-language transfer of phonological awareness. Contemporary Educational Psychology, 20, 275–303. Comeau, L., Cormier, P., Grandmaison, E., & Lacroix, D. (1999). A longitudinal study of phonological processing skills in children learning to read in a second language. Journal of Educational Psychology, 91, 29–43. Cummins, J. (1984). Bilingualism and special education: Issues in assessment and pedagogy. Austin, TX: Pro-Ed. Dufva, M., & Voeten, M. J. M. (1999). Native language literacy and phonological memory as prerequisites for learning English as a foreign language. Applied Psycholinguistics, 20, 329–348. Durgunoglu, A. Y., Nagy, W. E., & Hancin-Bhatt, B. J. (1993). Cross-language transfer of phonological awareness. Journal of Educational Psychology, 85, 453–465. Ehri, L. C. (1992). Reconceptualizing the development of sight word reading and its relationship to recoding. In P. B. Gough, L. C. Ehri, & R. Treiman (Eds.), Reading acquisition (pp. 107–143). Hillsdale, NJ: Erlbaum. Ezra, E., & Kerman, S. (1998). Flying colors. Raanana, Israel: Eric Cohen Books. Frost, R. (2005). Orthographic systems and skilled word recognition process in reading. In M. J. Snowling, & C. Hulme (Eds.), The science of reading: A handbook (pp. 272–295). Oxford, UK: Blackwell. Gathercole, S. E., & Thorn, A. S. C. (1998). Phonological short-term memory and foreign language learning. In A. F. Healy & L. E. Bourne Jr. (Eds.), Foreign language learning: Psycholinguistic studies on training and retention (pp. 141–160). Hillsdale, NJ: Erlbaum. Geva, E., & Siegel, L. (2000). Orthographic and cognitive factors in the concurrent development of basic reading skills in two languages. Reading and Writing, 12, 1–30. Geva, E., Wade-Woolley, L., & Shany, M. (1993). The concurrent development of spelling and decoding in two different orthographies. Journal of Reading Behavior, 25, 383–406. Gholomain, M., & Geva, E. (1999). Orthographic and cognitive factors in the concurrent development of basic reading skills in English and Persian. Language Learning, 49, 183–217. Glantz, I. (1991). Xemed, ma’arexet l’bdika m’kifa, [Xemed – A comprehensive testing battery]. Tel Aviv: Barak Information Systems. Greenbaum, N., & Lichter, Y. (1996). Milot tefel [Hebrew word attack sub-test]. In N. Greenbaum & Y. Lichter (Eds.), Ivxun kri’a ktiva [Reading and writing diagnoses] (p. 8). Oranim: Oranim College. Hagiliassis, N., Pratt, C., & Johnston, M. (2006). Orthographic and phonological processes in reading. Reading and Writing, 19, 235–263. Jongejan, W., Verhoeven, L., & Siegel, L. S. (2007). Predictors of reading and spelling in firstand second-language learners. Journal of Educational Psychology, 99, 835–851. Kahn-Horwitz, J., Shimron, J., & Sparks, R. L. (2005). Predicting foreign language reading achievement in elementary school students. Reading and Writing, 18, 527–558. Kahn-Horwitz, J., Shimron, J., & Sparks, R. L. (2006). Weak and strong novice readers of English as a foreign language: Effects of first language and socioeconomic status. Annals of Dyslexia, 56, 161–186. Kail, R., & Hall, L. K. (1994). Processing speed, naming speed, and reading. Developmental Psychology, 30, 949–954. Koda, K. (1992). The effects of lower-level processing skills on FL reading performance: Implications for instruction. The Modern Language Journal, 76, 502–512.

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Koda, K. (1995). Cognitive consequences of L1 and L2 orthographies. In I. Taylor & D. R. Olson (Eds.), Scripts and literacy (pp. 311–326). Netherlands: Kluwer. Koda, K. (1996). Second language word recognition research: A critical review. Modern Language Journal, 80, 450–460. Koda, K. (2005). Insights into second language reading: A cross-linguistic approach. New York: Cambridge University Press. Leikin, M., Share, D. L., & Schwartz, M. (2005). Difficulties in L2 Hebrew reading in Russian-speaking second graders. Reading and Writing, 18, 455–472. Ministry of Education, State of Israel. (2001). English curriculum: Principles and standards for learning English as a foreign language in Israeli schools. Jerusalem: Ministry of Education. Muter, V., & Diethelm, K. (2001). The contribution of phonological skills and letter knowledge to early reading development in a multilingual population. Language Learning, 5, 187–219. Nakamato, J., Lindsey, K. A., & Manis, F. R. (2007). A longitudinal analysis of English language learners’ word decoding and reading comprehension. Reading and Writing, 20, 691–719. Nassaji, H., & Geva, E. (1999). The contribution of phonological and orthographic processing skills to adult ESL reading: Evidence from native speakers of Farsi. Applied Psycholinguistics, 20, 241–267. Oloffson, A., & Niedersoe, J. (1997). Early language development and kindergarten phonological awareness as predictors of reading problems: From 3 to 8 years of age. In C. K. Leong & R. M. Joshi (Eds.), Cross-language studies of learning to reading and spell (pp. 289–306). Netherlands: Kluwer. Parel, R. (2004). The impact of lexical inferencing strategies on second language reading proficiency. Reading and Writing, 17, 847–873. Seymour, P. H. K., Aro, M., & Erskine, J. M. (2003). Foundation literacy acquisition in European orthographies. British Journal of Psychology, R94, 143–174. Shany, M., Zieger, T., & Ravid, D. (2001). Pitu’ax v’tikuf el kley ivxun R l’tahalixim bsisim b’kriya uv’xtiv: Mem’tsa’im R al tif’kud kor’im t’kinim v’hatsa’ot l’ iluv kley ha’ivxun b’ha’araxot kor’im mit’ka im [The development and validation of tests for basic processes in reading and spelling: Performance of normally-achieving readers at various grade levels and implications for the assessment of individuals with reading disabilities]. Script: Literacy Research, Theory and Practice, 2, 167–203. Share, D. L. (1995). Phonological recoding and self-teaching: Sine qua non of reading acquisition. Cognition, 55, 151–218. Share, D. L., & Stanovich, K. (1995). Cognitive processes in early reading development: Accommodating individual differences into a model of acquisition. Issues in Education, 1, 1–57. Sparks, R. (1995). Examining the linguistic coding differences hypothesis to explain individual differences in foreign language learning. Annals of Dyslexia, 45, 187–214. Sparks, R., & Ganschow, L. (1993a). Searching for the cognitive locus of foreign language learning difficulties: Linking native and foreign language learning. Modern Language Journal, 77, 289–302. Sparks, R., & Ganschow, L. (1993b). The impact of native language learning problems on FL learning: Case study illustrations of the linguistic coding deficit hypothesis. Modern Language Journal, 77, 58–74. Sparks, R., Ganschow, L., & Patton, J. (2008). L1 and L2 literacy, aptitude, and affective variables as discriminators among high and low-achieving L2 learners. In J. Kormos & E. Kontra (Eds.), Language learners with special needs: An international perspective (pp. 11–35). London: Multilingual Matters. Sparks, R., Patton, J., Ganschow, L., & Humbach, N. (2009). Long-term cross linguistic transfer of skills from L1 to L2. Language Learning, 59, 203–243.

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Sparks, R., Patton, J., Ganschow, L., Humbach, N., & Javorsky, J. (2008). Early firstlanguage reading and spelling skills predict later second-language reading and spelling skills. Journal of Educational Psychology, 100, 162–174. Stanovich, K. E., & Siegel, L. S. (1994). Phenotypic performance profile of children with reading disabilities: A regression-based test of the phonological-core variable-difference model. Journal of Educational Psychology, 86, 24–53. van Gelderen, A., Schoonen, R., Stoel, R. D., & de Glopper, K. (2007). Development of adolescent reading comprehension in language 1 and language 2: A longitudinal analysis of constituent components. Journal of Educational Psychology, 99, 477–491. Wade-Woolley, L., Chiappe, P., & Siegel, L. (1998). Learning to read in a second language: Does phonological awareness matter? Paper presented to the fifth annual meeting of the Society for the Scientific Study of Reading, San Diego, CA. Woodcock, R. (1987). Woodcock reading mastery test-revised. Circle Pines, MN: American Guidance.

Chapter 3

Literacy Reflexes of Arabic Diglossia Elinor Saiegh-Haddad

3.1 Introduction The term ‘‘diglossia’’ emerged in sociolinguistic theory to describe a situation where in a given society there is more than one language variety in use. In what is probably the earliest use of the term, Karl Krumbacher (1902, cf. Sotiropoulos, 1977) used the term diglossia, a translation from Greek meaning ‘‘bilingualism’’, to describe the situation of Greek, with Dimotiki (popular language, or people’s language) as the medium for everyday conversation and Katharevusa (pure language) as the written medium. William Marcais (1930, cf. Zughoul, 1980) then used the term to describe the linguistic situation in the Arabic speaking world and the remarkable gulf between spoken Arabic vernaculars and the written standard- Classical Arabic. The term was publicized in a famous 1959 Word article by the linguist Charles Ferguson (1959) who offered the first coherent theory of diglossia referring to Arabic as a typical example. Ferguson proposes a classification of diglossic features that include function, prestige, literary heritage, acquisition, standardization, stability, grammar, lexicon, and phonology. According to Ferguson, a diglossic context is characterized by a stable co-existence of two linguistically-related language varieties, a High variety and a Low variety, which are used for two sets of complementary social functions; Such rigid functional complementarity, it is argued, should give way only to slight and insignificant overlap (Maamouri, 1998). In a diglossic context, no section of the community uses the High variety for ordinary conversation. This is arguably ‘‘the most important factor in a diglossic situation and one that makes for relative stability’’ (Keller, 1982, p. 90). In a diglossic context, the two language varieties are associated with different degrees of prestige. The High variety is considered prestigious and elegant; it is used for formal linguistic functions, such as religious sermons, news broadcasts, speeches, etc, and is the only written code. The Low variety E. Saiegh-Haddad (*) Department of English Linguistics, Bar-Ilan University, Ramat-Gan, Israel e-mail: [email protected] M. Leikin et al. (eds.), Current Issues in Bilingualism, Literacy Studies 5, DOI 10.1007/978-94-007-2327-6_3, Ó Springer ScienceþBusiness Media B.V. 2012

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is stigmatized as a literary from and is an exclusively spoken code. The High variety is usually associated with a rich literary tradition and is the standardized form that is encoded in dictionaries and books. As it is only a written variety, the High variety is nobody’s mother tongue. Instead, it is the Low code that children acquire as their first language. Stability is another important feature of diglossia as a long-lived phenomenon. Finally, in a typical diglossic context, the two varieties of the language are linguistically related, though the phonology, morphology, and syntax of the Low variety are often simpler than that of the High variety. A diglossic context is also characterized by the existence of a large set of paired lexical items, which are available in both codes but which, though linguistically related, are phonologically distinct. Fishman (1967) has reformulated and extended the term ‘‘diglossia’’. According to Fishman, diglossia does not necessarily encompass two varieties of a language, a High standard and a Low spoken vernacular, but may also be extended to refer to situations where two dialects or registers are used for socially distinct sets of functions. Classical examples include the Standard German-Swiss German context of Switzerland and the Creole-French context in Haiti. The hallmark of this new definition is that the two codes are functionally different. In yet another extension of the term, Fishman (1991), uses the concept diglossia to refer to bilingual communities. Such reformulation encompasses under the term ‘‘diglossia’’ many other bilingual contexts, including the English–Latin context of Medieval England. While the broader meaning of the term ‘‘diglossia’’ has gained widespread currency, scholars warn against such a mix of terms. Hudson (1991), for instance, argues that Fishman’s (1991) reformulation is problematic as the direction of language evolution in a classic diglossic context is opposite to that in the case of widespread bilingualism. In other words, while in a diglossic context, the Low variety, or at least some linguistic aspects of the Low variety take over the outdated High variety, in a bilingual context the Low variety loses ground to the superposed High variety. In a more recent account, Hudson (2002) stresses the need for sociolinguistic theory to distinguish typical diglossic contexts from standard-with-dialect contexts or contexts of societal bilingualism. Hudson points to a central feature unique to diglossia. He argues that, unlike other contexts, societal bilingualism or standard-with-dialects, stratification of variation in diglossia shows sensitivity to differences in situational context (use-oriented) without much sensitivity to differences in social class (user-oriented) (Bell, 1984; Walters, 1994). In the same vein, Anghelescu (1974) had warned that such terminological mix disguises the true nature of diglossia and reduces it to ‘‘stylistic functional variation’’. According to Anghelescu, ‘‘diglossia implies sufficiently similar languages for the speakers to feel that it is the same language, yet remote enough, so that the acquisition of the literary language implies long-term efforts and can never be fully achieved’’ (cf. Maamouri, 1998, p. 30).

3

Literacy Reflexes of Arabic Diglossia

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3.2 Arabic Diglossia Perhaps one of the most compelling features of Arabic, especially in the context of literacy acquisition, is its diglossic nature (Al-Batal, 1992; Al-Toma, 1969; Haeri, 2000). The most important feature of diglossia, and one that has direct implications for literacy acquisition in Arabic, is the establishment of rigid and complementary functional separation of two linguistic codes: the written and the spoken. According to Hymes (1973), the dominant practical response to linguistic diversity is ‘‘to impose a novel unity in the form of the hegemony of one language or standard’’ (p. 22). The standardization of Arabic, which began in the 8th and 9th centuries A.D., has produced a set of norms that the early grammarians called fusha (Maamouri, 1998). Over the course of many years, the continued use of this favored set of written linguistic norms led to substantial differences between the dynamic spoken vernaculars and the fixed written form, making the two varieties distinct and linguistically distant, and engendered the notion that the written standard was the ‘‘real language’’ while the other varieties of it were ‘‘degenerate’’ and ‘‘corrupt’’ versions (Maamouri, 1998). The term fusha /fusħa/ is currently used to refer both to Classical Arabic (the language of the Qur’an), and to a modern descendant of Classical Arabic, Modern Standard Arabic (hereafter, MSA, or Standard Arabic), which serves as the modern written standard and the variety used in formal oral discourse. In contrast, the term ‘‘The Arabic Language’’, al’arabiya, is an abstraction that refers to the written standard(s), as well as the sum of all the varieties in use in the Arab region (Maamouri, 1998). Another unique feature of diglossia that has direct ramifications for literacy development in Arabic is acquisition. While all Arab children naturally acquire the local spoken vernacular of the speech community to which they belong, learning the written standard, i.e., MSA, comes about mainly as a result of formal instruction in reading. Thus, MSA is nobody’s mother tongue (Coulmas, 1987; Joseph, 1987). It is typically never spoken at home or in the neighborhood. It is argued that the fact that the functional distribution of codes in a diglossic context protects the role of the Low variety as a natively learned variety is what distinguishes diglossia from other interlingual or intralingual situational alternation (Hudson, 2002, p. 7). This, together with the linguistic distance between Spoken Arabic and the linguistic system encoded in print (Standard Arabic), implies a series of challenges to the acquisition of literacy in Arabic. In the next section we provide a linguistic description of Arabic diglossia. Then we review recent psycholinguistic evidence in support of the impact of diglossia on the acquisition of basic literacy processes in Arabic.

3.3 The Linguistic Distance in Diglossic Arabic All spoken Arabic vernaculars are linguistically related to Standard Arabic. Yet, the linguistic relatedness between Spoken and Standard Arabic is ‘‘flexible’’ and ‘‘changeable’’ (Kaye, 1972). Despite linguistic relatedness between the two linguistic codes, a linguistic analysis of the structure of Standard Arabic and

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any given spoken Arabic vernacular reveals differences in all language domains of language and most clearly in the lexicon, the phonology and the morphosyntax. In the following section we will focus on the phonological and lexical distance between Spoken and Standard Arabic. A major manifestation of the linguistic distance between Standard and Spoken Arabic exists in the phonemic inventories of the two language varieties. Although Standard Arabic shares most of the phonemes with all spoken vernaculars, no single Spoken Arabic vernacular has the same set of phonemes as Standard Arabic (Maamouri, 1998). For instance, while the phonemic inventory of MSA includes voiced, voiceless, and emphatic interdental fricatives, /ð/, / y/, /ð/, these phonemes are absent from a local dialect of Northern Palestinian Arabic spoken in the north of Israel. In this dialect, then, paired lexical items existing in both Spoken and Standard Arabic have different phonological structures in the two varieties, with Standard phonemes systematically substituted for by Spoken phonemes. For instance, the Standard word /ðakar/, meaning ‘‘male’’, becomes /dakar/ in this dialect of Spoken Arabic. Another phonological disparity between Standard and Spoken Arabic pertains to the internal phonological composition of the syllable. The internal phonological structure of the syllables in Standard and Spoken Arabic is subject to different phonotactic constraints. For instance, while word initial (onset) consonantal clusters are not permissible in Standard Arabic, they are frequent in many Spoken Arabic vernaculars. As a result, the Standard word /tura : b/, meaning ‘‘soil’’, becomes /tra: b/ in some vernaculars. At the same time, while word final (coda) consonantal clusters are rare in spoken Arabic vernaculars, it is a very common monosyllabic word structure in Standard Arabic. This explains the reason that the Standard word /sah|/, meaning ‘‘plain’’, becomes /sahi|/ in Spoken Arabic, or that the Standard word /ya|Z/, meaning ‘‘snow’’, becomes /ta|iZ/, respectively, with both the segmental and the syllabic structure of the word altered in accordance with the phonological constraints of the specific spoken vernacular. The above illustration of some of the phonological distance parameters between Standard and Spoken Arabic (for a more detailed description see Levin, 1994) suggests that even for shared vocabulary items (so-called paired lexical items) there may be a substantial phonological difference between their forms in Standard and Spoken Arabic. Paired lexical items (cognate words) were found by a recent study to make up about 40% of the lexicon of 5-year-old Arabic native speaking children (Saiegh-Haddad, ms.). This study also showed that the next largest category in the lexicon of children is Spoken Arabic unique words. That is, words, which exist in Spoken Arabic only and have a completely different form in Standard Arabic. This category was found to make up about another 40% of the children’s lexicon leaving only 20% overlapping words. These findings support the remarkable linguistic distance between Spoken and Standard Arabic.

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3.4 The Acquisition of Basic Reading Processes in Diglossic Arabic Learning to read in Arabic, and owing to the diglossic context explicated earlier, requires the acquisition of two systems: an orthographic system and a linguistic system. Perhaps the first and most basic linguistic system that children must become familiar with in order to embark upon the process of reading acquisition is the phonological system of the language of literacy. Phonological skills are fundamental to the acquisition of reading as they are directly implicated in the execution of two critical word reading processes: phonological segmentation and phonological recoding. To be able to read, children must first become aware of the phonological structure of spoken words (for reviews, see Adams, 1990; Goswami & Bryant, 1990; National Reading Panel, 2000). Phonological awareness underlies the ability to segment words into phonemes. Having segmented the word, the reader is then required to translate the graphemes of written words into the corresponding oral language phonemes. Such a phonological recoding process is the hallmark of word decoding in an alphabetic orthography. If a basic prerequisite to reading is for beginning readers to become aware of the phonological structure of the written language, the question that looms large relates to the acquisition of reading in the absence of such a foundational infrastructure. In other words, how do beginning readers develop reading in a context where reading is first learned in a language that is phonologically distinct from the oral language they have already acquired, as is the case with Arabic native speaking children learning to read in MSA? Does the phonological distance between the two varieties of the language, the spoken vernacular and the written standard, disrupt the natural acquisition of basic reading processes? These questions have guided the research reviewed in this paper. Saiegh-Haddad (2003, 2004, 2007) tested the effect of the linguistic distance (phonological and lexical) between Standard and a local Arabic vernacular spoken in the north of Israel on phonological awareness among kindergarten, 1st, 2nd, and 3rd graders. These studies showed that the linguistic affiliation of the target phoneme (Standard versus Spoken) reliably predicted children’s phoneme isolation performance in kindergarten through the second grade. This effect fell below statistical significance in the third grade, 3 years after extensive formal exposure to Standard Arabic. As such, both kindergarten, first-grade, and second-grade children found Standard phonemes, and despite proper articulation, significantly harder to isolate than Spoken phonemes. This factor was found to interact with grade, with the linguistic affiliation of the syllable in which the phoneme was embedded, and with the lexical status of the word resulting in particular difficulty when kindergarteners were asked to isolate a Standard phoneme from a Standard syllable, or from a Standard word. These results were argued to be attributed to a deficiency in the phonological representations of Standard linguistic structures (phonemes, syllables, and words) which appears to disrupt phonological analysis (Elbro, 1996, 1998; Goswami, 2000, 2002; Katz, 1986).

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The finding that the absence of some phonemes, syllabic structures, and words from the spoken vernacular of children remains significant in explaining phoneme isolation performance in Standard Arabic, even at the end of the second grade, has serious implications for the effect of the linguistic profile of the spoken vernacular of children, and of the linguistic distance between this variety and the linguistic system encoded in print, on the development of phonemic awareness in the language of literacy. The results also have serious ramifications for the cross-dialectal validity of phonological sensitivity tasks in MSA, and imply that a thorough analysis of the linguistic distance between the specific spoken vernacular and MSA is warranted before any such task is designed. Though the linguistic affiliation of the phonological structure was found to impact the phoneme isolation performance of preliterate kindergarteners and literate children in the early grades, the latter were found to significantly outperform the former. This implies that though first grade children have somewhat benefited from the increased exposure and experience with Standard Arabic structures that formal literacy instruction allows, they were still facing particular difficulty when confronted with the task of isolating standard phonological structures. This finding demonstrates one of the unique complexities present in learning to read in Standard Arabic. While in other linguistic contexts, beginning readers come to the reading task with ample knowledge and experience with the linguistic structures of the language of literacy to embark upon the task of learning to decode oral language linguistic structures, Arabic native children are required to acquire both the linguistic system of the written language and its orthographic representation. Acquiring the linguistic system of the language of literacy requires the construction of proper phonological representations for the novel linguistic units that the written language encodes. Given consistent evidence in favor of the impact of the diglossic linguistic distance on children’s phonological sensitivity for contrastive Standard linguistic structures, the question that naturally follows relates to the impact of the linguistic distance on the phonological recoding, or the decoding skills of Arabic native children. This question was addressed in Saiegh-Haddad (2003, 2005). These studies tested the pseudoword decoding accuracy and fluency (speed) of first grade children and showed that the linguistic affiliation of the phonemes that make up pseudowords reliably explained the decoding accuracy of children at the end of the first grade. As such, the results showed that, despite generally high rates of decoding accuracy, a large percentage of the decoding errors committed by children were related to Standard phonemes and Standard syllabic structures. Furthermore, children’s errors were primarily phonetic and constituted primarily of phonologically similar pseudowords that reflected difficulty in the phonological recoding of novel phonological structures. In contrast, Spoken Arabic phonemes and Spoken syllabic structures that were available in the oral language of children were almost perfectly decoded. With respect to decoding fluency, Saiegh-Haddad (2005) found that speed of converting letters into sounds (letter recoding speed) along with memory and rapid

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automatized naming were the strongest predictors. Given the transparent orthography of voweled Arabic, the high decoding accuracy that children had revealed was not surprising. As such, the regular and consistent orthographic representation of oral language phonemes make the phonological recoding of those graphemes a straightforward task (Seymour et al., 2003) and encourage an analytic, phonological assembly decoding mechanism. Given this decoding strategy, and as some of the graphemes (primarily single letters) map onto novel phonemes, it follows, and as the above study has shown, that the great majority of the children’s decoding errors would be specifically bound to novel phonological units. Hence, two sets of forces operate in the acquisition of reading fluency in voweled Arabic. The first is the shallow orthography. The second is the diglossic context. Arabic pseudoword reading fluency, at the end of the first grade, was best predicted by letter recoding speed, memory, and rapid naming. These findings are consistent with earlier evidence supporting the role of such cognitive skills to reading in general (Abu-Rabia & Siegel, 2002; Bowers & Wolf, 1993; Geva & Siegel, 2000; McBride-Chang, 1995; Wolf & Bowers, 1999; Wolf, Bowers, & Biddle, 2000; Wolf et al., 2002), and to reading in a shallow orthography, in particular (de Jong & van der Leij, 1999; Landerl & Wimmer, 2000; Wimmer, Mayringer, & Landerl, 1998, 2000). Yet, the prediction that phonological processing (phoneme discrimination and phoneme isolation), especially for Standard phonemes, would turn out a significant correlate of reading fluency in diglossic Arabic was not supported. Although phoneme isolation for Standard phonemes was more difficult than that for Spoken phonemes, the study revealed only a moderate correlation between phoneme isolation and reading fluency. Further, this relationship disappeared when rapid naming, or when letter recoding speed, along with memory, were entered into the regression equation. Though inconsistent with the prediction that phonological awareness in Arabic, and because of the phonological distance between Standard and Spoken Arabic, would turn out a strong correlate of reading fluency, this finding is supportive of recently emerging evidence demonstrating significant shrinkage in the power of phonemic awareness in predicting individual differences in reading fluency in a shallow orthography (de Jong & van der Leij, 1999; Landerl & Wimmer, 2000; Wimmer et al., 1998, 2000). In a recent study (Saiegh-Haddad, Levin, Hende, & Ziv, 2011), we tested the effect of the phonological distance in diglossic Arabic on kindergarten children’s phoneme recognition, a task that does not require phonological production. Using a picture selection task and through careful manipulation of the phonological properties of target phonemes and distractors, the study showed that children’s recognition of Standard phonemes was poorer than that of Spoken phonemes. This finding was interpreted as indicating a deficiency in the phonological representations of Standard words. The study also tested two hypotheses regarding the specific consequences of under-specified phonological representations: phonological encoding versus phonological processing. These hypotheses were addressed through an analysis of the relative power of

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distractors. The findings revealed that children’s difficulty in accessing Standard Arabic phonemes was due to a difficulty in the phonological encoding of Standard Arabic lexical items and suggested the need for explicit, systematic, and sustained exposure to Standard Arabic phonological structures. The evidence reviewed above shows that diglossia does not support the acquisition of basic literacy processes in Arabic, and may indeed contribute to the widespread low levels of mother tongue reading comprehension scores (Kramarsky & Mevarech, 2003; Olshtain & Rozovsky, 2004). The findings also support the conjecture that diglossia may be to blame for the high rates of illiteracy in the Arabic speaking world (Ayari, 1996). Yet, is the linguistic distance between Spoken and Standard Arabic the only factor to blame? The infrastructure for literacy acquisition is established first in the home of the child. Thus, literacy acquisition is embedded in the socio-cultural contexts of the young children’s families. In effect, the belief system of parents regarding literacy should affect parent-child literacy interactions and activities. The impact of these factors on literacy development in diglossic Arabic remains largely unexplored. Iraqi (1990), in a study of book use habits in Arab Israeli families found that only five (1.8%) of the 290 Arab families investigated reported reading to their children from books. In 58.2% of the families, parents orally recited stories that they remembered from their own childhood, and in the remaining 40.0% of them said that they had used books in storytelling sessions but did not read from them. The two reasons that parents provide for not reading from books were that children do not understand the language of the book (Standard Arabic) and that they do not enjoy being read to from books. The Arab parents’ belief system regarding the importance of early exposure to Standard Arabic and regarding their children’s ability to acquire basic literacy skills at an early age determines parent-child literacy activities and interactions. This may be a very important determinant of children’s later literacy achievement and is a question for future research to explore. Informal experiences and exposure to literacy in the home of the child may be best tapped by preschoolers’ familiarity with letters. In a pilot study of 77 Arab Israeli middle-to-low class children, we tested children’s knowledge about Arabic letters: concept, function, name, and sound (Saiegh-Haddad, 2009). This study showed that, at the age of three, 98.8% of the children did not have a concept of letter. That is, upon presentation on a card, children could not categorize them as letters and only few said that they were numbers. This rate dropped to 57.1% at the age of four. Only at the age of five did all children realize that what they were shown were letters. With regard to the function of letters, 84.4% of the 3-year-olds did not know what letters were used for. At the age of four the percentage dropped to 71.4%. At the age of five, only 1 year before the first grade, 46.2% of all children did not know what the function of letters was. As to the number of letters that children could identify (either by name or sound), 93.8% of the three-year-olds, 75% of 4-year-olds, and 7.7% of 5-year-olds could not identify any of the 28 Arabic letters. Knowledge about the direction of writing and personal-name writing was assessed as well. Here,

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65.5% of 3-year-olds did not know the direction of writing (right to left) and 93.8% of them could not write their names. These figures dropped to 41.7% and 75% at the age of four, and 15.4% and 15.4%, at the age of five, respectively. These compelling figures suggest that, though the linguistic distance between Spoken Arabic and Standard Arabic may be one important factor to blame, it is essential that future research investigate the direct effect of the literacy environment in which the child is raised, as well as the effect of the socio-cultural context in which informal literacy is embedded on the acquisition of literacy in Arabic. This is a significant avenue for future research to pursue. In support of the above argument, Levin, Saiegh-Haddad, Hende, and Ziv (2008) tested letter knowledge and phonological awareness in low SES 5-yearold Arabic native speaking children and the impact of an intervention program on children’s acquisition of these skills and showed that 40% of the children could not name any letter in the pretest, and, on average, this group succeeded in naming less than a single letter at that point in time. This performance level is considerably low when compared with middle-class children reared in other countries. For instance, American and Brazilian-Portuguese preschoolers were found to name an average of 64% of the letters in their alphabets (Treiman, Kessler & Pollo, 2006). Similarly, Hebrew speaking preschoolers and kindergartens, in a low-to-middle SES sample, though not taught about letters at school, succeeded in naming 61% of the letters (Treiman, Levin, & Kessler, 2006). The study also showed, however, that the intervention program succeeded in raising the letter knowledge and phonological processing performance of the children in the intervention group to a level comparable to that of their English- and Hebrew-speaking counterparts. The sustained low level of literacy knowledge throughout the school year among kindergartners in the control comparison group suggests that these children were deprived of the education that might have prepared them for learning to read and write in school. This deprivation exacerbates the effect of the linguistic distance between the spoken and the written codes on the acquisition of literacy in young Arabic speaking children and increases their risk for academic failure.

3.5 Conclusion Strong linguistic skills are associated with better reading outcomes. Given the diglossic context of Arabic and the remarkable orality-literacy gap, the question is how the linguistic disparity between Spoken Arabic and the language of literacy might factor into the unfortunate literacy and educational failure of Arab children. Despite frequently articulated concerns over the possibility that this longlived phenomenon of diglossia may be to blame for the widespread illiteracy in the Arab World (Ayari, 1996) and claims, explicit or implicit, by others that the acquisition of reading in Standard Arabic may be comparable to literacy acquisition in a foreign or second language (Abu-Rabia, 2000; Ibrahim, 1977,

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1983), the direct impact of the linguistic distance between Spoken and Standard Arabic on the acquisition of literacy has only recently begun to attract empirical attention. The studies reviewed here converge in demonstrating that the linguistic distance between Spoken Arabic, which children acquire as a mother tongue, and Standard Arabic, which is acquired primarily as a result of formal instruction in reading, does not support the natural acquisition of basic reading processes in Arabic (Saiegh-Haddad, 2003, 2004, 2005, 2007, 2008; SaieghHaddad et al., 2011). The linguistic duality problem that diglossia as a sociolinguistic phenomenon presents is supported and perpetuated by a unique socio-cultural milieu in which Arabic literacy acquisition is embedded. The complex linguistic reality results in poor language skills in the written code and, in turn, in linguistic insecurity that curtails language practice and impacts literacy-related practices and outcomes. This perpetuates the gulf between the two codes and stabilizes the diglossic reality. Further, the widespread low levels of proficiency in the written code and the high rates of illiteracy, together with abject poverty and low socio-educational background results in children beginning the process of literacy acquisition with little or no knowledge about the basic prerequisite language and literacy skills that form the infrastructure of reading development. This deprivation brings about more deprivation and less chances of success.

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Chapter 4

Multilingualism Among Israeli Arabs, and the Neuropsychology of Reading in Different Languages Zohar Eviatar and Raphiq Ibrahim

In this chapter we focus on two major topics. The first examines the linguistic situation in the Arab population of Israel, which is quite complex, and has implications for reading acquisition. As we show, literate Israeli Arabs are minimally quadralingual, and reading and writing in multiple languages are always acquired in the non-native language. The second topic focuses the psycholinguistic characteristics of Arabic and Hebrew orthography, and on models of differences in the functional architecture of reading in Hebrew and in Arabic.

4.1 Multilingualism in the Arab Context in Israel 4.1.1 Diglossia or Multilingualism? In Arabic, the spoken form (ammia – the local dialect) is used by speakers of the language in a specified geographic area for daily verbal communication, and is the native language of virtually all Arabic speakers. This form is differentiated from the fuṣḥa (the literary form), which is the language in which all speakers of Arabic, from all over the world, read and write. This literary Arabic is universally used in the Arab world for formal communication and is known as ‘‘written Arabic’’ or ‘‘Modern Standard Arabic’’ (MSA). Spoken Arabic (SA) appears entirely in colloquial dialect and has no written form. Hence, from the ecological point of view, SA and MSA could be considered as an instance of ‘‘diglossia’’, that is, a social environment in which a community uses two forms of the same language concomitantly (Ferguson, 1959). However, from a linguistic perspective, literate Arabic speakers could be considered, de facto, bilinguals, and contribute to the debate as to whether the two forms of Arabic represent different languages (Eid, 1990). We take up this debate below. Z. Eviatar (*) Department of Psychology, University of Haifa, Haifa, Israel Institute for Information Processing and Decision Making, University of Haifa, Haifa, Israel e-mail: [email protected] M. Leikin et al. (eds.), Current Issues in Bilingualism, Literacy Studies 5, DOI 10.1007/978-94-007-2327-6_4, Ó Springer ScienceþBusiness Media B.V. 2012

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Z. Eviatar and R. Ibrahim

One of the foci in bilingualism research has been the effect of bilingualism on cognitive and paralinguistic development. Recently we (Eviatar & Ibrahim, 2001) asked how early exposure to the two forms of Arabic can affect the metalinguistic abilities of children. The received view in bilingualism literature is that the challenges posed by two linguistic systems promote the development of cognitive strategies that result in heightened metalinguistic abilities in young children (e.g., Bialystok, 1991). Metalinguistic awareness refers to the ability to think about the linguistic nature of the message and to be aware of certain properties of language such as its arbitrariness and phonological structure (Ben Zeev, 1977; Dash & Mishra, 1992). To be metalinguistically aware is to solve linguistic problems such as the detection of ambiguity and grammaticality (Galambos & Hakuta, 1988; Galambos & Goldin Meadow, 1990), to create new words (Titone, 1994), and to be able to segment words into their constituents (Campbell & Sais, 1995). All of these require an awareness of language as a system and the ability to access and manipulate knowledge about that system (Bialystok & Ryan, 1985). We focused on the finding that exposure to two languages results in a specific pattern of performance on three types of tests (arbitrariness, phonological awareness, and vocabulary size) and asked whether children exposed to the two forms of Arabic would show this pattern. That is, we asked, are the two forms of Arabic different enough from each other to result in the pattern typical of bilingualism? We tested Arabic-speaking children, who are exposed to both SA and MSA and compared them to Russian-Hebrew bilinguals and Hebrewspeaking monolinguals. All of the children were in kindergarten or in first grade. The results of the Russian-Hebrew bilinguals showed the classic pattern resulting from exposure to two languages: higher performance levels in metalinguistic tests and lower performance levels in the vocabulary measure as compared to monolinguals. The Arab children’s performance mimicked those of the bilingual children for the most part, and suggested that exposure to MSA in early childhood affects metalinguistic skills in the same manner as that reported for children exposed to two different languages. Thus, Arab children enter first grade as bilinguals, and those who attend the Arab school system begin to learn to read MSA in first grade, to speak Hebrew in second grade, and to read and write in Hebrew and in English in third grade. At the high-school level, most students are as proficient in Hebrew as they are in MSA. Ibrahim (Ibrahim, 1998; Ibrahim & Aharon-Peretz, 2005) examined the status of MSA and Hebrew in high-school students. The logic was the following: if MSA constitutes a second language for the Arabic speaker, then the results obtained regarding the lexical status of MSA words and their connections to meaning should be similar to patterns found for Hebrew. On the other hand, if the daily interactive use of SA and MSA, along with the sociolinguistic reality in which the two languages may be considered two forms of one language, have led to the combination of both forms of Arabic in a single lexicon, the results of linguistic manipulations between the two forms of Arabic should resemble those known to exist when the same linguistic manipulations are

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Multilingualism Among Israeli Arabs, and the Neuropsychology of Reading . . .

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performed within a language. The relations between the two forms of Arabic were compared to the relations existing between Hebrew and SA. Ibrahim compared semantic priming effects within Spoken Arabic, with the effects found across languages, with MSA or Hebrew being the other language. The results in all of the studies were consistent and straightforward: when both the primes and the targets were presented in SA, the semantic priming effect was significantly greater than when the prime and target words were from MSA or Hebrew. Most importantly, the cross-language priming effects on response times were virtually the same, regardless of whether the second language was Hebrew or MSA. As with the young children, these findings suggest that the representation of MSA is that of a second language (L2), similar to Hebrew, and that SA and MSA have the status of two separate languages in the cognitive systems of Arabic speaking adolescents. These findings align nicely with previously reported asymmetry in crosslingual semantic priming (Altarriba, 1992; Keatley & DeGelder, 1992). The interpretation of the difference between the patterns of priming within and across languages is that words in a second language have looser connections with their meanings than do words in the first language. Therefore the semantic priming pattern described above suggests that, at least in regard to their connections with the semantic network, MSA, as well as Hebrew, constitute second languages for the bilingual native speaker of SA. Being Semitic languages, Hebrew and both SA and MSA have similar morphological structure. Ibrahim (2006) examined to what extent the morphophonological similarity among the languages is modulated by their psychological status as a native or a second language. Based on a distributed conceptual representations model (see for example, McClelland, Rumelhart, & Hinton, 1986), de Groot (e.g., 1992, 1995) accounted for the morpho-phonemic similarity effect of cognate translation equivalents by assuming that because they have a common etymology, they also share more meaning features than noncognate translation equivalents. Therefore priming between cognate translations is more effective than between non-cognate translations. In essence, according to her view, repetition priming between translation equivalents, like semantic priming, originates from activation of common semantic features in the conceptual system. If this is the case, then the findings cited above might be due to the morpho-phonemic similarity among SA and MSA and Hebrew and MSA. Ibrahim (2006) asked if the difference in semantic overlap of HebrewMSA and SA-MSA translation equivalants remained constant across repetition lags. The results showed larger priming effects for cognate Hebrew – MSA than SA – MSA pairs at lag 0, on the one hand, and smaller priming effects at lag 4, on the other hand. Ibrahim concluded that non-linguistic factors qualified the influence of the linguistic factors in determining the magnitude of the morphophonemic similarity effects. Specifically, he proposed that among these factors are lexical-episodic associations, which are apparently stronger between translation equivalents in two languages that are interactively and concomitantly used on an everyday basis (such as SA and MSA), than between translation

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equivalents in languages that are not concomitantly used (such as Hebrew and MSA). In concert with previous findings, this study indicated that despite extremely intensive and concomitant use of Spoken and Literary Arabic, this does not bring about a change in their status as first and second languages, respectively. However, under such circumstances, associative links are formed between translation equivalents at the lexical level. The strength of these associations is determined by the frequency of concomitant use and by the psychological perception of the two languages as being forms of a single language. To summarize, the linguisitic requirements of literate Israeli Arabs are quite complex. Adults can be minimally considered quadrilingual, with SA as L1, and MSA, Hebrew and English as additional languages. Because SA does not have a written form, all reading and writing are carried out in the nonnative language.

4.1.2 Multilingualism and Reading Acquisition Ayari (1996) and Maamouri (1998) have suggested that the diglossic situation in Arabic might be related to some of the hardships that native Arabic beginning readers encounter and might even hinder their acquisition of basic academic skills. Abu-Rabia (2000) directly investigated the contention that reading difficulties in Arabic in elementary school result from the diglossic situation of fuṣḥa, the language of books and school instructions, and its opposition to the spoken dialect of the home. Starting from the belief shared by educators, teachers, and parents that the exposure of young Arabic speakers to fuṣḥa in the preschool period is not useful and a burden to all, Abu-Rabia compared the reading comprehension performance of first and second grade children who had been experimentally exposed to literary Arabic throughout their preschooling period with the reading performance of a parallel control group only exposed to spoken Arabic during that period. He found, contrary to the commonly held belief, that the early exposure of Arab preschool children to fuṣḥa text (stories) enhances their reading comprehension abilities and improves their performance in reading comprehension tests 2 years later. Finally, more than his scientific findings, Abu-Rabia’s conclusions (2000: 155) are worth noting: (a) policy-makers may incorporate this pedagogy in all preschool years, (b) educating elementary-school teachers and kindergarten teachers in diglossic issues, and (c) the recommendation that ‘‘teachers at all levels use literary Arabic as the language of instruction.’’ Elinor Saiegh-Haddad (2003) studied the role of oral language in the acquisition of basic fuṣḥa reading processes in kindergarten and first grade Arabicspeaking children. She hypothesized that because native speakers of Arabic first learn to read in fuṣḥa, a language structurally different from the local dialect they grow up speaking, the linguistic differences between the two Arabic language varieties would interfere with the acquisition of basic reading processes. In a series of studies of the acquisition of reading in diglossic Arabic (Saiegh-Haddad, 2004, 2005) Saiegh-Haddad tried to answer the following

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questions: first, do diglossic variables or linguistic distance parameters interfere with the acquisition of basic reading processes in fuṣḥa? Second, which diglossic structures interfere with the acquisition of basic reading skills, phonological, syntactic, morphosyntactic or lexical? Third, which reading skills (phonemic awareness, word decoding, reading fluency, or reading comprehension) are sensitive to diglossic variables? Testing phonemic awareness skill and decoding pseudo-word for example, showed that although the first grade children seemed to have benefited from the increased exposure to fuṣḥa structures that formal literacy instruction allowed, they still found the task of isolating standard phonological structures quite difficult, especially for sounds that do not occur in their local dialect. The findings were similar to those reported by Abu-Rabia, as the first grade children seemed to have benefited from the increased exposure to fuṣḥa structures that formal literacy instruction allowed. Saiegh-Haddad concluded that, diglossia (presented by the linguistic disparity between SA of children and the linguistic system encoded in print) does not appear to support the natural acquisition of basic literacy processes in Arabic. In that regard, it could even contribute to the proven low levels of mother tongue literacy achievement in Arabic, as international literacy assessment projects have revealed (Olshtain & Rozovsky, 2004) and may support Ayari (1996) who blames the diglossia for the high rates of illiteracy in the Arabic-speaking world. In the following section we review some of the findings on reading in Hebrew and Arabic from both psycholinguistic and neuropsychological perspectives.

4.2 Reading in Hebrew and in Arabic 4.2.1 The Importance of Vowels Unlike the Latin orthography in which vowels are represented by letters, in Arabic and Hebrew vowels are not part of the alphabet. Vowelization is optional, and most texts do not include them. When vowels do appear (in poetry, children’s books and liturgical texts), they are signified by diacritical marks above, below or within the body of the word. To complicate matters, there are four letters which also specify long vowels, in addition to their role in signifying specific consonants (in Hebrew: ‘alef , vav, yud and he’; in Arabic: ‘alif’ or ‘imaala, waaw, yaa’). However, in some cases it is difficult for the reader to determine whether these dual-function letters represent a vowel or a consonant. Research exploring the processing of vowel diacritics in Hebrew has revealed that naming of unambiguous words was facilitated when these were presented in pointed script (Frost, 1994), while lexical decisions did not benefit from pointing (Bentin & Frost, 1987; Frost, 1994, 1995; Koriat, 1984, 1985a; for an exception see Koriat, 1985b). Only studies that applied an interference paradigm demonstrated automatic processing of vowel information for naming as

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well as for verbal lexical decisions and semantic judgments (Navon & Shimron, 1981). These researchers used an interference paradigm in which vowel information conflicted with the response suggested by the relevant consonant information. In three experimental groups, adult native Hebrew speakers were presented with correctly voweled words, unvoweled words, and ‘‘phonemically distorted’’ vowels, in which the vowels turned the sound of a word into a nonword. Although participants were instructed to ignore the vowel information, responses for phonemically incorrect pointing were considerably slower, indicating that participants were not able to disregard the presented vowel information. In addition, ‘‘graphemically distorted’’ pointing was applied, in which orthographically incorrect diacritics changed the visual pattern of a word, but nevertheless preserved its correct sound. This kind of pointing was introduced to control for the fact that phonemically incorrect pointing also provided incompatible visual cues. The fact that orthographically incorrect pointing did not interfere with naming latencies suggested that the interference produced by phonemic distortion was due to phonological processing. The authors concluded that vowel graphemes are automatically translated into phonemes. Smolka and Eviatar (2006) showed that this automatic phonological recoding occurs in the left hemisphere (LH) of adult readers, and that diacritics are processed as visual patterns in the right hemisphere (RH). The Arabic script uses diacritical forms (or diacritics) for three short vowels (a-fatha, u-damme, i-kasra) that represent the long vowels: a; o; e (‫ﻱ‬, ‫ﻭ‬, ‫)ﺍ‬. An additional diacritical marking, the shadda, is used for lexical differentiation. Most of the grammatical functions at both the morphological and syntactic levels are represented by the short vowels, which also represent mood and case endings in the Verb-Subject-Object literary (fuṣḥa) syntax. From a psycholinguistic view, inclusion of these marks specifies the phonological form of the orthographic string, making it completely transparent in terms of orthography/ phonology relations. In both Arabic and Hebrew, the majority of written materials do not include the diacritical marks, such that a single printed word is often not only ambiguous between different lexical items (this ambiguity is normally solved by semantic and syntactic processes in text comprehension), but also does not specify the phonological form of the letter string. Thus in their unvoweled form, Hebrew and Arabic orthographies contain a limited amount of vowel information and include a large number of homographs. For example, the bare unvowelized fuṣḥa form TH-K-R (‫ )ﺫﻛﺭ‬has five readings and five corresponding semantic interpretations: (a) thakara ‘‘mentioned’’ (b) thakkara ‘‘remind (singular/masculine)’’ (c) thokera ‘‘was mentioned’’ (d) theker ‘‘learning situation’’ and (e) thakar ‘‘masculine’’. Nevertheless, as mentioned above, it has been found that in both Hebrew (Bentin, Bargai, & Katz, 1984) and Arabic (Roman & Pavard, 1987) the addition of phonological disambiguating vowel points inhibits (rather than facilitates) lexical decision. On the basis of such results, it has been suggested that, at least in Hebrew, correct lexical decisions may be initiated on the basis of orthographic codes, before a particular

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phonological unit has been accessed (Bentin & Frost, 1987). Evidence for orthographic-based access in Hebrew has been presented by Peleg and Eviatar (2009), who showed that heterophonic homographs in Hebrew (ambiguous words that have an identical graphemic form and different phonological forms, such as ‘‘tear’’) as well as homophonic homographs (ambiguous words with identical graphemic and phonological forms, such as ‘‘bank’’) activate both meanings, when probed very early in the reading process. An important longitudinal study on the acquisition of literacy and Arabic reading skills was done by Wranger in Morocco (Wagner, Spratt, & Ezzaki, 1989; see also, Wagner, 1993). Wranger and his colleagues investigated whether preschool experience with a spoken Moroccan Arabic dialect facilitates literacy acquisition differently than preschool experience with Berber, which is a member of the Hamitic family of languages and has no semantic or syntactic similarity to Arabic. This study compared the performance of monolingual and bilingual Arabic- and Berber-speaking children in learning to read MSA and French. The results showed an advantage for the children whose mother tongue was the Arabic dialect over Berber-speaking children in MSA. In contrast, the preschool experience of the two languages groups had little effect in learning to read French. The researchers concluded that the superiority of the Arabic speaking children in the in the early stages of MSA literacy acquisition is due primarily to the substantial similarity and transfer from spoken Moroccan Arabic to MSA, but not to French. Wagner (1993) also showed that knowledge in first grade of Arabic letters, their graphemic variability and pronunciation, predicted more than 30% of the variance in reading achievement 5 years later. Early decoding skills at the single word level explained an additional 14% of the same variance. Wagner concluded that learning to read in Arabic necessitates an even greater reliance on decoding skills than in other languages. Wagner highlights ‘‘the absence of vocalization diacritics as the main reason behind the growing difficulty of decoding for word recognition and paragraph comprehension, a difficulty which mars advanced Arabic reading stages and requires knowledge of appropriately correct inflectional endings and the ability to place full and correct diacritical marking’’ (p. 240). Azzam (1990) examined the misreadings and misspellings that Arab primary school children make and identified vocalization and its use of diacritical markings as the main culprit. Her research seems to suggest that diacritical markings are significantly important in the process of reading and comprehending written language at all levels of Arabic reading. Abu-Rabia (1998) also investigated the effect of vowels on reading accuracy in Arabic orthography. He presented four kinds of written fuṣḥa Arabic texts (narrative, informative, poetic, and Koranic) to sixty-four native Arabic speakers to be read aloud. Three texts of each kind were presented in three reading conditions: correctly vowelized, unvowelized, and wrongly vowelized. The most important finding of this study is that vowels were found to significantly influence the reading of both poor and skilled readers in the four fuṣḥa writing styles in all three

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conditions. It was also found that both skilled and poor readers improved their reading accuracy in all writing styles when they read with vowels. This last study reinforces and supports similar previous findings obtained by Abu-Rabia (1997), where it was demonstrated that the vowels and the sentence context were significant factors for word recognition for both skilled and poor fuṣḥa readers. Thus, vowel diacritics are automatically processed in Hebrew, and facilitate naming even in skilled readers. However, word recognition in Hebrew can be orthographically based, with vowels, when they are automatically recoded into phonology, actually slowing the process down. In Arabic, the inclusion of diacritics improves reading accuracy of both beginning and skilled readers.

4.2.2 Orthographic Complexity Although Arab children’s scores on tests of phonological awareness were higher than those of monolingual Hebrew speakers, their scores on tests of reading achievement were lower (Eviatar & Ibrahim, 2001; Ibrahim, Eviatar, & Aharon Peretz, 2002). We suggested that this is due to the complexity of Arabic orthography as compared with Hebrew orthography. Indeed, comparing Arabic and Hebrew orthographic systems with English, additional complexity is found in both orthographies but to a much larger extent in Arabic than in Hebrew. The two orthographies differ in two central aspects. The first aspect is related to shape of some letters that differ depending on their placement in the word. This phenomenon is much less extensive in Hebrew than in Arabic. In Hebrew there are five letters that change shape when they are word final: (‫ם‬-‫מ‬, ‫ן‬-‫נ‬, ‫ץ‬-‫צ‬, ‫ף‬-‫פ‬, ‫ך‬-‫)כ‬. The Arabic writing system is an alphabetic system with twenty eight basic consonant letters. Most of these consonants show a very close resemblance in form, with only additional dots or strokes to distinguish them from each other. They are usually composed of one base form and most of them have up to three or four distinct variant shapes. Graphemic variants differ depending on whether they occur in a word in the initial, middle or final position and whether they follow a connecting or a non-connecting letter (for example, the phoneme /h/ is represented as: ). The second characteristic has to do with diacritics and dots. In Hebrew, dots occur only to mark vowels and as a stress-marking device (dagesh). In the case of three letters, this stress-marking device (which does not appear in unvowelized scripts) changes the phonemic representation of the letters from fricatives (v, x, f) to stops (b, k, p for the letters ‫ פ ק ב‬respectively). In the unvowelized form of the script, these letters can be disambiguated by their place in the word, as only word or syllable initial placement indicate the stop consonant. In Arabic, the use of dots is more extensive: many letters have a similar or even identical structure and are distinguished only on the basis of the existence, location and number of dots (e.g., the Arabic letters representing /t/ and /n ( )

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become the graphemes representing /th/ and /b/ ( ) by adding or changing the number or location of dots. We tested the hypothesis that the graphemic complexity of Arabic is larger than in Hebrew, and that this results in additional perceptual load (Ibrahim, Aharon-Peretz, & Eviatar, 2002). The subjects tested were all adolescent healthy native Arabic speakers who had mastered Hebrew as a second language. We used oral and visual variants of the trail making test (Reitan & Wolfson, 1993) in both languages. Both versions have two levels of complexity: Level A requires connecting visually numbers or letters in order. Level B in the two modalities requires alternation between letters and numbers. Level B in the oral version requires declamation of the alternation. Performance time was the dependent variable. At the low level of complexity (Level A) there were no differences between performance in Hebrew and in Arabic in either the oral and the visual versions. In the more complex version (Level B), language (Hebrew or Arabic) did not affect speed in the oral version, but in the visual version, Arabic was performed significantly slower than Hebrew. These findings supported our major conclusion that Arabic letters are harder to identify than Hebrew letters as a result of their greater visual complexity. In two divided visual field studies we have shown that Arabic letters are harder to identify than English and Hebrew letters and have suggested that the locus of this difficulty is in the right hemisphere. In the first study (Eviatar & Ibrahim, 2004) we examined directly the effects of grapheme–phoneme conversion in English, Hebrew and Arabic, using a lateralized nonsense syllable identification task. The syllables were constructed as consonant–vowelconsonant (CVC) trigrams (the vowels in Hebrew and Arabic were letters that double as consonants or vowels), and the task of the participants was to identify the three letters. The stimuli were presented vertically in three conditions: left visual field (LVF), right visual field (RVF), and bilaterally (BVF). The participants were university students, native readers of each of the languages. In this study we were interested in errors, so we titrated exposure duration independently for each participant, in order to achieve a duration that resulted in 50% errors. This paradigm allowed us to measure three dependent measures that indexed different aspects of the task. The first measure was the mean exposure duration that was reached in each of the three groups of participants in order to achieve a 50% error rate. This is an index of the speed at which native readers can identify letters in each of the languages. This measure revealed that the Arabic readers required significantly longer exposure durations that the readers of Hebrew and English, and that Hebrew readers required significantly longer exposure durations that the readers of English. Thus, these results suggest that English letters are easier to identify than Hebrew letters, and that Arabic letters are the hardest to identify. The second measure in this study was the total number of errors in each presentation condition (LVF, RVF, and BVF). This measure revealed that all of the participants showed a right visual field advantage (RVFA) that reflects specialization of the left hemisphere (LH) for this linguistic task. This advantage, the difference between performance levels in the

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LVF and in the RVF was significantly larger in the Arabic speakers than in the other groups, as a result of poorer performance in the LVF in Arabic than in the other languages, while performance in the other presentation conditions (RVF, BVF) was equivalent among the groups. The third measure in this study was the difference between errors on the first letter and errors on the last letter of the trigram, a qualitative measure of sequential processing (Levy, Heller, Banich, & Burton, 1983; Eviatar, Hellige, & Zaidel, 1997). This qualitative measure revealed that Arabic and Hebrew speakers evinced a similar pattern that was different from the one shown by the English speakers. We interpreted this as indicating a different division of labor between the hemispheres while reading English or the Semitic languages, and attributed the difference to the demands made by concatenative versus nonconcatenative word morphology. We discuss this issue in more detail below. Of importance to us here is that it took longer for Arabic speakers to identify Arabic letters than it did for Hebrew speakers to identify Hebrew letters or English speakers to identify English letters. In addition, the large difference between performance levels in the two visual fields of Arabic speakers suggested that there are large differences in the abilities of the hemispheres in letter identification in Arabic, but not in the other languages. In the second divided visual field study (Eviatar, Ibrahim, & Ganayim, 2004) we explored the locus of this difference, and showed that adult native Arabic speakers who can read both Arabic and Hebrew, are better at identifying letters in Hebrew than in Arabic, and that the main disadvantage for Arabic letters is in the left visual field, when they are exposed to the right hemisphere (RH). We asked native Arabic speakers and native Hebrew speakers to perform a lateralized letter matching task in both Arabic and Hebrew, using a physical identity criterion (the Arabic speakers were literate in both languages, but the Hebrew speakers could not read Arabic, and thus performed the task as a pattern matching task). The pattern of results in response times was as we expected, revealing a RVFA in all of the conditions in which the participants could read (all except Hebrew speakers in Arabic, who showed a slight LVFA in this condition). The results of the accuracy measure were quite dramatic. In Hebrew, both groups revealed low error rates and equivalent performance in the two visual fields (both hemispheres are able to match letters quite well). In Arabic, the Hebrew speakers made many errors, with equivalent performance in the two visual fields. Arabic speakers revealed good performance in the RVF (their LH was able to match letters in Arabic as well as in Hebrew). In the LVF, however, Arabic speakers made as many errors as Hebrew speakers (who cannot read the language)! We hypothesized that the reason for this RH disadvantage in letter recognition is the complexity of grapheme-phoneme relations in Arabic. In order to examine our hypothesis that the RH cannot differentiate between very similar different letters in Arabic, whereas the LH can do so, we created a global-local task with two types of incongruent stimuli: one where the two letters on the two levels of the hierarchical stimulus were physically very different from each other: ‫ ﺕ‬and ‫ ;ﻡ‬and another where the two letters were very similar to each other: ‫ ﺕ‬and ‫ﺏ‬. Participants were required to

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attend to the local or the global levels of these hierarchical stimuli in different blocks. We measured the difference between congruent (where the same letter was used on both levels of the stimuli) versus incongruent conditions (where the letter in the global level was made out of small versions of the other letter). This difference indicated the degree of interference between the levels. In the first condition, where the letters were very different from each other, we replicated the results of other studies in other languages (e.g., Lamb, Robertson, & Knight, 1990). We found a global precedence (responses to the global level were always faster than to the local level (Navon, 1977)), and an asymmetry in the degree of interference between the two visual fields: stronger interference from the global level to the local level in the LVF, and the opposite pattern in the RVF. This pattern has been used to support the hypothesis that the LH is relatively more sensitive to the local aspects of visual stimuli and that the RH is relatively more sensitive to the global aspects of these stimuli. Most interestingly, however, in the second condition, where the two letters differed only in the number and placement of dots, there was no incongruence effect in the LVF at all, while congruent stimuli were faster than incongruent stimuli in the RVF in the local conditions. These results show that the RH cannot discriminate between letters that differ only in the placement or number of dots (e.g., /t/- ‫ﺕ‬ and /b/ - ‫)ﺏ‬, but that the LH can do so. Thus, in the case of Arabic, an important part of the literacy problem is posed by the Arabic orthographic system and its failure to support easy and efficient reading. Previous research on reading acquisition in the Arabic language has revealed that this process is slower than in Hebrew. We have shown that in both beginning and skilled readers, letter discrimination in Arabic is quite difficult. In the next section we examine the effects of word morphology in Arabic and in Hebrew on the process of reading, and on the division of labor between the cerebral hemispheres in the early stages of visual word recognition.

4.2.3 Word Morphology Arabic and Hebrew, as Semitic languages, are characterized by a nonconcatenative, highly productive derivational morphology (Berman, 1978). In both languages words are constructed by combining a consonantal root (that carries most of the semantic information) and a word pattern that includes vowels as well as consonants, and provides information about the word class and its morphological status. Hence, the majority of words in Hebrew and Arabic are at the very least bi-morphemic, but none of the composing morphemes are words by themselves. In most words, the core meaning is conveyed by the root, while the phonological pattern conveys word class information. For example, in Arabic the word (TAKREEM) consists of the root (KRM, whose semantic space includes things having to do with respect) and the phonological pattern TA- -I-. The combination results in the word ‘‘honor.’’ The letters that make up the root may be dispersed across the word, inter-digitated with letters

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that can double as vowels and other consonants that belong to the morphological pattern. Roman and Pavard (1987) used oculomotor recording techniques to evaluate visual scanning strategies. They found that although mean reading time did not differ between Arabic and French texts (note that for conveying identical content, the number of words needed in Arabic is less than in French because Arabic morphology is more dense), gaze duration per word was significantly longer in Arabic (342 ms) than in French (215 ms). This phenomenon also has been found in comparisons of Hebrew and English text reading, in which the morphology of Hebrew is dense and similar to that of Arabic, and English morphology is concatenative and more similar to French (Shimron & Sivan, 1994). A number of psycholinguistic studies (Frost & Bentin, 1992; Frost, Katz & Bentin, 1987; Deutsch, Frost, & Forster, 1998; Berent, 2002) have explored the effects of the morphology and orthography of Hebrew on lexical access and the structure of the mental lexicon. One of the conclusions from these studies is that the nonconcatenative and agglutinative morphological structure of Hebrew, together with the distributional properties of abstract word forms, results in the inclusion of subword morphological units in the mental lexicon of Hebrew speakers. Similarly, Prunet, Beland, and Idrissi (2000) report a case study of an Arabic-French agrammatic patient, who showed identical deficits in the two languages, except for a specific type of error, metathesis, in which he modified the order of the root consonants, with the vowel patterns remaining intact, only in Arabic, not in French. They interpret this finding as reflecting the manner in which words are stored in the mental lexicon in the two languages: whole words plus affixes in French, and roots plus word patterns in Arabic. These findings converge with the conclusions of Eviatar (1999, Experiment 4) and Eviatar and Ibrahim (2004), who showed that nonsense CVC trigrams are processed sequentially in both visual fields in English, but in neither visual field in Hebrew and in Arabic, and hypothesized that this is because Hebrew and Arabic nonwords cannot be read sequentially. A similar conclusion for words was reached by Farid and Grainger (1996), who showed that the location of initial fixation in a word is different in French and in Arabic words. In French, fixation slightly to the left of the word’s center results in best recognition for both prefixed and suffixed words, while in Arabic, prefixed words result in best recognition from leftward fixations and suffixed words result in best recognition from rightward initial fixations. They suggest that this is due to the greater importance of morphological structure in Arabic, because ‘‘. . .much of the phonological representation of the word can be recovered only after successfully matching the consonant cluster to a lexical representation’’ (p. 364), that is, after extraction of the root. Berent (2002) has also concluded that in Hebrew, ‘‘Speakers decompose the root from the word pattern in on-line word identification. . .’’ (p. 335). Most recently we reported that the different manner in which words are constructed in English and in Hebrew and Arabic has an effect on the division of labor between the cerebral hemispheres in a lateralized lexical decision task

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(Eviatar & Ibrahim, 2007). We presented native speakers of Arabic, Hebrew, and English with morphologically simple and complex words and nonwords in their native language, and measured indexes of hemispheric integration. Morphological complexity was operationalized differently in English than in the Semitic languages. In English we defined monomorphemic words as morphologically simple, and derivations (e.g., farmer¼farmþer) as morphologically complex. Morphologically complex nonwords were made up of legal morphemes in illegal combinations (e.g., logly). In Arabic and in Hebrew we defined a word as morphologically simple if the rootþwordform structure was not transparent (e.g., the word is not easily divisible into these morphemes or the root is not generative, and appears only in that form), and as morphologically complex if it was easily and transparently divisible into these elements. Morphologically complex nonwords were created by inserting nonexistent roots into legal wordforms. In English, we replicated the findings of previous studies: similarly to Iacoboni and Zaidel (1996), we showed that while the RH is able to independently recognize nonwords; it draws upon resources of the LH when encountering words. Similarly to Burgess and Skodis (1993) in English, and to Koenig, Wetzel, and Caramazza (1992) in French, we showed that for the English speakers, only the LH was sensitive to the morphological complexity of the stimuli. Morphological complexity affected words and nonwords in the same manner, with complex stimuli requiring longer latencies to be identified either as a word or as a nonword only in the RVF. As opposed to the English speakers, both groups of speakers of the Semitic languages showed bilateral sensitivity to morphological complexity. In addition, the Arabic and Hebrew readers showed higher values on our indexes of interhemispheric integration, suggesting more intensive hemispheric cooperation during the reading of Hebrew and Arabic than of English. Interestingly, in both languages, morphological complexity had opposing effects for words and for nonwords. Morphological complexity, or transparency of the root þ word form structure, facilitated the recognition of words and decelerated the rejection of nonwords. We suggested that the nonconcatenative morphology of the Semitic languages, in which words are analyzed into their root and word-form constituents, requires that both hemispheres be sensitive to morphological structure. The automatic analysis of a character string into a recognizable word-form and a root resulted in faster recognition of complex words than of the simple words, which are not divisible in this way. This analysis also resulted in slower responses to complex nonwords than to simple nonwords, which did not contain a recognizable word form. Thus, the word form made complex nonwords more ‘‘word-like’’, requiring a more intensive search before they could be correctly rejected in the lexical decision task. In general, we found that the manner in which words are formed in these different languages resulted in different types of interhemispheric division of labor in the lexical decision task. Specifically, we showed that when languages

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make different types of demands upon the cognitive system, interhemispheric interaction is dynamic and is suited to these demands. Arabic and Hebrew require a higher level of interhemispheric interaction than does English.

4.3 Reading in the Non-native Language Recently we have examined the interaction of the effects of reading Arabic and other languages (Ibrahim & Eviatar, 2009). We took advantage of the high facility of Arab university students in Hebrew and English, in order to examine the manner in which such multilingual brains deal with word morphology. We used the same paradigm described above, with trilingual Arab participants making lexical decisions on morphologically simple and complex words and nonwords, in Arabic, in Hebrew, and in English. One of the interesting results from this study is that in the RVF/LH there was a significant difference between performance levels in the three languages, reflecting significantly better performance in Arabic, which these participants learned to read first, than in Hebrew and English, which these participants consider their nonnative languages. However, in the LVF/RH, there was no difference between performance levels in the three languages. We interpret this as reflecting the specific RH deficit in reading Arabic, which lowers performance in the LVF for this language, such that it is not better than the second and third languages, in which these participants have lower facility. Another interesting result from this study is that the participants showed the same patterns of interhemispheric cooperation in the three languages, suggesting that they used the same reading strategies in all of the languages. For Hebrew, the patterns are similar to the ones shown by native Hebrew speakers, suggesting that morphological processes are similar in these similar languages. However, the patterns shown by native Arabic speakers in English are different from the patterns shown by native English speakers. Thus, our participants were reading a second (or third) language with the same mechanisms as the first learned language. This type of pattern was also reported by Eviatar (1999) for native Hebrew readers recognizing nonsense syllables in English. Eviatar (1999) suggested that this is due to the demand for morphological decomposition in Hebrew that determines reading strategies for other languages as well. The results reported here suggest that these same demands occur for Arabic readers.

4.4 Concluding Remarks In this chapter we discussed the Arabic literacy problem by taking up an important issue in the study of multilingual processing and languages’ representation. One of the critical issues discussed was whether the representations of native spoken language of Arab speakers (SA) and written Arabic (MSA) by literal

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Arabic speakers are organized in a typical L2 to L1 relationship. The evidence we presented in our series of studies revealed that spoken and literary forms of Arabic are treated by proficient speakers/readers as different languages. This conclusion, in concert with previous findings (Wagner et al., 1989, Azzam, 1990; Ayari, 1996; Maamouri, 1998; Abu-Rabia, 2000; Saiegh-Haddad, 2003) suggests that the diglossic situation in Arabic might be related to some of the hardships that native Arabic beginning readers encounter and might even hinder their acquisition of basic academic skills. An additional important part of the Arabic literacy problem is posed by the Arabic orthographic system and its failure to support easy and efficient reading (Ibrahim et al., 2002). In subsequent studies we have shown that Arabic letters are harder to identify than English and Hebrew letters and have suggested that the locus of this difficulty is in the right hemisphere (Eviatar & Ibrahim, 2004; Eviatar et al., 2004). From the neuropsychological perspective, we discussed how an individual’s language experience influences the amount of hemispheric interaction during language processing, as indexed by the degree of difference in visual field asymmetry in unilateral versus bilateral presentation conditions during a visual lexical decision task. Under the premise that larger asymmetries during bilateral presentation reflect increased interhemispheric disruption and presumably therefore imply interhemispheric cooperation under normal conditions, we found that when languages make different types of demands upon the cognitive system, interhemispheric interaction is dynamic and is suited to these demands. Arabic and Hebrew require a higher level of interhemispheric interaction than does English (Eviatar & Ibrahim, 2007). In the light of above, we argue for inclusion of the neurofunctional perspective as a comprehensive basis for the discussion of teaching second language (L2). After all, teachers deal every day with the ability of students to learn and they necessitate the knowledge of the structural relationship between languages, of relevant pedagogical methods, to allow them monitoring the learning process, checking if it is optimally effective, and to intervene to shape it toward effectiveness.

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Part II

Academic Achievement of Children Coming from Immigrant Families

Chapter 5

Cognitive, Language, and Literacy Development in Socio-culturally Vulnerable School Children – The Case of Ethiopian Israeli Children Michal Shany and Esther Geva

5.1 Introduction Israel is an immigration country. New immigrants are faced with the challenges of acculturation to new norms, values and expectations (Berry, 2003). This chapter is concerned with the children of immigrants who came to Israel from Ethiopia in the last two decades. According to official statistics of the Israeli Municipalities (2006, 2007), children of Ethiopian families constitute 10% of the immigrant children living in Israel. Various reports suggest that the school dropout rates in this community is twice as high as in the general population. The picture emerging from various reports (e.g., Levin et al., 2002) and from the media (e.g., Yediot Axronot, January 1, 2008) is that the academic achievement of children in this group is especially low, and that a disproportionate number of children from this community are placed in special education programs (Berhanu, 2005). Factors associated with different cultural norms and expectations (Levin-Rozalis & Shafran, 2003; Berhanu, 2005; Bar-Yosef, 2001), conformity to strongly entrenched traditional norms (for example, obedience to elders of the family and the entire adult community, being quiet and respectful), different patterns of socialization, and external locus of control, have been offered as processes that contribute to the academic failure of individuals from this group in the host country (Horowitz & Mosher, 1997; Korten, 1972). Concomitant with the absence of literacy skills in their home language, the Ethiopian Israeli students need to develop their language and literacy skills in a language (Hebrew) that is different from the language spoken at home (Amharic). To date, most reports involving students from the Ethiopian immigrant community have focused on gaps in general academic achievement between this group and other immigrant groups, or in comparison to the general population (e.g., Levin et al., 2002; Meitzav, 2006; Brookdale Institute, 2003). Indeed, there is a growing body of research focusing on the language and literacy skills of M. Shany (*) Department of Learning Disabilities, Faculty of Education, University of Haifa, Haifa, Israel e-mail: [email protected] M. Leikin et al. (eds.), Current Issues in Bilingualism, Literacy Studies 5, DOI 10.1007/978-94-007-2327-6_5, Ó Springer ScienceþBusiness Media B.V. 2012

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various groups of immigrants, but this research has involved immigrants who are literate to varying degrees in their first language (L1). To date, however, no studies examined systematically, and in depth the development of components of language and literacy development in a large representative sample of Ethiopian students. This chapter addresses this dearth. Given global demographic immigration trends, a careful analysis of the situation in the Ethiopian immigrant community in Israel is important because it likely mirrors other similar immigrant communities elsewhere. In particular, even though in the last decade the number of studies examining the development of language and literacy skills in second language (L2) learners has mushroomed, very little is known about the development of language and literacy skills in immigrant school children who are expected to transition rapidly from an oral society to a Westernized, literate society. In this chapter, we report on research that targeted development in a number of related domains that underlie literacy development. In particular, the research focused on the cultural, cognitive, language and literacy development of this vulnerable group of minority children, whose parents made an abrupt transition from Ethiopia to Israel in the 1980s and 1990s (Bender, 1985; Shenkut, 1991). This cross-sectional study of Ethiopian Israeli children in grades one-to-six provides a window into development in the cognitive, linguistic, cultural, and literacy domains. We compare the performance of the Ethiopian Israeli children to that of their Non-Ethiopian peers, who live in the same poor communities, and attend the same classes. The following key questions are examined in this chapter: 1. Are there gaps between low SES Ethiopian Israeli and Non-Ethiopian groups on cultural, cognitive, linguistic, and literacy dimensions? 2. In what domains do skill gaps that exist in the primary grades disappear in higher grades? 3. In what domains do skills gaps persist or increase? In order to better understand the issues facing the Ethiopian Israeli community it is essential to consider key aspects of the historical, socio-cultural, economic, and educational context of this community. It is also important to discuss briefly the research literature concerning the development of language and literacy skills in the societal language of children who speak a different language at home. Before we launch into a description of the study, we provide in the next two sections an overview of these two areas.

5.1.1 The Ethiopian Israeli Community: The Socio-cultural Context 5.1.1.1 Transition from Ethiopia to Israel Along with other groups, many Ethiopian Jews fled from Ethiopia to Sudan in the 1970s due to a civil war and famine, and lived in refugee camps. Subsequently, many Ethiopian Jews arrived in Israel in a number of waves in the

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mid-1980s and 1990s. The migration experience was especially traumatic (Bar-Yosef, 2001) and arrival in Israel led to major changes in community organization (Berhanu, 2005). The bulk of this community was rural and there is evidence that the communal, patriarchal and interconnected community structure already began to crumble with the transition to refugee camps. This process continued with the abrupt cultural changes that took place as a result of contact with Israeli society (Ben-Ezer, 1992; Berhanu, 2005; Bodovski, David, & Eran, 1994; Kaplan, 1992). The majority of Ethiopian immigrants came from a rural, oral tradition society, where over 90% of the community members were illiterate (Bender, 1985; Shenkut, 1991). In Ethiopia they lived within a traditional structure, consisting of compounds of the larger kinship group. The communities were led by elders and traditional priests who played an important role in maintaining and transmitting communal-cultural knowledge (Bodovski et al., 1994). 5.1.1.2 Employment, Education, Acculturation, and Language Proficiency The declared policy of the Israeli government is to spread the immigrants from Ethiopia throughout the country. However, according to an official report of the Israeli Knesset (Parliament) in Israel (Vertsberger & Noyfeld, 2003), based on the 2002 census, most congregate in a small number of towns in the North and Center of Israel, and live in very poor neighborhoods. Most Ethiopian immigrants are unskilled workers, and the unemployment rate among the Ethiopian community living in Israel is higher than in the general population (Svirsky & Svirsky, 2002). Over 52% of Ethiopian families live below the poverty line, in comparison with 16% in the general population (Bank of Israel, 2006). Wide cultural, social, occupational, and literacy differences between the community of Ethiopian origin and the host Israeli society persist (Bodovski et al., 1994; Levin-Rozalis, 2000; Gaon, King, & Volda-Tzadik, 2006; Offer, 2004). More recent statistics provide a more promising picture. Whereas in the mid-90s, 55% of adults of Ethiopian origin ages 22–64 had no formal education, in recent years this rate has dropped to 42%. Another promising statistic is the fact that the number of individuals who obtained at least high school education has increased from 6% to 15% (Israel Statistical Municipalities, 2006, 2007). As might be expected in any group of immigrants, about 40% of the immigrants who came in the 1980s and 1990s, and 60% of more recent immigrants from Ethiopia indicate that they have only minimal command of Hebrew. In addition, 55% of the male adults cannot read or write Hebrew, and this percentage is even higher among women (70%) (King, Effrati, & Netzer, 2003). In comparison with other immigrant groups, the linguistic integration of immigrants from Ethiopia has been alarmingly slow (Barkon & Avinor, 1995, Bar-Yosef, 2001; Spolsky, 1996). Upon arrival to Israel, Ethiopian adults could attend a 1-year intensive Hebrew language and literacy program, known as Ulpan. In our sample about 35% of the mothers and fathers attended this

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basic, Hebrew based, adult education program, and for many this was the first time they were exposed to written language of any sort. In Ethiopian culture, the main responsibility of fathers is to ensure that their children behave properly and respect the elders of the family (Berhanu, 2005; Horowitz & Mosher, 1997; Korten, 1972; Yediot Axronot, January 1, 2008). But in Israel the children speak Hebrew better than their parents, and as a result the balance of power in the home has shifted to other family members, and the fathers do not bare the same authority (Segal, 2006). Once their children begin to attend school Ethiopian Israeli parents tend to be less involved, since they feel that the school is an official authority that bears responsibility for their children’s education. However, the schools interpret this lack of involvement as lack of interest (Bar-Yosef, 2001; Stravas & Olshtain, 2006). Most Ethiopian immigrant families do not share with the Israeli school system a language or concepts about the actual role that parents in other segments of Israeli society are likely to undertake in the ‘‘education enterprise’’ of their children (Stravas & Olshtain, 2006). In this regard, it is useful to borrow from sociology the ‘‘cultural capital’’ framework (Bourdieu & Passeron, 1990). Cultural capital involves the maintenance and transmission of forms of knowledge, values, education, and expectations, and includes the interplay of individual values and attributions, cultural goods (e.g., books, computers), and educational institutions such as academic credentials and diplomas. According to Bourdieu and Passeron (1990) disadvantages and inequalities are maintained from one generation to the next, partly through the educational system that reproduces social structures. Using this framework, it is possible to see that the Ethiopian Israeli community does not possess the cultural capital resources that would enable it to transmit to their children the modes of language, literacy, and strategic skills that are crucial for further learning in a westernized culture. From a socio-cultural perspective, it is obvious that there is no ‘‘fit’’ between children’s home culture and the culture of the school and classroom. According to this view, poor academic performance does not necessarily reflect the negative influence of children’s home cultural characteristics on their learning, but rather, the inability of schools to adapt instruction to relevant aspects of children’s home cultures (Rueda, August, & Goldenberg, 2006). In spite of various well-intentioned programs, it has been difficult to bridge the difference between Ethiopian and Israeli cultural values, attributions, and expectations. The prevailing societal view is one of deficit, and as a result the community has been further alienated from the mainstream culture. 5.1.1.3 Academic Achievement A recent, large scale, comprehensive study of academic achievement in mathematics and literacy skills compared the achievement of children of Ethiopian and Russian immigrants to that of non-immigrant Israeli students, in Grades 5, 10 and 11 (Levin et al., 2002). In general, achievement scores in both immigrant groups were lower than those of the non-immigrant comparison group.

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However, the researchers found that the literacy skills of immigrant students from Russia catch up after 10–11 years of schooling in the societal language, and already by Grade 9 the gap is rather small. However, the performance of youth of Ethiopian origin is consistently lower than that of the Russian immigrant and non-immigrant students, and the gaps in academic achievement continue to be rather large even for the 10% of Ethiopian students who complete their high school education (Levin et al., 2002). According to Barkon and Avinor (1995), young children growing up in Ethiopian families are exposed to oral Amharic at home, but immigrant adolescents have lost their L1 (Amharic) skills, and they continue to have poor Hebrew language proficiency. Other research has shown that, over and above Socio-Economic Status (SES), parental education correlates with educational outcomes for immigrant children (Hooddinoot, Lethbridge, & Phipps, 2002; Willms, 2003). In addition, research has shown that both home-based and community-based variables mediate language and literacy achievement and are significant predictors of language and school achievement (Leseman & de Jong, 1998; Willms, 2003). In this regard, one would not expect perhaps that children of Ethiopian Israeli immigrants who live in poverty should fare any better than children of other communities who live in poverty. However, as is evident from the discussion above, in this community one notes the interaction of a number of familial and community level risk factors, including the break-up of traditional institutions, and diminishing exposure to traditional modes of literacy (Segal, 2006). Other interacting factors include societal prejudice, lack of fit in cultural resources between the culture of origin and the host country, poverty and living in poor communities, and having parents who come from a culture that is predominantly oral. Poverty interacts with societal power relations that prevent the minority group from ensuring that aspects of the curriculum, assessment, and teacher education reflect and acknowledge the values of the vulnerable community and its modes of transmission (Cummins, in press). On the whole, these factors come together to create a challenging backdrop against which children of immigrants from Ethiopia need to develop language and literacy skills and achieve academically.

5.2 Theoretical Framework: L2 Literacy Development Reading, writing and language skills are complex cognitive activities involving sub-components that interact with each other and affect each other. Even though the Ethiopian Israeli children are known to be underachieving academically, it is not known to what extent they underachieve on all aspects of language and literacy, nor has their performance on various language and literacy skill components been examined developmentally. The recent literature on language and literacy development in second language (L2) learners is of some relevance in the present context.

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5.2.1 Word Level Skills in L2 Learners Some might expect that due to lack of language proficiency in the target language, students learning to read in L2 might have poorer word level reading skills than monolingual (L1) students. However, the conclusions of a recent comprehensive systematic review conducted by the National Literacy Panel (NLP), that focused on research on students who develop their language and literacy skills in a language different from their home language (August & Shanahan, 2006), are more nuanced. It appears that the difference between language-minority students and their native-speaking counterparts on word level skills such as word recognition, decoding, and spelling is not very robust. This general conclusion is based on studies involving immigrant children learning English (the societal language) as their second language (ESL) with various home languages, including Punjabi (Chiappe & Siegel, 1999), Urdu (Mumtaz & Humphreys, 2001), Italian (D’Angiulli, Siegel, & Maggi, 2004), Portuguese (Da Fontoura & Siegel, 1995), Spanish (Durgunoglu, Nagy, & Hancin-Bhatt, 1993; Lindsey, Manis, & Bailey, 2003) and from various other ESL backgrounds (Lesaux & Siegel, 2003; Chiappe, Siegel, & Wade-Woolley, 2002; Geva, Yaghoub-Zadeh, & Schuster, 2000; WadeWoolley & Siegel, 1997). This conclusion has also been reached with regard to other language combinations such as Turkish-Dutch (e.g., Verhoeven, 1990), Arabic-English (Abu-Rabia & Siegel, 2002), English-Farsi (Arab-Moghaddam & Seńećhal, 2001; Gholamain & Geva, 1999) and French-English, (Comeau, Cormier, Grandmaison, & Lacroix, 1999; Lafrance & Gottardo, 2005). The overall conclusion from these studies is that accurate word level skills are not heavily dependent on oral language proficiency. Of particular relevance are a number of studies that focused on the word level skills of English speaking children who were learning Hebrew in bilingual English-Hebrew schools (Geva & Siegel, 2000; Geva & Wade-Woolley, 1998; Geva, Wade-Woolley & Shany, 1997; Wade-Woolley & Geva, 2000). These studies have shown that in spite of limited language proficiency in Hebrew, these middle-class children can learn to decode and spell Hebrew words with accuracy, and decode Hebrew words with efficiency. These outcomes can be understood to some extent by considering typological differences in orthographic and language features (Katz & Frost, 1992). Thanks to the simplicity of the phonological structure of Hebrew (Ziegler & Goswami, 2005; Share, 2008), the lexical outcome of assembling into words a series of matched graphemephonemes in vowelled Hebrew is unequivocal, and can be accomplished with accuracy even in the absence of linguistic proficiency. In this regard, Share (2008) concludes in a recent review that ‘‘These findings converge on the conclusion that both lexical and extra-lexical factors, such as syntax and vocabulary, are superfluous when spelling-sound relations are straightforward, but are indispensable when the orthography is opaque.’’ This observation should apply to immigrant children whose Hebrew language proficiency is underdeveloped, including the Ethiopian Israeli children who were the focus of this study.

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5.2.2 Reading Comprehension and L2 Learners Successful reading comprehension requires the integration of various component skills, including accurate and efficient word reading, reading fluency, awareness of text features, language proficiency (including vocabulary, morphological, grammatical, and pragmatic skills), background knowledge, and various reading strategies (Deacon & Kirby, 2004; Mu¨ller & Brady, 2001; Pressley, 1998; National Reading Panel, [NRP], 2000; RAND). Recent studies of language-minority students indicate that the reading comprehension performance of minority students falls well below that of their native-speaking peers (Lesaux & Geva, 2006). As part of the NLP systematic review, the authors of one of the chapters (Lesaux & Geva, 2006) conclude that numerous variables at the individual level (e.g., L2 vocabulary, background knowledge, motivation) and contextual level (e.g., familiarity with text structure conventions, home literacy, demographics) affect the second-language reading comprehension of language-minority students. Various variables contribute to L2 reading comprehension, including word level reading skills such as automatic word recognition and decoding skills (Reese, Garnier, Gallimore, & Goldenberg, 2000; Verhoeven, 1990), metalinguistic awareness (Carlisle, Beeman, Davis, & Spharim, 1999), background and cultural knowledge (Carlisle et al., 1999; Droop & Verhoeven, 2003; Lee & Schallert, 1997), the use of cohesion markers and reading strategies (Padroń & Waxman, 1988), and language skills, including vocabulary, morphological and syntactic knowledge (Droop & Verhoeven, 2003; Geva & Yaghoub-Zadeh, 2006; Nakamoto, Lindsey, & Manis, 2008; Proctor, Carlo, August, & Snow, 2005; Yaghoub Zadeh, Farnia, & Geva, 2011). As noted above, in spite of poorer L2 language proficiency, L2 learners do not typically differ on basic word-based skills such as word recognition, pseudoword decoding and spelling. However, L2 oral language comprehension skills are strongly and consistently related to text comprehension. As noted in the NLP systematic review, demographic factors such as parental education and poverty indicators have also been consistently shown to be related to reading comprehension of minority students (Lesaux with Koda, Siegel, & Shanahan, 2006). In general, the more home literacy experiences and opportunities children have, the more likely they are to do well on literacy outcomes (Goldenberg et al., 2006). In addition, research on the contributions of home practices has shown that the attitudes, literacy related activities, and the degree of linguistic sophistication that children are exposed to at home from an early age have a long lasting impact on later academic achievement (August & Shanahan, 2006). However, for children who come from cultures that do not promote written language literacy, there may not be a fit between the language, learning and strategies that are utilized and valued in the L2 environment and the skills and values fostered at home.

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According to the ‘‘Linguistic Interdependence Hypothesis’’ (Cummins, 1991), reading skills in the native language (L1) will transfer to reading in the L2, provided that an adequate level proficiency in the L2 has been achieved. As part of the NLP review Dressler and Kamil (2006) conclude that there is evidence for cross-language transfer of reading comprehension ability in bilinguals speaking different languages (e.g., Lee & Schallert, 1997; Reese et al., 2000; Royer & Carlo, 1991; Verhoeven, 1994). Indeed, transfer effect has been noted in various studies involving minority language students. Importantly, Gersten (1999) cautions, however, that transfer of skills from the L1 to the L2 will occur when well trained teachers deliver adequate L2 instruction. In the present context, where there is no systematic exposure to the language and literacy skills of the home language and where the teachers are less likely to be trained in adequate L2 instruction, such transfer is less likely to occur.

5.2.3 Underlying Cognitive-Linguistic Processes in L1 and L2 Moving from contextual to intra-individual factors, studies examining underlying processing skills have consistently found that cognitive skills such as phonological processing skills, including phonemic awareness, rapid lexical access, and phonological memory, predict word identification skills in English, the L2. (For more details see the conclusion of the NLP report, August & Shanahan, 2006). Another body of research has examined cognitive and neurological processes that underlie the reading process in spite of typological differences in the spoken language or the orthography. The focus of these studies has been on examining ‘‘universal’’ cross-linguistic commonalities and ‘‘typological’’ differences in the role processes such as phonemic awareness and rapid serial naming. Support for universal commonalities comes, for example, from studies comparing good and poor readers across orthographies (e.g., Da Fontoura & Siegel, 1995; Katzir, Shaul, Breznitz, & Wolf, 2004). It suggest that regardless of the orthographies involved, bilinguals or L2 learners who have decoding and spelling problems in their native language will have difficulties in their L2 as well. Evidence for typological effects comes from research on bilingual children (e.g., Geva & Siegel, 2000; Geva, Wade-Woolley & Shany, 1993; Mumtaz & Humphreys, 2001; Wang & Geva, 2003; Wade-Woolley & Geva, 2000). This research suggests that the type of reading and spelling errors observed in novice L2 students reflects typological influences. On the whole, this research suggests that the ‘‘typological’’ and ‘‘universal’’ frameworks are complementary (Geva, 2007). In his review, Share (2008) argues that ‘‘accuracy. . .is largely a non-issue for the majority of the worlds’ (alphabetic) orthographies in which performance levels approach ceiling by the end of Grade 1 (Seymour, Aro, & Erskine, 2003)’’, and that ‘‘when accuracy asymptotes quickly, speed and fluency become the discriminating measures of developmental and individual differences. . .’’. In fact, this point is more or less relevant also when ESL readers are compared to non-ESL readers. For example, Geva and Yaghoub-Zadeh (2006) examined the

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extent to which ESL and monolingual English speakers are similar on various aspects of reading fluency, and whether reading fluency in ESL and monolingual children can be understood in terms of similar underlying processing components. In spite of an oral language proficiency advantage in the English monolingual group, they did not have an advantage on any of the cognitive and reading measures. Two robust predictors of word reading fluency in both language groups were rapid automatized naming (RAN) and phonological awareness (PA), though oral sentence comprehension made a modest contribution as well. Of particular relevance here are two additional studies by Geva and her colleagues (Geva et al., 1993, 1997). Geva et al. (1993) provide evidence that phonemic awareness may play a more temporary role in learning to read Hebrew than it does in English. In that study the authors found a correlation of 0.62 between word reading and phonemic awareness in children’s L1 (English), but only 0.32 for Hebrew (the L2). Geva et al. (1997) found that reading efficiency indices (based on accuracy and speed) of word recognition in L1 (English) and L2 (Hebrew) were very similar, though when it came to reading simple narratives children were more efficient in English, their L1, than in Hebrew, a language in which their language proficiency was minimal. On the whole then, it appears that processing components such as phonemic awareness and rapid automatized naming (RAN) underlie word-based skills of L2 learners of alphabetic languages, but language proficiency is important for text fluency and text comprehension. There is ample evidence that rapid automatized naming may be a strong(er) predictor of reading fluency in regular writing systems such as Hebrew and Dutch (Breznitz, 2006; de Jong & van der Leij, 2003; Wimmer, 1993) than in writing systems that are not as regular, such as English. As for L2 children, there is evidence that ESL readers may be slower at naming simple items than their L1 counterparts at the beginning of school, but that RAN speed improves and catches up with their L1 peers (e.g., Gholamain & Geva, 1999; Lesaux & Siegel, 2003; Geva & Yaghoub Zadeh, 2006). RAN predicts reading accuracy and fluency in primary level ESL readers (Geva et al., 2000; Geva & Yaghoub-Zadeh, 2006; Lesaux & Siegel, 2003). Given this literature, there is good reason to expect that the performance of Ethiopian Israeli minority children whose Hebrew language skills are developing at school would improve at the same rate as their monolingual counterparts on underlying cognitive processing components such as naming speed and phonemic awareness. However, given the available literature it may be expected that the performance of Ethiopian Israeli minority children on higher level, more complex language and literacy tasks may fall increasingly behind. On the whole, this brief literature review suggests that Ethiopian Israeli minority children will not display serious difficulties on simple cognitive underlying skills related to word-based reading skills, nor will they experience difficulties in developed word-based reading skills. However, it is reasonable to hypothesize that their Hebrew (L2) language skills will continue to be underdeveloped and that, relatedly, they will be having difficulties with reading comprehension.

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5.3 Method 5.3.1 Participants 5.3.1.1 Children The sample consisted of 326 children, 175 Ethiopian Israeli and 151 NonEthiopians. The participants were drawn from Grades 1, 2, 4, and 6, in six towns in the North and Center of Israel. The Ethiopian Israeli and NonEthiopian participants within each school in each grade level came from the same classrooms. This design enabled us to minimize confounding due to instructional and neighborhood differences between the two groups. The percent of Ethiopian children in each classroom ranged from 48% to 58%, with an average of 53%. The sample consisted of 152 boys, (88 Ethiopians and 64 NonEthiopians), and 174 girls, (87 Ethiopians and 87 Non-Ethiopians). Table 5.1 presents the distribution of participants by group, gender, and grade level. A chisquare analysis, examining the distribution of males and females was not significant (Chi-square (1,1) ¼ 2.034), p ¼ 0.154). Ethiopian and Non-Ethiopian students lived in the same poor neighborhoods. All the Ethiopian participants were students whose families immigrated to Israel from Ethiopia, who were born in Israel or came to Israel before the age of 2. All children from the comparison group of non-Ethiopians were born in Israel to non-Ethiopian families. 5.3.1.2 Families Home Language and Literacy We first present descriptive information about home language, literacy, and poverty indices in the Ethiopian Israeli in comparison with the non-Ethiopian families, whose children participated in the study. We were unable to interview parents directly due to limited access to bilingual interpreters. Instead, this information was obtained through questionnaires filled out by the classroom teachers and the school-home liaisons. The Teacher Questionnaire included questions about demographic and family language and literacy factors. The questionnaire was divided into two main sections. The first section focused on the children and included items such age of onset of kindergarten education, country of birth, gender, spoken language(s) and level of mastery (for target Table 5.1 Distribution of participants by ethnicity, gender and grade levels Ethiopians Non-Ethiopians Grade level Boys Girls Total Boys Girls Total Total sample Grade 1 Grade 2 Grade 4 Grade 6 Total sample

34 18 19 17 87

24 24 20 19 87

58 42 39 36 175

20 14 14 16 64

22 20 22 23 87

42 34 36 39 151

100 76 75 75 326

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children and their parents). The second part focused on family variables such as parental occupation, number of children and other adults living with the family, number of rooms, and level of mastery of spoken and written language skills in Hebrew and Amharic. It should be noted that since all participants were drawn from the same neighborhoods and schools, inspection of the questionnaires revealed that the reported demographic data did not differ across grades. Therefore, we report the aggregate data for the whole sample. Among the Ethiopian mothers, 1.1% spoke only Hebrew, 72.5% spoke a mixture of Hebrew and Amharic, and 26.5% spoke only Amharic. Among the non-Ethiopian mothers, 57.1% spoke only Hebrew at home and 42.9% spoke a mixture of Hebrew and one of 9 other languages (including Russian, Kavkaz, followed by French, Persian, Kurdish, Romanian, Spanish, and Portuguese). The difference in distribution between the Ethiopian and non-Ethiopian groups in terms of maternal literacy (in Hebrew and/or another language) was significant (Chi-square (3,1) 347.16, p < 0.0001). The patterns are highly similar for fathers, except that among Ethiopian fathers (in contrast with Ethiopian mothers), 30.5% speak only Amharic, and have no proficiency in Hebrew. It was impossible to collect reliable information about parental education. Based on national surveys, Gould, Lavy, and Paserman (2004) report that parents of Ethiopian children typically have 1 or 2 years of education, compared to an average of over 11.5 years for parents of Israeli Jewish children. There is no reason to believe that these national patterns do not apply to the Non-Ethiopian parents in our sample. Poverty A series of t-tests was used to compare the groups on available poverty indicators. Significant differences between the Ethiopian and Non-Ethiopian groups were found on: (a) mean number of rooms at home: M ¼ 3.45 (SD ¼ 0.90) in the Ethiopian families versus M ¼ 4.09 (SD ¼ 1.28) in non-Ethiopian families (t (1, 315)¼ 5.07, p < 0.0001); (b) mean number of family members per household: M ¼ 7.41 (SD ¼ 2.21) in the Ethiopian families versus M ¼ 5.54 (SD ¼ 1.26) in non-Ethiopian families (t (1,172) ¼ 7.02, p < 0.0001); and (c) density (mean number of persons per room): M ¼ 4.50 (SD ¼ 2.23) in the Ethiopian families versus M ¼ 2.33 (SD ¼ 1.51) in non-Ethiopian families (t (1, 165) ¼ 7.77, p < 0.0001). On all these indicators the Ethiopian families fared worse than the Non-Ethiopian families. Parent employment was rated according to a three-level scale: 1 ¼ unemployed; 2 ¼ unskilled work; 3 ¼ skilled work. The results indicated that the vocational training level of the NonEthiopians was significantly higher, M ¼ 2.27 (SD ¼ 0.63) versus M ¼ 1.83 (SD ¼ 0.69) among the Ethiopian workers (t (1, 260) ¼ 5.36, p < 0.0001). Overall, 30.5% of the Ethiopian fathers and 54% of the mothers were unemployed, versus 5.9% of the non- Ethiopian fathers and 28% of the non-Ethiopian mothers. Again, these differences were significant for both fathers (Chi-square (6,6) 29.0 p < 0.0001) and mothers (Chi-square (6,6) 36.05 p < 0.0001). These differences are in line with various reports based on national surveys.

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5.3.2 The Curriculum The Ethiopian and Non-Ethiopian children learn the regular, centralized, curriculum, designed by the Ministry of Education (http://cms.education.gov.il). In elementary schools in Israel, minority children do not receive any formal instruction in their home language.1 In another study based in the same dataset, BenDavid (2005) reported that the Ethiopian children had very little proficiency in Amharic and that very few were able to engage in simple conversation in Amharic. Similar results were reported for Ethiopian children in kindergarten (Shany, Geva, & Melech, 2010). In informal communication (Dec 26, 2007), Ministry of Education supervisors indicated to us that various enrichment programs are available, but implementation is not compulsory or systematic, and that it depends on funding allocation by the municipality and local decisions at the school level. Enrichment programs were more likely to be implemented in the early years following immigration than it has been in more recent years. No formal followup on these programs, their implementation and outcomes is available.

5.3.3 Measures 5.3.3.1 Cognitive Non-verbal Ability The Raven’s Matrices test (Raven & Court, 1976) was administered. This test is designed to assess non-verbal intellectual and reasoning ability and the ability to make sense of increasingly complex visually presented stimuli, to draw meaning out of ambiguity and to perceive and think clearly. The test, considered by some to be relatively culture-free, consists of 5 subtests. Scores can range from 0 to 36, and the analyses were based on raw scores because norms for immigrant children are not available. Age in months was used to control for developmental effects where relevant. Rapid Automatized Naming (RAN) Object Naming Speed (RAN-O): This subtest of the reading and writing diagnostic test ‘‘Alef Ad Taf’’ (Shany, Lachman, Shalem, Bahat, & Zeiger, 2006) consists of pictures of 5 objects: flower, cat, book, watch and flag, each repeated randomly 10 times. The 50 printed objects are printed on a sheet (10 items per line) and the child is asked to name them out loud as fast as s/he can. Practice items ensure that the child is familiar with the names of the objects. Results are reported in terms of time (in seconds) to name the objects. Reliability 1

Beginning in Grade 7, some schools offer weekly, 2–3 h of instruction in the home language (http://cms.education.gov.il).

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(correlation with Rapid Alternate Stimulus subtest, Shany et al., 2006) is r ¼ 0.61 for Grade 2, r ¼ 0.59 for Grade 4, and r ¼ 0.63 for Grade 6. Digit Naming Speed (RAN-D): This subtest (Shany et al., 2006) consists of 5 digits: 1, 5, 9, 3 and 7. Each digit is repeated randomly 10 times. The 50 digit, printed on a sheet (10 items per line) are presented to the child, who has to name them as fast as s/he can. Practice items ensure that the child is familiar with the names of the digits. Results are reported in terms of time (in seconds) to name the digits. Reliability (correlation with RAN-L subtest, Shany et al., 2006) is r ¼ 0.74 for Grade 2, r ¼ 0.69 for Grade 4, and r ¼ 0.67 for Grade 6. Letter Naming Speed (RAN-L): This subtest (Shany et al., 2006) consists of 5 Hebrew letters: ‫( ס‬/s/), ‫א‬, (/a/), ‫ ד‬/d/), ‫( ג‬/g/) and ‫ ל‬/l/), each repeated randomly 10 times. The 50 letters, printed on a sheet (10 items per line), are presented to the child, who has to name them aloud as fast as s/he can. Practice items ensure that the child is familiar with the names of the digits. Results are reported in terms of time (in seconds) to name all the letters. Reliability (correlation with RAN-D, Shany et al., 2006) is r ¼ 0.74, r–0.69, and r ¼ 0.67 for Grades 2, 4, and 6 respectively.

Working Memory This subtest (Shany et al., 2006) was adapted from Daneman and Carpenter (1980). In this test the participant hears sentences, is asked to complete the missing word in each, and then repeat the missing words to all the sentences in the same sequence. For example: The hens lay ___(eggs); An airplane flies in the ___(sky). In this example, the child has to provide the words ‘‘eggs’’ and ‘‘sky’’ and then repeat these two words. The number of items in sets increases gradually from 2 to 6. The child receives one point for each correctly repeated word and an extra point for repeating all the words in each set in the correct sequence. The Cronbach Alpha for this test is 0.81.

5.3.3.2 Cultural Literacy Faces and Places This subtest is taken from the standardized Hebrew version of the K-ABC (Fraser, Shimrovski, Wolf, & Hazani, 1994). The subtest includes 33 pictures involving ‘‘faces and places’’ that have to be named by the participants. The faces and places include famous objects (e.g., Noah’s ark), figures in famous stories (e. g., Pinocchio, Little Red Riding Hood), famous monuments (e.g., the Wailing Wall), and symbols (e.g., the Star of David). Scores can range from 0 to 33, and raw scores were used in the analyses. The split-half reliability of this normed test is r ¼ 0.70.

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5.3.3.3 Language Skills Phonetic Discrimination This subtest was taken from the Diagnostic Battery for Reading Processes in Hebrew (Lachman & Shalem, 1998). Fifteen items were randomly taken from the original test which consists of 30 word pairs. Four items consist of identical pairs and 11 of different pairs. The items may differ on the first, second or the final consonant (e.g., ‘‘safar’’ – tzafar (counted – honked), ‘‘kibel’’ —‘‘kipel’’ (receivedfolded). The tester says each pair one at a time and the child has to say whether the words are ‘‘the same’’ or, ‘‘not the same’’. Scores range from 0 to 15.2 Phonemic Awareness Phonemic awareness was assessed with a subtest of the standardized Alef Ad Taf test (Shany et al., 2006). This subtest focuses on children’s ability to segment spoken real words into phonemes (e.g., ‘‘Say xatul (cat)’’. ‘‘Now say it without the /x/’’ (response: /atul/). This is a more demanding task as the correct response begins with the vowel /a/). None of the outcomes of this phoneme level word manipulation is a real word in Hebrew. National norms are available for this task (Shany et al., 2006). Scores can range from 0 to 16, and Alpha-Cronbach is 0.87 in Grades 2 and 4, and 0.86 in Grade 6. Receptive Vocabulary Children’s command of Hebrew receptive vocabulary was assessed with a standardized Hebrew adaptation of the Peabody Picture Vocabulary Test (PPVT, Dunn, 1965) (Solberg & Nevo, 1979). In this test the child hears a word, is shown four pictures, and is asked to point to the picture that matches the word heard. There are 110 items on the test and testing is stopped when the child makes 6 consecutive errors. National norms are available for this task (Solberg & Nevo, 1979). Split-half reliability for the Hebrew version is 0.90. Syntactic Skills The Test of Receptive Oral Grammar (TROG; Bishop, 1989), adapted to Hebrew from English is a receptive task of syntactic skills. Children listen to progressively longer and increasingly more complex sentences, presented one at a time, and for each item are asked to point to one of four pictures that matches the sentence. Foils include syntactic and semantic distracters. There are 4 items testing each of 20 syntactic categories such as negatives (e.g., ‘‘the boy is not running’’); passives (e.g., ‘‘the elephant is pushed by the child’’); x but not y (e.g., ‘‘The box but not the chair is red’’); and complex sentences (e.g., ‘‘The circle in which there is a star is 2

The authors of this test do not report on reliability.

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red’’). Unless all the items within a category are correct, the whole category is discounted. Each correct category receives a score of 1, and test scores can range from 0 to 20. The Cronbach alpha for this test is 0.70. 5.3.3.4 Hebrew Reading and Spelling Word Reading Word reading was assessed with a subtest of the standardized Alef Ad Taf test (Shany et al., 2006). This subtest focuses on children’s ability to read 38 isolated words, representing various morphological structures, and arranged according to length and frequency. Measures of rate (WPM) and accuracy (% of errors) are calculated. Alpha-Cronbach is 0.90 in Grade 2, 0.85 in Grade 4, and 0.75 in Grade 6. Alpha-Cronbach and test norms are unavailable for Grade 1. Spelling This test was developed specifically for the present research and has no national norms. In this task the child has to write 48 dictated words. Each word is presented orally in isolation, in context (within a sentence) and again in isolation. The testers are instructed not to stress homophones (such as the phoneme / X/ in the word ‘‘xalav’’ (translation: milk). The overall Alpha-Cronbach is 0.87. Listening Comprehension This test, developed by Shatil (2002), requires participants to listen to a recorded story about a little boy and his dog. After having heard the story the child hears a series 12 statements related to the story, each presented twice, and has to respond ‘‘correct’’ or ‘‘incorrect’’ to each item. Test-retest reliability is 0.72. Reading Comprehension In this experimental task, six texts were developed altogether, 2 for each grade level (2, 4, and 6).3 For each grade level one text describes how to prepare a popular Ethiopian dish (Injara) and the other describes how to prepare a Middle Eastern dish (Cousous). While the content of the texts is identical across grade levels, the texts become more complex from grade to grade in terms of range of vocabulary and syntactic complexity. Ten questions that address four levels of comprehension follow each text. The items assess vocabulary, main idea in each paragraph, main idea and application of the knowledge and syntactic structures. Two experts (linguists) rated the texts and confirmed the increasing level of linguistic complexity of the stories. The Cronbach alpha was low in Grade 2 (0.42,) but acceptable 0.67, and 0.63, for Grades 4, and 6, respectively. 3

In Israel reading comprehension is not evaluated in Grade 1, and listening comprehension is evaluated instead.

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5.3.4 Procedures Data collection took place towards the end of the school year, between April and June. Tasks were administered individually, by trained graduate students of education. In Grades 1 and 2 the tasks were administered over two sessions, lasting 75 min each. A 1-week interval separated the two sessions. In Grades 4 and 6 the tasks were administered in one, 2-h, session. The cognitive measures were administered first, followed by the language and literacy measures.

5.4 Results 5.4.1 Do Cognitive, Cultural, Language, and Literacy Skills Correlate with SES? Even though all the participating schools were ranked as low SES, as discussed above, there were significant differences between the Ethiopian and NonEthiopian samples on various demographic variables. Ethiopian children are rarely exposed to Hebrew at home. Instead, they are exposed to Amharic or a mixture of Hebrew and Amharic, and only about a third of their parents are reported to be literate in Hebrew. In addition, Ethiopian Israeli parents who are employed are more likely to hold less skilled jobs, and housing density is higher in Ethiopian families than in non-Ethiopian. We first examined whether differences between poverty and ‘‘extreme’’ poverty might be related in a systematic manner to various cognitive, language and literacy skills. Correlations indicated that housing density and parental occupation rank correlated significantly with group (r ¼ 0.49, p < 0.01) and with each other (r ¼ 0.31, p < 0.01), indicating that in the Ethiopian group more people live in each household than in the Non-Ethiopian group. These correlations suggest that, in contrast with the Non-Ethiopian group, Ethiopian parents were more likely to be unemployed or to be unskilled laborers than skilled workers. Finally, with two exceptions (Faces and Places, and Phonemic Awareness), neither household density nor parental occupation correlated with any of the child-level measures. The correlation of occupation rank with Phonemic Awareness and Faces and Places was low butt significant (r ¼ 0.13, p < 0.05, and r ¼ 0.12, p < 0.05, respectively). That is, in both groups a relatively higher occupation rank was associated with somewhat better performance on these two child-level measures. In other words, in this study, ethnicity, poverty indicators, and cultural differences appear to form one complex cluster, but the variance on the available poverty and low SES indicators did not correlate in a systematic and direct manner with the bulk of child level cognitive, language, and literacy measures. A multiple analysis of variance (MANOVA) was run on the cognitive and language measures. Another MANOVA was run with the literacy measures. In these analyses, the effects of grade and group and the interaction of grade by group were examined. Where a significant interaction was found, a Bonferroni

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post-hoc test was applied to clarify the nature of the interaction. Tables 5.3, 5.4, and 5.5 present, by grade and group, summary statistics and the MANOVA results for cognitive skills, cultural literacy and language skills, and literacy measures in the Ethiopian and Non-Ethiopian groups. For comparison purposes, depending on availability, the equivalent to group means are presented also in terms of performance rank, percentile scores, percentile ranges, or standard score equivalents. The overall MANOVA results on the cognitive and language measures indicated significant effect of grade (F3,325 ¼ 16.02, Z2 ¼ 0.26, p < 0.001), group (F3,325 ¼ 5.55, Z2 ¼ 0.15, p < 0.001), and a significant interaction of grade and group (F3,325 ¼ 1.51, Z2 ¼ 0.05, p < 0.05).

5.4.1.1 Non-verbal Ability As can be seen in Table 5.2, there was a significant grade and group effect on the Raven’s matrices test. Within each group there was significant improvement across grades, and the Ethiopian group means were significantly lower than the means for the Non-Ethiopian groups at each grade level. The interaction of grade by group was not significant. A comparison of these statistics with the equivalent percentile scores published in the Raven’s Matrices manual indicates that, in comparison to the norming population, the mean percentile scores in both Ethiopian and Non-Ethiopian groups in Grades 1 and 2 are within the average range, but they decrease considerably in both groups in Grades 4 and 6.

5.4.1.2 Speed of Lexical Access – (RAN) As can be seen in Table 5.2 on RAN-Objects there was a significant grade and group effect. In both groups there was a significant improvement from grade to grade, and at each grade level the Ethiopian group was significantly slower in naming objects than the Non-Ethiopian group. As noted in Table 5.2, in comparison to the published norms (Shany et al., 2006), the mean equivalent in Grades 2 and 4 are in the Low to Low Average percentile ranges, but by Grade 6 the mean equivalent percentile score is in the Average range in the case of the Ethiopian group, and in the High Average range in the Non-Ethiopian group. In other words, the gaps decrease in relation to the norming population. A different pattern was noted with regard to RAN-Digits and RAN-Letters. There was a significant grade and a significant group effect. In both groups there was a significant improvement in naming speed from grade to grade. There was also a significant interaction of grade by group for each measure, indicating that the gap between the Ethiopian and Non-Ethiopian groups decreased gradually. In particular, on RAN-Digits the group effect was significant in Grades 1 and 2, but was no longer significant in Grades 4 and 6. The gap between the naming time on RAN-Digits in the Ethiopian and Non-Ethiopian groups decreased gradually from a significant gap of 9.87 seconds in Grade 1,

48.90 (10.66) NA

9.58 (6.81) (n ¼ 38) NA

Performance Rank RAN–L (sec.) 60.66 (20.51) Percentile Range NA

Performance Rank Working Memoryb 8.22 (0–45)a (5.52) (n ¼ 55) Percentiles Range NA

Average

Low av. 9.66 (4.78) (n ¼ 29) 35.1–65

Very Low 49.90 (16.14) 25.1–35

Low 40.84 (11.10) 7.1–16

20.62 (5.01) 44 61.19 (11.23) 16.1–25

Grade 2 Eth (n ¼ 42)

High

Low 14.71 (7.39) (n ¼ 21) 80.1–90

Low 42.50 (8.70) 16.1–25

Average 32.88 (6.25) 16.1–25

21.85 (4.11) 50 54.94 (11.21) 35.1–65

NEth (n ¼ 34)

High av.

Very Low 15.85 (6.30) (n ¼ 26) 65.1–80

Low 35.51 (8.48) 7.1–16

Low av. 28.79 (7.50) 16.1–25

24.46 (4.94) 22 49.46 (10.77) 25.1–35


High av.

Low 17.06 (8.25) (n ¼ 35) 65.1–80

Low av. 34.00 (5.88) 16.1–25

Average 28.11 (5.09) 25.1–35

26.08 (5.01) 30 46.25 (7.18) 35.1–65

NEth (n ¼ 36)

High av.

Average 18.87 (9.04) (n ¼ 15) 65.1–80

Average 28.75 (5.56) 35.1–65

Average 24.44 (5.27) 35.1–65

26.03 (4.82) 13 42.22 (10.96) 35.1–65


High

Average 20.67 (7.33) (n ¼ 9) 80.1–90

High av. 27.38 (5.76) 35.1–65

High av. 21.97 (5.62) 65.1–80

29.12 (4.72) 22 37.41 (7.47) 65.1–80

NEth (n ¼ 39)

24.08***

78.85*** Z2 ¼ 0.43

93.37*** Z2 ¼ 0.47

73.66*** Z2 ¼ 0.41

60.26*** Z2 ¼ 0.36

Grade effect F(3, 323)

Range of scores; A separate ANOVA due to missing data on this measure – F(3, 228); *** p < 0.001; ** p < 0.01; * p < 0.05

Performance Rank

a

b

40.45 (8.61) NA

Performance Rank RAN–D (sec.) 50.32 (15.05) Percentiles Range NA

Percentiles Range

Percentiles RAN–O (sec.)

19.67 (4.89) 67 58.74 (13.07) NA

NEth (n ¼ 42)

17.34 (4.64) 37 68.41 (13.99) NA

Raven’s (0–36)a

Tasks


5.28*

16.00*** Z2 ¼ 0.05

25.31*** Z2 ¼ 0.07

22.62*** Z2 ¼ 0.07

14.85*** Z2 ¼ 0.05

Group effect F(1, 325)

0.96

3.58* Z2 ¼ 0.03

4.57** Z2 ¼ 0.04

1.31

0.550

Grade group F(3, 322)

Table 5.2 Performance of Ethiopian and non-Ethiopian children in grades 1, 2, 4, and 6 on cognitive components: Descriptive statistics and MANOVA results

94 M. Shany and E. Geva

5


95

to a non-significant difference of 0.98 and 2/47 seconds in Grades 4 and 6, respectively. As for a comparison to the norms published by Shany et al. (2006) one notes in Table 5.2 that whereas the mean equivalent scores were in the Very Low to Low percentile ranges in Grades 2 and 4, by Grade 6, the equivalent percentile scores were in the Average to High Average ranges. Likewise, on RAN-Letters the mean gap between Ethiopian and NonEthiopian groups decreased from a significant difference in favor of the NonEthiopian group in Grades 1 and 2 to a non-significant difference in Grades 4 and 6. Relatedly, with regard to the published norms (Shany et al., 2006), whereas the mean equivalent scores were in the Very Low to Low percentile ranges in Grades 2 and 4, by Grade 6, the equivalent scores were in the Average percentile ranges.

5.4.1.3 Working Memory On Working Memory there was a significant grade and group effect, and the interaction of group by grade was not significant. Performance improved significantly from grade to grade, and at each grade level the Ethiopian group was consistently lower than the Non-Ethiopian group. In comparison to the published norms (Shany et al., 2006), the performance of the Ethiopian and NonEthiopian groups is not lower than in the norming population, and the equivalents of the mean percentages vary from Average to High.

5.4.1.4 Cultural Literacy As can be seen in Table 5.3, there was a significant grade and group effect on this measure. Mean scores increased significantly from grade to grade, and the Ethiopian group performed consistently below the Non-Ethiopian group at each grade level. The means on the K-ABC for the Ethiopian group were 1 standard deviation below the normed mean at each grade level, whereas in the Non-Ethiopian group the standard score equivalents at each grade level were 0.5 standard deviations below the normed mean.

5.4.2 The Development of Language Skills 5.4.2.1 Phoneme Discrimination On Phone Discrimination there was a significant grade effect. Students in both groups improved significantly their performance from grade to grade. Neither the effect of group nor the interaction of grade by group were significant. In comparison with a large study (Lachman& Shalem, 1998) it appears that the two groups performed within developmental norms.

a

52.36 (7.42) 65

14.21 (3.75) 38

12.83 (3.69) 25

10.12 (3.95)

11.80 (2.22) (n ¼ 41)

8.28 (2.68) 92

49.77 (8.52) 63

10.24 (4.22)

11.88 (1.94) (n ¼ 57)

6.98 (2.98) 88

NEth (n ¼ 42)

13.79 (3.63) 25

Average 52.26 (11.45) 51

9.72 (3.71) 35.1–65

12.56 (2.07) (n ¼ 41)

8.44 (3.39) 85


14.24 (1.97) 38

Average 52.44 (12.61) 51

8.60 (3.12) 35.1–65

12.73 (1.84) (n ¼ 33)

9.73 (3.26) 92

NEth (n ¼ 34) 13.72 (3.02) 93

NEth (n ¼ 36)

13.58 (1.38) (n ¼ 36)

15.14 (3.79) 86


13.51 (1.25) (n ¼ 39)

18.05 (4.44) 93

NEth (n ¼ 39)

15.97 (1.94) 25

Low-av. 59.69 (11.52) 45 17.00 (1.59) 38

Low-av. 63.78 (10.26) 50 17.22 (1.91) 25

Average 66.61 (10.38) 45

17.28 (3.16) 25

Average 78.79 (11.78) 58

Scores are equivalent to percentile 30-40 7.02 6.25 4.62 4.30 (4.10) (4.26) (4.14) (3.68) 16.1–25 25.1–35 35.1–65 35.1–65

Language Skills 12.72 13.50 (2.11) (1.08) (n ¼ 39) (n ¼ 36)

11.44 (3.44) 84


Range of scores; b A separate ANOVA due to missing data on this measure; *** p < 0.001; ** p < 0.01; * p < 0.05

Performance Rank Vocabulary: PPVT (0–110)a Standard Scores Equivalent Grammatical skills TROG (0–20)a Percentile

Percentile Phonemic Awareness No. Errors (0–16)a Percentiles Range

Phoneme Discriminationb No. correct (0–15)a

Cultural Literacy Faces and Places: KAB-C (0–33)a Standard Scores Equivalent

Tasks


31.51*** Z2 ¼ 0.23

73.34*** Z2 ¼ 0.41

34.98*** Z2 ¼ 0.25

13.94*** Z2 ¼ 0.12

113.41*** Z2 ¼ 0.52

Grade effect F(3, 323)

4.89* Z2 ¼ 0.02

16.46*** Z2 ¼ 0.05

1.75

0.975

26.23*** Z2 ¼ 0.08


0.84

4.72** Z2 ¼ 0.05

0.26

0.970

1.09

Grade group F(3, 322)

Table 5.3 Performance of Ethiopian and non-Ethiopian children in grades 1, 2, 4, and 6 on cultural and language components: Descriptive statistics and MANOVA results


5


97

5.4.2.2 Phonemic Awareness There was a significant grade effect on this task. Performance improved significantly between Grade 2 and Grade 4, and between Grade 4 and Grade 6, in both groups. The group and interaction effects were not significant. The equivalents of the means in the Ethiopian group are in the Average range in Grade 2, in the Low-Average range in Grade 4, and again in the Average range in Grade 6. The equivalents of the means in the Non-Ethiopian group are identical to those noted in the Ethiopian samples (Shany et al., 2006) (Comparison statistics are unavailable for Grade 1). 5.4.2.3 Vocabulary As can be seen in Table 5.3, there was a significant grade effect on the vocabulary test. Post-hoc tests indicated that there was no significant difference between Grades 1 and 2, but the increase from Grade 2 to Grade 4 and from Grade 4 to Grade 6 was significant. There was also group effect, and a significant grade by group effect. The mean in the Ethiopian group was significantly lower than in the Non-Ethiopian group only in Grade 6. Notably, in relation to the norming population, the mean equivalent vocabulary standard scores decrease over time in both groups. 5.4.2.4 Grammatical Skills As can be seen in Table 5.3, there was a significant grade effect. Growth from Grade 2 to 4 was statistically significant, but the mean differences in the number of blocks mastered in Grades 1 vs. 2 and in Grades 4 vs. 6 were not statistically different from each other within each group. At each grade level the mean in the Ethiopian group was statistically lower than in the Non-Ethiopian group. The equivalent blocks in the norming population are 15, 16, 18, and 18 in Grades 1, 2, 3, and 6, respectively. That is, performance in both groups is below the comparable published norms for these age groups, and in fact, relative to the population, level of performance is constant in the Ethiopian group, and decreases in the Non-Ethiopian group.

5.4.3 The Development of Reading and Writing Skills 5.4.3.1 Word Reading Accuracy As can be seen in Table 5.4, there was a significant grade effect, but the group and interaction of grade by group effects were not significant. There was a significant increase in accuracy between Grades 1 and 2 and between Grades 2 and 4, but the increase between Grades 4 and 6 was not statistically significant. The equivalent word reading accuracy mean scores (50th percentile) reported by Shany et al. (2006) for the norming population are M ¼ 22.32 (SD ¼ 18.10),

a

20.25 (12.28) NA NA 33.99 (22.86) No norms No norms 27.92 (11.06) 10.62 (1.40)

F ¼ 1.50; (1, 93), p ¼ 0.223

16.93 (8.48) NA NA 43.26 (27.39) No norms No norms 20.52 (3.30) 10.18 (1.90)

NEth (n ¼ 42)

Range of scores; *** p < 0.001; * p < 0.05

Words –WPM (38 words) Percentiles Range Performance Rank Words – Accuracy % Errors Percentiles Range Performance Rank Spelling (0–48)# correcta Discourse/ Reading Comprehensiona

Tasks

Grade 1 Eth (n ¼ 58) 36.27 (20.03) 65.1–80 High-average 34.44 (24.09) 16.1–25 low 37.25 (8.59) 7.14 (3.62)

NEth (n ¼ 34) 48.88 (24.21) 35.1–65 Average 25.44 (21.09) 7.1–16 Very-Low 40.78 (8.52) 17.41 (6.37)

Grade 4 Eth (n ¼ 39) 43.33 (15.55) 25.1–35 Low-average 19.66 (13.17) 16.1–25 low 42.81 (5.08) 19.48 (6.16)

NEth (n ¼ 36)

F ¼ 0.565; (1, 63), p < 0.555 F ¼ 1.89; (1, 69), p < 0.174

26.07 (15.21) 25.1–35 Low-average 32.78 (23.31) 25.1–35 Low-average 32.06 (12.10) 6.93 (3.70)

Grade 2 Eth (n ¼ 42) 67.91 (22.00) 35.1–65 Average 14.04 (13.54) 16.1–25 low 44.69 (5.74) 19.53 (4.02) F ¼ 7.16; (1, 74), p < 0.009

60.71 (17.12) 35.1–65 Average 16.45 (12.46) 16.1–25 low 45.33 (5.27) 17.14 (3.63)

3.01* Z2 ¼ 0.03

1.04

2.81* Z2 ¼ 0.03

2.78

10.48*** Z2 ¼ 0.03

20.86*** Z2 ¼ 0.16

79.89*** Z2 ¼ 0.43

Grade group F(3, 322) 3.94* Z2 ¼ 0.01


111.15*** Z2 ¼ 0.51

Grade 6 Eth NEth Grade effect (n ¼ 36) (n ¼ 39) F(3, 323)

Table 5.4 Performance of Ethiopian children and non-Ethiopian children in grades 1, 2, 4, and 6 on word level reading components: Descriptive statistics and MANOVA results


5


99

M ¼ 14.14 (SD ¼ 12.94), and M ¼ 10.02 (SD ¼ 8.93) for Grades 2, 4 and 6, respectively. (Comparison statistics are not available for Grade 1). As can be seen in Table 5.3, both groups perform consistently in the low range at each grade level. 5.4.3.2 Word Reading Rate As can be seen in Table 5.4, there was a significant grade effect, a significant group effect, and a significant interaction of grade by group. Increase in word reading rate was significant from grade to grade in both groups. In addition, the group difference in word reading rate was significant only in Grade 2. (Comparison statistics are not available for Grade 1). In comparison to the norming population, performance in both the Ethiopian and Non-Ethiopian groups at each grade level was in the average range. 5.4.3.3 Spelling As noted in Table 5.4, there was a significant grade effect, a significant group effect, and a significant grade by group effect. The increase from Grade 1 to 2 and from Grade 2 to 4 was significant, but Grades 4 and 6 were not statistically different from each other. The Ethiopian group was lower than the NonEthiopian group in Grades 1 and 2, but not in Grades 4 and 6. 5.4.3.4 Discourse Comprehension Listening Comprehension Data for this task are available only for Grade 1. A one-way ANOVA indicated that the groups did not differ from each other. The group means are equivalent to the 75th percentile, as reported by Shatil (2002) in a large representative sample (n ¼ 349). Reading Comprehension There is no standardized reading comprehension test in Hebrew. As noted above, the content of the tests remained constant across grade levels, but the texts administered in Grades 2, 4, and 6 varied as a function of length, vocabulary, and language complexity. One-way ANOVAs, with group as the independent variables (summarized in Table 5.4), revealed that in Grades 2 and 4 the groups did not differ from each other, but by Grade 6, the Non-Ethiopian group outperformed the Ethiopian group. Table 5.5 summarizes the general trends that emerged in the results shown in Table 5.4. The columns on the left summarize the group comparisons and the columns on the right summarize comparisons with various norming populations. These trends are addressed in the Discussion section below.

Cognitive skills Raven’s RAN–Oa RAN–D RAN– L Working Memoryb Cultural literacy Faces and Places: KAB-C Language skills Phoneme Discrimination Phonemic Awareness Vocabulary: PPVT Grammatical skills

Domains

yes

yes

yes

yes

yes

yes

no

yes

no

yes

yes yes Yes yes no

no

yes

yes

ys yes Yes yes no

no

yes

yes yes

yes yes yes yes yes

yes yes

yes

yes

no

no

yes yes yes

yes yes yes

yes

yes

yes

yes

yes

yes

yes

yes

Table 5.5 Summary of results: Gap patterns from early grades (1 and 2) to higher grades (4 and 6) Comparison between the research groups Comparison of research groups with national norms Do the gaps Do the gaps Do the gaps decrease/ increase in persist in disappear in Are there higher higher higher gaps in early grades? grades? grades? grades? Do the gaps Do the Do the gaps Are there gaps persist increase in decrease/ gaps in higher in higher disappear in early grades? Eth. NEth. Eth. NEth. Eth. NEth. Eth. NEth. grades? higher grades? grades?


b

a

yes

yes

yes no

Do the gaps decrease/ disappear in higher grades?

In Gr. 2 no

Are there gaps in early grades?

In Gr. 6

no yes

No norms No norms

no yes

yes

yes

Even though there was a difference between the groups, both performed in the average range in comparison to the norming population The same comment

Cognitive skills Words –WPM Words – Accuracy Spelling Discourse/ Reading Comp.

Domains

Table 5.5 (continued) Comparison of research groups with national norms Do the gaps Do the gaps Do the gaps decrease/ increase in persist in Are there disappear in higher higher gaps in early higher grades? grades? grades? grades? Do the gaps Do the gaps persist increase in higher in higher grades? Eth. NEth. Eth. NEth. Eth. NEth. Eth. NEth. grades?

Comparison between the research groups

5 Cognitive, Language, and Literacy Development in Socio-culturally Vulnerable . . . 101

102


5.5 Discussion To date, most of the official and non-official available reports on Ethiopian Israeli children that focused on academic achievement focused on older learners. These reports consistently highlighted gaps between the performance of these students and other immigrant groups and the general population. The present research examined in depth various component processes that underlie academic achievement of Ethiopian children and compared their performance to that of their Non-Ethiopian peers, who live in the same poor communities, attend the same classes, and are exposed to the same national curriculum. One general observation that emerges from the current study is that the Ethiopian children are not consistently low on all aspects of cognitive, language and literacy skills; on some components they are not different from their counterparts, and on some they begin with very low skills but they close the gaps over time. Importantly, in spite of linguistic, economic, and cultural differences, on certain components children of Ethiopian families are inherently similar to the general population. At the same time, on certain components of language and literacy the gaps increase over time. In what follows we discuss these various trends. The two levels of comparison shown in Table 5.5 are highly informative: the Ethiopian and non-Ethiopian groups, coming from a number of towns and schools in Israel, all lived in depressed neighborhoods, and in each case the Ethiopian and non-Ethiopian students received identical instruction. The comparison between Ethiopian and non-Ethiopian students therefore underscores the cultural differences that exert their effect over and above the influence of what happens, at least formally, at school. The comparison with the general norms, on the other hand, underscores the effects of living in poor neighborhoods in relation to general population trends.

5.5.1 No Gaps Between the Ethiopian and Non-Ethiopian Groups Beginning in Grade 1, the Ethiopian and Non-Ethiopian groups did not differ from each other on phoneme discrimination and on phonemic awareness. In addition, overall, both groups were not different from each other or from the general population on these skills. In this regard, it is interesting to note that in a study that compared Ethiopian and Non-Ethiopian children in kindergarten (based on the same sample), Shany et al. (2010) found differences between the groups on phoneme awareness and phoneme discrimination. In other words, with the onset of formal education and learning to read Hebrew, the differences between the Ethiopian and Non-Ethiopian children on these basic processing skills gradually disappeared. As noted in Table 5.5, even though their performance in Grade 4 is better than in Grade 2, the rate of improvement of phoneme awareness in the Ethiopian group is not as steep as in the general population.

5

Cognitive, Language, and Literacy Development in Socio-culturally Vulnerable . . . 103

On word reading accuracy there were no differences between the groups across grades. However, in comparison with the norming sample, both groups performed consistently in the low range. This finding is in line with numerous other studies involving L2 students that have shown that with the onset of formal education, there are no differences between L1 and ESL learners on phonemic awareness and word level reading skills. At the same time, these observations suggest that regardless of home language, the performance of children who come from low SES backgrounds may lag behind the general population (Oller & Eilers, 2002; Willms, 2003). In line with the general literature concerning the development of word-level skills in ESL learners, this lag may be attributed therefore less to home language than to insufficient exposure to extended reading and rich language and literacy contexts, as reflected in the low familiarity of children in both groups with popular children’s books (Faces and Places). On another basic underlying cognitive measure, working memory, while there was a difference between the two groups, in fact, both performed within the average range in relation to the norming population. It appears that on basic underlying cognitive measures that are less susceptible to cultural, linguistic, or educational influences, the Ethiopian group was not inherently different from the general population (nor was the comparison group of Non-Ethiopian children).

5.5.2 Closing Gaps Between the Ethiopian and Non-Ethiopian Groups On certain measures gaps existed between the Ethiopian and Non-Ethiopian students in the early school years (Grades 1 and 2), but disappeared by Grade 4. This trend was noted with regard to alphanumeric naming speed (letter and digits), word reading rate, and spelling. Moreover, when the gaps close between the Ethiopian and Non-Ethiopian groups on these basic processing components, both groups become similar to the norming population. The reduction over time of gaps between language minority children and their L1 counterparts on tests of speed of lexical retrieval of basic units such as digits and letters is well documented in the literature (Gholamain & Geva, 1999; Lesaux & Siegel, 2003; Geva & Yaghoub-Zadeh, 2006). The interesting question we need to explain is why in this study the gap in object naming persists, even though it disappears on the alphanumeric naming tasks. A possible explanation comes from the developmental literature on naming tasks. For example, cognitive researchers have shown that object naming is slower than letter and digit naming, and have explained that object naming is semantically more complex, and involves higher level retrieval processes than letter or digit naming, probably because it involves an open and less rehearsed class (Wolf & Goodglass, 1986; Southwood & Chatterjee, 1999, 2000). In this respect it is useful to consider the results in the Ehtiopian and Non-Ethiopian groups in

104


comparison to the norming data. Up to Grade 4, both the Ehtiopian and NonEthiopian groups are slower in alphanumeric naming tasks than the norming population, and one would argue that this might be a consequence of their low SES (Lucchese & Tamis-LeMonda, 2007). However, on object naming, up to Grade 4 only the Ethiopian children are slower in comparison to the norms. It is possible that this pattern reflects generally less developed semantic networks. According to the literature (Hedden, Lautenschlager, & Park, 2005; Salthouse, 1993), the object naming speed task is related to language proficiency, specifically, to vocabulary size, an-area on which Ethiopian children are lower in comparison to Non-Ethiopians. Even though in Grade 6 Ethiopian children performed on the object naming task within the average range, a significant gap in comparison to the Non-Ethiopian group was still apparent. In other words, as in the general literature, it is possible that the pattern noted on rapid object naming is related more generally to language development. However, as they move to higher grades, the Ethiopian Israeli children are not slower, relative to their counterparts, on rapid naming of simple alphanumeric items such as letters and digits that have been shown to be related to decoding skills (Sunseth & Bowers, 2002). These tasks are not related to vocabulary knowledge in L2 learners either (Geva, 2006). In line with this literature, the performance of the Ethiopian group on the alphanumeric tasks is not problematic in either of the groups targeted in this study. The results regarding spelling show that the Grade 1 gaps between the Ethiopian and Non-Ethiopian groups disappear by Grade 2. Similarly, other research has shown that the spelling gaps between monolingual and ESL learners coming from somewhat economically less challenged neighborhoods either close over time (Fashola, Drum, Mayer, & Kang, 1996; Wang & Geva, 2003) or are non-existent (Geva & Lafrance, 2011). These results are in line with the general argument that decoding and spelling skills are less susceptible to the influences of language proficiency, and that once the basic tools of spelling have been acquired, the L2 or minority learners do not necessarily lag in terms of their spelling skills (Geva & Lafrance, 2011; Wade-Woolley & Siegel, 1997).

5.5.3 Persistent Gaps Between the Ethiopian and Non-Ethiopian Groups Gaps persisted between the groups across grades on non-verbal ability, cultural knowledge, and grammatical skills. Even though the Ethiopian and NonEthiopian groups alike can be considered as low SES, the gap between them on non-verbal ability persists. Moreover, the gap between both groups and the national norms also increases systematically across grades. Even though the Raven’s test used in this study to evaluate non-verbal ability is considered to be a relatively culture-free task, we concur with Kozulin (1999) and Tzuriel and Kaufman (1994) who maintain that poor performance on such a task does reflect cultural differences, lack of exposure, and lack of opportunities to

5


develop the underlying problem solving skills needed to do well on this task. Indeed, there is scientific evidence (e.g., Kozulin, 1999; Tzuriel & Kaufman, 1994) that it is possible to improve the performance of Ethiopian children on the Raven’s Matrices with intensive and targeted intervention. We would argue that at least in regard to the Ethiopian sample, the Raven’s Matrices should be seen as reflecting to some extent cultural knowledge and experience, rather than intellectual, problem-solving ability. King et al. (2003) report that 60% of Ethiopian homes do not have any toys or books, and in another 20–25% of the families, up to 5 toys and 10 books were found on average. Ethiopian children have very few opportunities to play with puzzles, and there is often a dearth of toys in their homes. This supports the conjecture that at least to some extent their poor performance on the non-verbal task reflects lack of exposure and opportunities to develop relevant skills involving the manipulation of visual arrays that are not necessarily representational. In a similar vein, the gap between the Ethiopian and Non-Ethiopian groups persisted on Faces and Places, a task that also captures cultural knowledge and exposure. Another area in which the differences between the groups persist involved grammatical skills. Our results indicated that the relative position in relation to the population norms is constant in the Ethiopian group (25th percentile), and that it decreases in the Non-Ethiopian group (from the 35th to the 25th percentile). The low performance of both groups on this aspect of oral language proficiency is again likely related to their low socio-economic status (SES), and more specifically to insufficient exposure to rich language in oral and written contexts. Ample studies have shown that low SES is associated with fewer language-promoting experiences during the preschool years, and the latter, in turn, are related to lower receptive language abilities (Arriaga, Fenson, Cronan, & Pethick, 1998; Hart & Risley, 1995; Walker, Greenwood, Hart, & Carta, 1994). From a deficit perspective, some might attribute this persistent gap between the Ethiopian children and the Non-Ethiopians to low parental command of Hebrew. However, research on bilingual children has shown that children exposed simultaneously to two languages may, in fact, have cognitive advantages thanks to the fact that they are exposed to two linguistic systems (Bialystok, 2001). Children can actually develop high levels of competence when they are exposed to the L1 and L2 in formal educational contexts (Genoz & Genessee, 1998) that consider bilingualism as additive and not as subtractive (Cummins, 1989). The key here is the extent to which the L2 and L1 are valued, and fostered within rich language and literacy contexts in both languages (Schwartz, Leikin, & Share, 2005). In studies conducted within additive contexts, Bialystok and Feng (2011) did not find evidence for bilingual deficits on various cognitive tasks, even though consistently the bilinguals had lower vocabulary scores than their monolingual counterparts. Clearly, early language development is rooted in the interactions children have with their parents and other care takers, and these interactions both foster developing language skills and provide a vital foundation for children’s academic performance (Lucchese & Tamis-LeMonda, 2007). What may matter is not merely the

106


fact that the parents either do not speak Hebrew (the societal language) or do not speak it well, but that the parents have very low written language literacy skills in either language, and that the range and quality of language used at home, whether in Hebrew or Amharic, does not prepare the children for the language and concepts that are needed to excel in Israeli schools. It is important also to acknowledge that the school curriculum does not address adequately and early enough these differences and needs and that it treats children’s exposure to the home language within a subtractive framework which discourages the development of skills in both the societal and the home language.

5.5.4 Gaps Between the Ethiopian and Non-Ethiopian Groups That Increase An alarming finding is the observation that in the case of vocabulary and reading comprehension the gaps between Ethiopian and Non-Ethiopian Israeli children increased by Grade 6.4 In addition, and as reflected in the standard scores equivalents of the vocabulary test, across grades, the vocabulary size of both groups is below population norms. As many researchers have noted, semantic knowledge develops through exposure to both oral and written language, and ample research indicates the serious risk that factors such as poverty and low parental education pose to children’s early language development (Hoff, 2003; Walker et al., 1994). The findings indicate however, that from the onset children in the Ethiopian group achieve even worse than the comparison group. In other words, the results suggest that while some improvement takes place in the Non-Ethiopian group, in the Ethiopian group there may not be much improvement. The significant interaction between groups and grades on vocabulary deserves attention by policy makers and educators. Why does the gap between the Ethiopian Israeli children and their counterparts increase significantly by Grade 6? It might be suggested that this increase is associated with restricted and low quality of interactions in the Hebrew language which children from the Ethiopian community experience with their parents, their peers, and their teachers. Moreover, from the ‘‘cultural capital’’ perspective (Bourdieu & Passeron, 1990), it seems that disadvantages are maintained from one generation to the next. In that respect, the low linguistic performance of the Ethiopian children on both vocabulary (and grammatical skills), might reflect the failure of schools to adapt instruction to the needs of this population (Rueda et al., 2006). Citing the National Reading Panel (2000) Biemiller (2006) wrote that ‘‘Current reading instruction is apparently premised on the view that children 4

We checked to see whether the increase in the gaps in Grade 6 relates to sampling issues – however, in Grade 6 the gap between Ethiopian and Non-Ethiopian samples on the Raven’s does not increase, and on some indices, such as phonological discrimination, the gap disappears.

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can build the vocabulary they need after learning to read (decode) fluently, as little or no vocabulary instruction occurs during the primary grades’’ (p. 44). Indeed, according to Israel Ministry of Education supervisors (personal communication, December 26, 2007), language enrichment programs are more likely to be implemented in the early years, following immigration and less likely to occur in higher grades. Vocabulary is a powerful predictor of reading comprehension (Biemiller, 2006), and a direct link seems to exists between an increase in the gap between the groups on vocabulary and on reading comprehension. Chall and colleagues (Chall, Jacobs, & Baldwin, 1990) have shown that in the lower grades the focus of instruction is on learning to read, and that regardless of SES (monolingual) children are less likely to be challenged by unfamiliar vocabulary and therefore the gap in language and reading skills in the lower grades is not as striking. However, many children coming from low SES families experience a ‘‘slump’’ in reading comprehension in grade 4, caused by below-grade vocabulary levels, and, while word recognition appears to be a major hurdle in the primary grades, word meaning becomes a major hurdle in Grade 4 and above (Chall, 1987). Studies focusing on minority students learning to read in the societal language demonstrate likewise that the reading comprehension of minority students falls well below that of their native-speaking peers (for a systematic review, see Lesaux & Geva, 2006). L2 students who have better developed L2 oral language comprehension skills are better able to comprehend texts (e.g., August, Carlo, Dressler, & Snow, 2005; Royer & Carlo, 1991). Of relevance here is the study of Proctor et al. (2005) who tested a structural equation model of second language (English as L2) reading comprehension and found that over and above adequate L2 decoding ability, L2 vocabulary knowledge is crucial for improved English reading comprehension outcomes for children of Spanish-speaking immigrants.

5.5.5 Language and Literacy Skills Among Children of Ethiopian Immigrants – What Develops? Overall, the results presented in this chapter indicate that on relatively simple language components, such as auditory discrimination and phonemic awareness, the Ethiopian and Non-Ethiopian groups perform in a similar way. On such simple language components, there is steady development from year to year and even though in the early years the group means are in the low-average by comparison to population mean, the gaps between the group means and the population mean appear to be closing sometime between Grades 4 and 6. In other words, the basic language components of children who come from low SES backgrounds emerge slowly, but with schooling and learning to read and write they master these basic components, and by the time they reach middle school these groups are not different from what one might expect in the population at large. While in and of itself this may be an encouraging trend, this slow emergence

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may have negative effects on the development of more complex and more demanding aspects of language, literacy, and academic achievement. A different picture emerges, however, with regards to more complex aspects of language skills, and in particular vocabulary and grammar. Three observations are particularly noteworthy with regard to vocabulary skills. First, the gap between the Ethiopian and Non-Ethiopian groups increases in the upper elementary years, even though the two groups are not that different from each other in the lower grades. Second, the performance of both groups is considerably below the national norms at each grade level, with a gap of at least 3 standard deviations. Third, the vocabulary skills of the Ethiopian group slide further away in relation to national norms. It may be argued that comparing the performance of the Ethiopian group to the national norms is inappropriate due to their different home language background. This may be a legitimate argument but it is less relevant in this context, as this study shows that regardless of home language, the vocabulary skills of school children who live in very poor neighborhoods are extremely poor and that they do not develop at an acceptable rate. This observation has been made in other linguistic contexts (e.g., Hart & Risley, 1995). The fact that with time the Ethiopian Israeli children fall further behind is especially worrisome. Theoretically, without a special intervention program one would expect a steady rate of growth over time. That is, one would expect that the relative standing of the Ethiopian Israeli group would be maintained relative to the population or at least in relation to the Non-Ethiopian comparison group consisting of children who attend the same schools and live in the same poor neighbourhoods. The fact that the Ethiopian Israeli children fall even further behind suggests that their language skills do not develop at a steady rate. This may not be attributed merely to their second language status, as studies of vocabulary development in L2 learners (e.g., Farnia & Geva, 2011) have shown that even after 6 years of instruction in the societal language, the vocabulary skills of ESL children do not catch up with those of their first language (L1) counterparts, but that in the ESL group there is steeper growth in vocabulary learning in the early school years than in the non ESL group. However, in this project, instead of seeing an upward trajectory we see a downwards trajectory. Vocabulary knowledge is strongly related to reading comprehension in both monolingual and L2 learners, but is not as strongly implicated in word-level skills (Bialystok & Feng, 2011; Geva, 2006). This is also the case in this study of Ethiopian Israeli children. Even though these children have rather limited vocabulary knowledge, their phonological awareness, rapid naming, and word-level skills are acceptable. That is – they have the cognitive underpinnings needed to learn to read and achieve academically. As has been shown elsewhere and in this study, large language and vocabulary differences and different developmental trajectories distinguish low and middle class children even before kindergarten (Hart & Risley, 1995, 1999, 2003). These differences are probably compounded by current school practices that allow further widening of vocabulary gaps during the primary years (Biemiller & Slonim, 2001).

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In sum, the children of Ethiopian immigrants are born into a culture of poverty, profound cultural differences, and lack of fit between home practice and beliefs on the one hand and the school system on the other. Our data suggest that less complex skills develop appropriately, as perhaps these skills are less susceptible to the cumulative effects of SES, cultural and school practices.. On these skills the Ethiopian Israeli children are not different from their nonEthiopian counterparts. However, on more complex skills, these children are not thriving because, in spite of their cognitive potential, they do not have sustained instructional and environmental exposure to cultural experiences that are needed in order to become more attuned to what it takes to become good readers, good writers, and sophisticated users of the language.

5.5.6 Summary and Implications Several trends and conclusions, relevant to the education of children of other groups migrating from non-literate to ‘‘developed’’ societies, should be stressed: Children who come from low SES backgrounds, from an oral tradition, and whose parents are illiterate in their L1 have more challenges in acquiring higher level language and literacy skills than low SES children whose parents are have gained some literacy skills. When families and/or a community have different cultural capital resources, they are limited in their ability to prepare and support their children in academic domains. In addition, when parents are not literate in their first language, their children cannot draw on their home language and L1 literacy in order to develop language skills. This is especially the case when the cultural institutions of the country of origin are not sustained in the new country. With development and schooling, gaps involving language and literacy components that are cognitively less complex and modularized (e.g., rapid retrieval of visual stimulus and phonological abilities) and word-based skills such as decoding, word reading efficiency, and spelling diminish or disappear. On the other hand the gaps persist or increase on more complex cognitive components that become increasingly more strategic and multi-componential, including non-verbal problem solving skills, language components such as vocabulary and grammatical knowledge, familiarity with the cultural symbols of the new country, and reading comprehension. As to the question of when can one expect low SES groups to perform more poorly than the population mean, four trends emerge. The first two trends characterize simple language and processing components: (a) when gaps do not exist between the two low SES groups beyond Grade 2, no gaps are noted between these groups and typical performance in the norming population either; (b) when gaps between the Ethiopian and Non-Ethiopian groups decrease, the gaps with national norms either decrease or stay stable. As for more complex aspects of language and literacy skills two trends appear: (c) when the gaps between the Ethiopian and Non-Ethiopian groups increase, both groups also decrease relative to the national norms; and d) when the gaps

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between the Ethiopian and Non-Ethiopian groups are stable, both groups either decrease relative to norm or they maintain their relative position. The comparison of the mean performance in the Ethiopian and NonEthiopian groups with national norms underscores the joint effects of home and community factors associated with low SES and lack of cultural fit on various cognitive, linguistic and literacy skills.5 It is evident that low SES and cultural differences are associated with a wide array of cognitive and academic outcomes, with long term effects. These differences emerge early and are amplified in later years (Bradley & Corwyn, 2002). These trends underscore the need for the introduction of sustained national policies concerning the introduction of very early prevention programs targeting children, families and the training of educators. Countries where immigrants do well have well-established language support programs in early childhood education and primary school, with clearly defined goals, standards and evaluation systems (CERI, 2006). Countries where immigrant and minority children do not do well should develop and undertake policies such as the recent introduction of the ‘‘Early Years’’ policy in Ontario and translate these recommendations into specific policy priorities, professional training, curriculum development, and follow up research. The Ontario plan – With Our Best Future in Mind: Implementing Early Learning in Ontario (Ontario Government, June 2009) – is a totally integrated pre-natal to 12 years plan that when fully implemented, will provide a universal platform for healthy child and family development. Acknowledgements The research reported in this paper was partially supported by a grant from the Ministry of Education, Chief Scientist’s Office, Israel.

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Wolf, M., & Goodglass, H. (1986). Dyslexia, dysnomia, and lexical retrieval: A longitudinal investigation. Brain and language, 28, 154–168. Yaghoub Zadeh, Z., Farnia, F., & Geva, E. (2011). Toward modeling reading development in young English as second language learners. Reading and Writing: An Interdisciplinary Journal. doi:10.1007/s11145-010-9252-0. Yediot Axronot, January 1, 2008. Ziegler, J. C., & Goswami, U. (2005). Reading acquisition, developmental Dyslexia, and skilled reading across languages: A psycholinguistic grain size theory. Psychological Bulletin, 131, 3–29.

Chapter 6

Second Generation Immigrants: A Socio-Linguistic Approach of Linguistic Development Within the Framework of Family Language Policy Mila Schwartz

6.1 Introduction Immigrant families overcome the process of ‘‘insertion,’’ in which they must find their way into host country society, sometimes being pressured to abandon their home country language or detach themselves from their country of origin (BenRafael et al., 2006). For example, Pease-Alvarez (2003) conducted in-depth interviews with 63 parents who were first and second generation immigrants from Mexico in California. The findings point out a strong tendency of some participants to abandon the use of Spanish with their children and adopt English monolingual norms and Anglo values in an effort to improve their social status and new cultural identity, and to enjoy the benefits associated with becoming Americans. On the other hand, the insertion in a new society might be characterized by a strong tendency to integrate by combining both the maintenance of the home country language and the acquisition of the host country language, as in the case of the last wave of Russian-Jewish immigrants from the former Soviet Union (FSU) in Israel (Horenczyk & Ben-Shalom, 2006; Lissitsa, 2007). Accordingly, the focus on the case of Russian-Jewish immigrants from the FSU and their Israeli-born children might provide a unique and intriguing case study of how family language policy (FLP) and family background can enhance first language (L1; the heritage language) inter-generational transmission and second language (L2) acquisition. This paper presents an analysis of studies focusing on the process of vocabulary acquisition among second generation immigrants from the FSU in Israel. As presented in the Introduction to this volume, this immigrant community is characterized by high education levels. Approximately 60% of the FSU immigrants in the workforce have academic professions, compared with 30% M. Schwartz (*) Research and Evaluation Authority, Oranim Academic College of Education, Kiryat Tivon, Israel Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, University of Haifa, Haifa, Israel e-mail: [email protected] M. Leikin et al. (eds.), Current Issues in Bilingualism, Literacy Studies 5, DOI 10.1007/978-94-007-2327-6_6, Ó Springer ScienceþBusiness Media B.V. 2012

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of the veteran Israeli population (Leshem & Lissak, 1999). At the same time, many individuals from this wave of immigration were obliged to seek alternative blue collar employment. Thus, one of the features of this wave of immigration is the discrepancy between the relatively low-middle socioeconomic status of the community and its high education level. In general, the first generation of immigrants from the FSU in Israel is distinguished by a relatively rapid and successful acquisition of Hebrew, the majority language, compared to other waves of immigration to the country (Olshtain & Kotik, 2000; Stavans & Goldzweig, 2008). Stavans and Goldzweig (2008) found that the Russian-Jewish immigrants’ increased proficiency in L2 does not pose a threat or a need to alter their perception of their L1 community or language as the cultural capital that is complete and satisfying. Note also that the promotion of supplementary after-school educational settings designed to preserve the cultural heritage and L1 in its literate form among second generation is one of the main target of this immigrant community. In addition, it was found that for these immigrants as parents, their child’s academic success is a very important personal objective in the country of origin, as well as in Israel as the host country (Horowitz, 1986). Focusing on this community, this chapter examines what socio-cultural and socio-linguistic factors are related to vocabulary in L1 and L2 among second generation immigrants within the context of the family language policy and its background (i.e., parental education, socio-economic status, and length of parents’ residence in the host country and social milieu).

6.2 Family Language Policy and Vocabulary in L1 and L2 Research on family language policy (FLP) incorporates analysis of language ideology, practice, and management, which were classified by Spolsky (2004) as components of the language policy model with respect to the speech community. In distinguishing these three components, Spolsky (2004:5) notes ‘‘. . .language practices – the habitual pattern of selecting among the varieties that make up its linguistic repertoire; its language beliefs or ideology – the beliefs about language and language use; and any specific efforts to modify or influence that practice by any kind of language intervention, planning or management.’’ Using this model at the family level enables us to integrate the separate components within a structural, flexible, and expandable framework. Developmental psychologists suggest that parents’ beliefs motivate their practices, which in turn are strong determinants of the children’s development (De Houwer, 1999; Johnson & Martin, 1985). For example, Barkhuizen (2006) found that Afrikaans-speaking South African immigrant parents in New Zealand believed that their children’s transition to English would be smooth if they were socialized in English during the pre-immigration stage. At the same time, there is a growing evidence for full complexity and non-linearity of relationships between parental language ideology and actual language and

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practice at home. More specifically, the declared language ideology of one or both parents does not necessarily coincide with the strategies followed consciously or unconsciously in language practice with children (De Houwer, 1999; Goodz, 1994; King, 2000; Kopeliovich, 2006; Schwartz, 2008; Spolsky, 2004). For example, Eilers, Pearson, and Cobo-Lewis’s (2006) study focused on the link between the Spanish-English speaking parents’ positive attitudes to their children balanced bilingual development (i.e., language ideology) and real language practice at home. The findings showed a clear-cut inconsistency between the parents’ ‘‘firm plans’’ to provide balanced bilingual development in Spanish and English for their newborns through the first 3 years of life and these plans actual realization. Thus, only one family out of 24 was persistent in providing equal exposure to both languages during the 3 years of the study. The parents’ beliefs might be realized by means of planned or non-planned regulation (i.e., management) of L1 vocabulary development. For example, parents might control L1/L2 vocabulary development by using enjoyable tactics such as joint reading and learning illustrated rhymes and poems by heart (Gregory, Arju, Jessel, Kenner, & Ruby, 2007; Kopeliovich, 2006). This family language strategy was found to be rather fruitful for L1 pronunciation improvement and understanding of culturally unique idioms in L1 as well. Through poetry recitation in L1 the family also enhances cultural identity of the second generation children. Note also that the acquisition, development, and maintenance of L1 across generations are encouraged and stimulated by family efforts to transmit its written form (Cummins, 2000; Pearson, 2007; Seville-Troike, 2000). It appears that within the framework of FLP, child language policy has received rather minor attention (Okita, 2002). This study tried to fill this void by exploring whether parental language ideology was indeed linked to the family’s language management strategies and contributed to the children’s L1 vocabulary by collecting both the parents’ reports and children’s reports on their attitudes toward the L1 maintenance. Concerning FLP and L2 vocabulary skills among the second generation, the existing data relate mostly to patterns of language input at home. The child’s language input refers to language interaction in the family milieu (parents, grandparents, siblings) (De Houwer, 1995). Note that findings regarding the link between L2 inputs at home and children’s L2 vocabulary are not conclusive. For example, addressing the role of dual input (L1þL2) at home, CoboLewis, Pearson, Eilers, and Umbel (2002) used English (L2) literacy and oral proficiency measures to compare bilingual children equally exposed to English (L2) and Spanish (L1) at home (ESH) with their bilingual peers exposed only to L1 Spanish at home (OSH) and with monolingual English-speaking children. Group selection was based on parental reports of family language practice in the family. The researchers reported a strong effect of ESH, especially on oral English (L2) proficiency. However, the authors concluded that L2 exposure was important mainly in the first years of life. The present project continues to study this issue.

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In addition to family language input, child’s social milieu (e.g., friends, classmates) might be another important factor linked to L2 vocabulary. Cobo-Lewis et al. (2002) concluded that since over 90% of children in the schools participating in the study were bilingual, there was an apparent effect of limited L2 native proficiency. This suggests the need to examine further the role that friends and classmates play in the attainment of L1/L2 vocabulary among second generation immigrants over and above family language practice. Note that when children are young, their parents might influence their childrens’ social milieu as a part of their language management. The parents might search for a supporting socio-linguistic environment, which provides L1 input and vice versa. For example, in his study of FLP among Afrikaans-speaking South African immigrants living in New Zealand, Barkhuizen (2006) found a tendency among parents to plan for their children’s maximum exposure to L1, including the choice of suburbs with a high concentration of South African immigrants. In contrast, Okita (2002) described the phenomenon of L1 avoidance among Japanese mothers in the UK married to English men by creating L2 English social milieu for themselves and their children.

6.3 Background Factors and Vocabulary in L1 and L2 In the present study, the focus was on several factors of family background that appear to be linked to FLP, such as parental education, socio-economic status (SES), and length of residence in the host country. Findings regarding parental education and children’s L1 vocabulary maintenance are inconsistent. It has often been claimed that ethno-linguistic minorities need a strong educational experience in their own language and traditions in order to maintain their mother tongue and ethnic identity (Kloss, 1966; Allard & Landry, 1992). For example, Guardado (2002) found that SpanishCanadian families in Vancouver children who maintained L1 (Spanish) came from families headed by parents with higher levels of education. At the same time, Doucet (1991), Harres (1989) and Bill, Hernandez-Chavez, and Hudson (2000) found that the opposite was true, so that the higher the educational level of the informants, the lower loyalty and retention rates for L1 and greater L1/L2 shift. Results concerning socio-economic status (SES) were also contradictory: some families of lower SES were favorably disposed toward language shift, whereas families from higher SES favored language maintenance (Williams, 1987; Lambert & Taylor, 1996). With regard to L2 vocabulary, the SES of immigrant families was found to be an important factor, but research results concerning its role are inconclusive. Most of the existing data on this factor come from a Miami study (Oller & Eilers, 2002, Pearson, 2007) where the parents were Spanish (L1) speaking immigrants from the Cuban elite escaping Castro who arrived in Miami in the early 1960s and were characterized by relatively high social status. Another group of studies focused on Spanish (L1)

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children of Mexican descent in US, with poor SES, low parental education, very low income and low educational level. Oller and Pearson (2002) argued that the apparent ability of children to profit from the bilingual experience might result from the advantage associated with their socio-economic background, which provides access to more reading material in the home, additional parental involvement in the education process, and consequently greater academic support. In contrast, bilingual children born into poverty have been exposed to fewer books and have had fewer opportunities to increase both their L1 and L2 vocabulary. This argument was examined in the Cobo-Lewis et al.’s (2002) study mentioned above. The researchers distinguished between the effects of SES and bilingualism, and demonstrated that SES had an especially large effect on English (L2) oral proficiency. Note, however, that to date the standard approach to the description of bilingual parental background has been limited to reports on income and occupation, without reference to education as a separate factor. This approach may be attributed to the fact that in most immigrant communities parental educational level is highly correlated with SES (Kosmin, 1990), with no discrepancy between the former and the latter. At the same time, it may be misleading to treat these factors as indistinguishable from one another for some immigrant communities, as for example the Russian-Jewish immigration in Israel, which is the focus of the present study. Concerning the length of the immigrant families’ residence in the host country, the literature suggests that it is strongly associated with both L2 proficiency and L1 attrition among immigrant children (Baker, 2001). The longer the families have resided in the country, the better their command of L2 and the greater the language shift. To what extent this is evident in our case of Russian-Jewish immigrants with a tendency for integration into host society? And does the role of the length of the parents’ residence in the host country retain its significance for L2 knowledge of their children as well? The present study seeks to answer these questions. In sum, despite obvious commonalities among factors affecting the lexical knowledge of the immigrants’ children, it is important to stress that the magnitude and strength of these factors tend to vary from one immigrant population to another. In most situations, the extent of L1/L2 knowledge is likely to be related to a complex interaction of many socio-cultural and socio-linguistic variables reflecting the unique context of each immigrant population (Edwards, 1992). It is important, therefore, to examine each ethno-linguistic group individually. Note, however, that no research can address all factors related to the role of socio-cultural and socio-linguistic conditions in children’s L1/L2 vocabulary knowledge (Baker, 2001; Ellis, 1985; Spolsky, 1989). Concerning L1 vocabulary knowledge as a dependent measure, the focus was, therefore, on the following independent variables of parents’ and children’s language ideology (i.e., language attitudes), parents’ language practice (i.e., language choice with children), parents’ language management (i.e., teaching L1 literacy to their children), background of FLP (i.e., length of parents’ residence in Israel,

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parental education level) and socio-economic index of the school as a measure of parents’ SES. Regarding L2 vocabulary knowledge as a dependent measure, the independent variables included were parents’ language practice (i.e., parentchild language and parents’ self-reported L2 proficiency), background of FLP (i.e., length of parents’ residence in Israel, parental education level, parental education in Israel), and children’s social milieu (percent of Russian-speaking classmates and percent of Russian-speaking friends) and socio-economic index of the school as a measure of parents’ SES.

6.4 Method 6.4.1 Participants The sample consisted of 70 second grade Russian-Hebrew speaking children and 70 of their parents (73% of the parents who participated were mothers). Children were selected from 12 elementary schools situated in the northern region of Israel. The children were speaking Russian as the first and dominant language at home, most of them were born in Israel (n ¼ 65) or immigrated to Israel at least 5 years before the start of schooling.

6.4.2 Measures 6.4.2.1 Socio-Economic Index of the Schools Because information concerning parental SES was not available, data on the socio-economic index (SEI) of each school involved in the study was collected. This index is calculated based on the parents’ reports regarding their income and occupation, and on a ranking of the families’ residential area, but not on their educational level. This index may therefore be considered as an equivalent of the SES of the families participating in the study. The socio-economic index of schools in Israel is measured on a 10-point scale ranging from 1 to 10, with higher scores indicating lower SES. 6.4.2.2 Parents’ Questionnaire The questionnaire was based in part on an existing questionnaire (DonitsaSchmidt, 1999) and was developed in part specifically for this study. The questionnaire took approximately 30 min to complete and included the following 4 sections (lettered A to D): (a) Background information: The parents were asked to provide information about the year of immigration, educational level of both parents, and schooling in Israel. (b) Language practice and Hebrew (L2) proficiency: Parents were asked to state their language of choice: only Russian (1), only Hebrew (2), or both

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Russian and Hebrew (3), with spouse, parents, and offspring and in various leisure time situations that necessitate the use of language (e.g., reading books for pleasure, reading newspapers, listening to radio programs, and watching TV). In addition, parents were asked to rate their language proficiency in Hebrew (L2) using ‘‘can-do’’ items in different skills (speaking, comprehending, writing, and reading), in both formal and informal situations (e.g., reading a book vs. reading signs). There were 8 items for each language. To increase statistical power and for the purpose of data reduction, a composite measure of parents’ Hebrew language proficiency (M ¼ 4.1; SD ¼ 0.81) has been constructed based on principal component analysis. (c) Language management: The parents were asked whether their child has learned to read Russian, and who exposed the child to Russian literacy (parents, grandparents, caregiver, or teacher within the framework of a community school). (d) Language ideology: Eight items concerning attitudes toward L1 maintenance and two items regarding myths about language, formulated as statements (see details in Schwartz, 2008). Responses were provided on a 5-point Likert-scale, ranging from ‘‘completely agree’’ to ‘‘completely disagree.’’ To increase statistical power and for the purpose of data reduction, principal component analysis was used to extract three factors: (1) ‘‘positive attitude toward development of L1 and L2 at home and L1 literacy acquisition at school’’ (Parents’ attitudes L1þL2); (2) ‘‘attitudes toward developing only L1 at home’’ (Parents’ attitudes L1); (3) ‘‘attitudes toward L1–L2 shifting’’ (Parents’ attitudes L2). 6.4.2.3 Children’s Questionnaire The questionnaire took approximately 20 min to complete and included the following three sections (lettered a to c): (a) Background information: The children were asked about number of close friends, and the number of Russian-speaking friends. (b) Language management and practice: Nine items requesting information about the children’s linguistic choice and use: (1) Russian only, (2) Hebrew only, or (3) both Russian and Hebrew, with father, mother, grandparents, siblings and Russian-speaking friends. This section also provided information about the children’s active practice of reading in Russian, that is, whether the children read frequently in Russian. (c) Language ideology: Eight yes-no questions were asked to determine the attitudes of the children toward L1 maintenance and L1–L2 shifting (see details in Schwartz, 2008). Because of the children’s young age, 3-point scale has been used to score responses, with the highest score (3) representing a positive answer and the lowest score (1) a negative one. Point 2 signified a neutral attitude. The principal component analysis has been applied to

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construct the following three factors: (1) ‘‘positive attitude toward development of L1 and L2 at home and L1 literacy acquisition at school’’ (Children’s attitudes L1þL2); (2) ‘‘attitudes toward developing only L1 at home’’ (Children’s attitudes L1); (3) ‘‘positive attitude toward only Hebrew at home’’ (Children’s attitudes L2). 6.4.2.4 Composite Measures of Russian and Hebrew Vocabulary Two composite measures of Russian (L1) and Hebrew (L2) vocabulary were created by extracting the first principal component from a set of five vocabulary measures (semantic categories, word descriptions with and without stimulus questions, antonyms, and receptive vocabulary) (see details in Schwartz, 2008; Schwartz, Kozminsky, & Leikin, 2009).

6.4.3 Procedure The study was carried out in the first 2 months of the school year. The children’s tasks and questionnaire were completed individually in two separate sessions lasting about 40 min each during school time. The questionnaires for parents were completed at home.

6.5 Results 6.5.1 Background of the Family Language Policy The SEI of the children’s schools ranged from 4.25 to 7.40, indicating a middlelow range. At the same time, the data obtained from the parents’ questionnaires showed that the level of education reported by parents was relatively high (M ¼ 14.0; SD ¼ 1.53, in years). All parents had at least a high school diploma (10 years of school in the FSU, where compulsory education is from age seven to seventeen. Forty-three percent of the women and 47% of the men had earned a university degree (at least 5 years of post–secondary education in the FSU). The correlation between maternal and paternal education was r ¼ 0.41, p < 0.01. The average score of the mother’s and the father’s education served as a measure of parental education. Furthermore, 60% of the parents were educated primarily in Israel: 69% participated in 1-year professional courses and 31% received conventional higher education. The correlation between parental educational level and their educational experience in Israel was reliable but rather low (r ¼ 0.26, p < 0.05). Therefore, parental educational level and their educational experience in Israel were treated as two separate and independent variables. As for length of the families’ residence in Israel, it was relatively long (M ¼ 11.6; SD ¼ 3.93).

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6.5.2 Family Language Practice and Management The parents’ questionnaire shows that Russian was the primary language used by parents with their spouses (72%), with their parents (100%), and when reading for pleasure (82%). At the same time, a strong tendency to permit a mixture of L1 and L2 in communication with the children was found. 69% of the parents noted that using Hebrew with the children was a choice conditioned mainly by linguistic circumstances, when it was impossible to find the right word or expression in Russian. As a rule, however, parents reported placing emphasis on maintaining L1. Language choice in other personal domains (reading newspapers, listening to radio, and watching TV) tended to include both Russian and Hebrew. As for social environment, 71% of the parents reported being part of a Russian-onlyspeaking social interaction. The children also reported frequent use of Russian with their parents (59% with fathers, 56% with mothers, 96% with grandparents), but some were more likely to communicate with their parents in Hebrew only (9% with fathers, and 11% with mothers). As expected, the children commonly used Hebrew with their siblings (43%) and with Russian-speaking friends (70%). Concerning family language management, 61% of the parents stated that their children have been taught literacy in L1 and in most cases within a supplementary education system. It was further found that 41% of children reported active involvement in reading in L1 and 70% stated that during childhood they were read to in the heritage language only. There was significant correlation between the parental report on children’s L1 literacy and the information provided by the children about active involvement in reading in L1 (r ¼ 0.45; p < 0.01). The absence of a stronger relationship between the former and the latter may be attributed to the fact that some children were not enthusiastic about reading in the heritage language. As for the Hebrew language, the parents reported a relatively high level of proficiency (M ¼ 4.1; SD ¼ 0.81), clearly indicated weaker ability in written domains (i.e., writing a formal letter, reading a book).

6.5.3 Family Language Ideology The majority of the parents had a positive attitude toward their children’s progress in both languages, with emphasis on the maintenance of the heritage language. Parents tended to support dual language development and valued mastery of both languages. In contrast, parents appeared to downplay widespread myths about linguistic handicaps attributed to bilingualism (Cummins, 1984). Only 3% of parents were unequivocal about the negative effect of a bilingual upbringing with L1 dominance at home. At the same time, the parents were decisive about the notion that the language of the host country can be learned easily in school.

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Despite being educated in a non-additive Hebrew context and with the notion that Hebrew is the language of national identity, 60% of bilingual children were agreeable to learning Russian in school. Only 30% of the children supported the idea of a complete L1–L2 shift at home. Finally, the children conclusively voiced the need for being more proficient in both Hebrew and Russian.

6.5.4 Correlational and Regression Analysis and First Language Vocabulary Knowledge A series of correlational analyses was conducted to examine the relation between the children’s vocabulary knowledge in L1 and the independent factors that may be connected to it: parents’ and children’s language ideology (i.e., language attitudes), parents’ language practice (i.e., language choice with children), parents’ language management (i.e., teaching L1 literacy to their children), background of FLP (i.e., length of parents’ residence in Israel, parental education level) and socio-economic index of the school as a measure of parents’ SES. Concerning FLP factors, significant positive relationships were found between the composite measure of vocabulary knowledge in L1 and the parents’ language management, i.e., children’s L1 literacy knowledge, (r ¼ 0.47, p < 0.001). In addition, a relatively weak but still significant negative correlation was found between vocabulary knowledge and the parent’s language use indicating that the more the co-existence of both languages was permitted at home, the weaker the L1 vocabulary knowledge was. Furthermore, a weak and insignificant association between all factors relating to the parents’ ideology regarding language and the dependent variable was found. The parents’ ideology concerning language did not correlate significantly with their reports about language management and practice at home, nor with any of the measures of the children’s attitudes about language. By contrast, there was a significant correlation between the composite measure of vocabulary knowledge in Russian and the children’s positive attitude toward the development of both languages at home and toward L1 literacy acquisition at school (r ¼ 0.39, p < 0.001). The correlational analysis revealed a weak but significant negative relationship between the children’s mastery of L1 vocabulary and their desire to speak only Hebrew at home (r ¼ –0.25, p < 0.05). Finally, children’s reports on active practice of reading in Russian were related considerably with their actual command of the heritage vocabulary (r ¼ 0.40; p < 0.01). Finally, concerning background factors of FLP (length of parents’ residence in Israel, parental education level and SEI of the school as a measure of parents’ SES) no significant correlations were obtained. Furthermore, a multiple regression analysis was prepared (see Table 6.1). The composite measure of L1 vocabulary knowledge was entered as a

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Table 6.1 Summary of multiple regression analysis for family policy variables contributing to the composite vocabulary knowledge in L1 Variable R2 ¼ 0.39 B SE B b SEI of the school Length of parents’ residence in Israel Parental education Parents’ attitudes L1þL2 Parents’ attitudes L1 Parents’ attitudes L2 Children’s attitudes L1þL2 Children’s attitudes L1 Children’s attitudes L2 Parent’s language practices (language choice with children) Parents’ language management (teaching children to read in L1)

0.12 0.01 0.03 –0.10 –0.18 –0.05 0.40 –0.17 –0.10 –0.20 0.24

0.10 0.03 0.07 0.11 0.11 0.08 0.16 0.11 0.09 0.08 0.08

0.15 0.06 0.05 –0.09 –0.17 –0.06 0.37* –0.22 –0.12 –0.25* 0.31**

* p direct object modifier. This strategy, however, seems to be language-related and complicated to a degree even for native speakers of Hebrew (Leikin & Breznitz, 2001; Leikin, 2008). Moreover, this strategy seems to develop at relatively later stages of language/reading acquisition (Sokolov, 1984), and Hebrew-speaking readers use several other procedures for processing the grammatical functions of words, including the word-order strategy (Leikin, 2002). Selection of a particular strategy may be influenced by different factors, including the lexical-morphological characteristics of the stimuli. Note, however, that the results obtained in Hebrew cannot be generalized or even adequately interpreted in the absence of data from other languages. Therefore, examination of the process of identification of the words’ grammatical functions in other languages becomes important for singling out the universal and specific features of sentence processing. Another aspect of the problem has to do with cognitive and neurophysiologic characteristics of bilingual language processing. Several studies on language processing by bilinguals have used ERP measures. Investigation of semantic aspects of language processing found the latency of the N400 component to semantic anomalies to be delayed in fluent bilinguals compared with monolinguals and in L2 compared with L1 within the bilingual group (Alvarez, Holcomb, & Grainger, 2003; Hahne et al., 2006; Weber-Fox & Neville, 1996). For phrase structure violations, monolinguals showed differential effects for an early left anterior negativity (N125) and a second left lateralized negativity (N300500), which were followed by a P600 effect (Hahne et al., 2006; Weber-Fox & Neville, 1996). Late L2-learners displayed a more bilateral ERP pattern for syntax-related negativity (N300500) and an absence of modulation of P600, which has been interpreted to reflect a process of syntactic

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Identification of Grammatical Functions in Two Languages

245

reanalysis and repair (Friederici, 1999). Other studies, however, detected P600 effects in L2 learners in the same conditions as in native speakers (e.g., Hahne & Friederici, 2001). Considered together, these results suggest that morphosyntactic processing of L2 learners depends, among other things, on their language proficiency (Clahsen & Felser, 2006a). The present study aimed to examine brain activity through ERP amplitudes and latencies and by areas of brain activation in adult native (Russian and Hebrew) and bilingual (Russian/Hebrew) readers when processing the grammatical functions of words during the reading of sentences in different languages. Primarily, we proposed to investigate differences between processing strategies and patterns of brain activation in Hebrew and Russian as first languages (L1). We also intended to trace differences in ERP measures between processing patterns in first and second languages. We hypothesized that there are substantial differences between sentence processing in Hebrew and Russian and between processing in L1 and L2. Specifically, we suggested that readers identify the grammatical functions of words using morphologically based verb-oriented strategies in Hebrew and morphologically based but not verb-oriented strategies in Russian. We expected also that all characteristics of native and second language processing outlined above have clear neurophysiological correlates and are manifested by changes in the amplitudes and latencies of N100/P200, P300, and P600 ERP components, with variation in the localization of brain activation for L1 and L2/L3 sentence processing.

12.3 Method 12.3.1 Participants Thirty-six normally reading, male university students from middle-class backgrounds participated in this study, consisting of 16 native speakers of Hebrew (who had also participated in Leikin’s study, 2008), and 20 native speakers of Russian. The Russian group consisted of bilingual individuals who had immigrated to Israel at least 5 years earlier, have since acquired a thorough command of Hebrew (after puberty), and still read fluently in their native language. Adequate levels of reading proficiency were assessed for both groups in both languages using standard reading tests for adults (National Institute for Testing and Evaluation, 1996; Test for Russian as a First Language, 2006). Participants ranged in age from 18 to 29 years (see Table 12.1). Each participant was right-handed and displayed normal or corrected to normal binocular vision. Participants did not report any history of reading disabilities or hard neurological signs. All participants were paid volunteers from the University of Haifa.

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M. Leikin and E. Ritvas

Table 12.1 Mean results of native Russian and Hebrew speakers in behavioral and readinga baseline tasks Russian Hebrew speakers speakers Measure M S.D. M S.D. t Age Raven matrices (raw scores) Digit span standard score Decoding, accuracy – words Decoding, speed – words (sec per item) Decoding, percent accuracy – pseudowords Decoding, speed – pseudowords (sec per item) Decoding, percent accuracy – connected text Decoding, output – connected text (words per minute) Reading comprehension (correct items)

25.9 58.6 11.5 98.9 0.6 98.8 0.7 99.5 270.2

1.82 15.33 3.70 2.03 0.11 1.87 0.16 0.46 30.69

25.9 70.0 12.7 99.4 0.5 95.5 1.2 99.6 141.7

2.06 19.86 2.18 0.59 0.08 4.47 0.23 0.47 23.86

0.14 1.96 1.13 1.10 3.74** 2.79* 7.50*** 0.17 13.85***

4.8

0.40

3.2

1.28

4.90***

* p < 0.05, ** p < 0.01, *** p < 0.001 a All the reading tasks were performed in the native language: Russian for native Russian speakers and Hebrew for native Hebrew speakers

12.3.2 Behavioral Baseline Measures 12.3.2.1 General Ability I. General nonverbal ability was assessed by the Raven Standard Progressive Matrices (Raven & Court, 1976), a nonverbal test for measuring IQ. II. Verbal Short Time Memory/Working Memory was assessed by the Digit Span Test (WAIS, Wechsler, 1994), in which the examinee is asked to repeat a number sequence identical to that presented by the examiner (in the same order for Digits Forward and in reverse order for Digits Backward). The longest correct sequence memorized was recorded and a standard score derived. 12.3.2.2 Reading Ability Several tests were used to obtain estimates of reading accuracy, time, and comprehension in Hebrew and Russian. The first set of tests provided measures of decoding accuracy for real words and pseudowords. The second set assessed reading time in context and evaluated reading comprehension. 12.3.2.3 Decoding Skills One Minute Tests (Shatil, 1997) for Hebrew language. This battery included two subtests in which participants were asked to read lists as quickly and accurately as possible within 1 min. The first list contained 100 real words

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arranged in order of increasing length (1 to 5 syllables) and decreasing frequency. The second list was comprised of 100 pseudowords arranged in order of increasing length (1 to 5 syllables). The decoding skills of the Russian (L1) group in Russian language were assessed by reading 40 pseudowords and 40 words arranged in order of increasing length (1 to 5 syllables) and decreasing frequency (Test for Russian as a First Language, 2006). Scores were based on the number of words/pseudowords read correctly. To obtain a comprehensive decoding score, Z-scores were first calculated for each of the tests (i.e., words and pseudowords for each language). 12.3.2.4 Reading Comprehension, Accuracy, and Speed in Context Text-reading performance was measured using 3 texts from the Reading Test section of the Israeli Psychometric SAT test (National Institute for Testing and Evaluation, 1996) containing one text in Hebrew and one in Russian (for the group of native Russian speakers). Each text contained a short story comprised of 25 sentences (about 300 words). The story was read silently in each language. Subsequently, 5 multiple-choice questions were presented. Comprehension scores were based on the total number of correct answers for each text.

12.3.3 Electrophysiological Baseline Measures 12.3.3.1 Target Detection Tasks These tasks were administered in order to habituate the participants to the experimental situation and to verify correct response based on brain activity (P300 component). The tasks were administered in auditory and visual modalities. For the auditory modalities, stimuli were 1000 and 3000 Hz tones presented consecutively through a PC speaker. For the visual modalities, stimuli were two Hebrew block letters, 0.64 cm (1/4 in) high, presented successively at the center of a computer screen. Stimulus presentation time depended upon the latency of the participants’ responses. Targets occurred 20% (n ¼ 20) of the time and non-targets 80% of the time (n ¼ 80). Stimuli were presented for duration of 250 ms at an ISI of 700 ms. Participants were asked to count the target stimuli and ignore the non-targets. 12.3.3.2 Experimental Stimuli Twenty five groups of sentences (75 sentences) in each of the two languages (Hebrew and Russian) were presented. Each group contained three sentences of 5–8 words each. Two multiple-choice questions were asked on each item. In each language the items were regular declarative sentences in SVO (subjectverb-object) syntactic order and included the three grammatical functions under study: subject, predicate, and direct object. Stimuli included the same words with interchangeable grammatical functions and positions in the sentences. In

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each group of three sentences the same word (noun) appeared in three different grammatical roles. Thus, the target word appeared at the beginning of the sentence (subject), in the intermediate or the terminal position (predicate; predicate nominative partly in Russian), and in the intermediate or the terminal position (object). For example, in Hebrew: ‫( את המוצרים השונים החבילה הכילה‬The package contained the various products), ‫( הקופסה הגדולה הייתה חבילה‬The big box was a package); ‫( אנחנו שולחים את החבילה לחברים‬We are sending the package to friends); and in Russian: Нефть разлилась по всему пляжу (The oil washed over the beach), Геологи нашли нефть в пустыне (Geologists found oil in the desert), Черная жидкость – нефть (The black liquid is oil). The length of the sentences in Hebrew and Russian were 5.7 and 5.9 words, respectively, with an average word length of 4.5 letters in Hebrew and 4.6 in Russian. We were only able to match word frequencies in Hebrew and Russian approximately, because there are no reliable data on word frequencies in Hebrew [except for the relatively old and small Balgur’s dictionary for school children (Balgur, 1968) (Zasorina, 1977)]. 12.3.3.3 Procedure Each testing session lasted approximately 60 min. Participants were seated in a quiet room, 1.5 m from a PC (Windows) computer screen. Experimental task presentation was counterbalanced. Participants were connected to an Electrocap and were instructed to remain quiet and refrain from moving during the testing session. They were also told that it was important to avoid excessive eye movements and blinking as much as possible. The items appeared one at a time on the computer screen. Participants were instructed to begin reading the item the moment it appeared on the screen. After reading the item, they pressed a button on the keyboard, whereupon the text was automatically erased and the multiple-choice questions were displayed. Participants indicated their answer by pressing a number on the keyboard (1–4) that corresponded to the answer chosen. Measures of comprehension and reaction time were determined for each reading item in the two presentation conditions. The two forms were counterbalanced across one experimental condition. 12.3.3.4 Window Presentation (With Electrophysiological Measures) The stimulus sentences appeared word by word. This manner of presentation was adopted in order to reduce eye movements by focusing the participant’s gaze on the center of the computer screen. As word presentation rates were calculated for each individual reader, presentation rates differed across participants. Thirty-two channels of electroencephalogram (EEG) were recorded using a Bio-Logic Brain Atlas III computer system with brain mapping capabilities. The system used a bandpass of 0.1–70 Hz interfaced with a 20-channel, 12-bit A/D converter. The EEGs were sampled at a rate of 250 Hz (dwell time ¼ 4.0 ms)

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beginning 100 ms before stimulus onset. A full array of electrodes was placed according to the International 10/20 system (Jasper, 1958) by means of an Electro-cap (a nylon cap fitted over the head with 9 mm tin electrodes sewn into it). Nineteen scalp electrodes were used according to standard 10/20 system locations: PF1, PF2, F7, F3, FZ, F4, F8, T3, C3, CZ, C4, T4, T5, P300, PZ, P4, T6, O1, O2, all referenced to an electrode on CVII (the seventh vertebra) and grounded to Fpz. In addition, one electrode was applied diagonally below the left eye to monitor eye movement. During data collection electrode impedances were kept below 5 K by first treating scalp areas with a mildly abrasive cleanser (Omni-Prep) and using an electrolyte gel (Electro-gel). Trial onset was marked on the Oz channel of EEG by a positive polarity 5 mV pulse delivered from an IBM-PC 486 computer. The pulse was delivered at the beginning of each word in each item. Signal averaging of the raw EEG data was performed off-line. EEG data were separated into discrete trials. After the eye movement correction, we determined the averages of the individual trials according to the experimental data set. There were three average trials, one for each of the three sentence elements across items (separately for each language). The averages were combined to form one set per participant, resulting in one data set for each participant and reflecting averaged EEG activity of the words representing subject, predicate, and object in two languages and for first and second language conditions. Evoked potentials were measured for each participant, for each word, in every item. Only single trials free from eye movements and associated with correct responses were averaged to obtain the event-related potentials. Grand averages over conditions and subjects were then performed for each experiment for each of the 19 scalp electrodes. ERP peaks were first identified and then validated by a machine-scoring algorithm. Latencies were measured from stimulus onset. Amplitudes were measured relative to the mean voltage of each channel during the pre-stimulus baseline.

12.4 Results 12.4.1 Background Behavioral Measures The performance of the Russian and Hebrew groups on behavioral cognitive and reading (in native language) baseline tasks is shown in Table 12.1. No differences were evident between the two groups on the general ability and working memory capacity tests, but significant differences were found between the two groups on most of the reading measures in their native languages (Russian and Hebrew, respectively). Russian readers exhibited significantly shorter reading times for most of the reading tasks than Hebrew readers did, and performed more accurately on these and on the reading comprehension test. Thus, the Russian readers were found to read more fluently and more accurately in their native language than Hebrew readers did in theirs. Russian speakers performed more poorly on Hebrew reading measures than in

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Table 12.2 Comparison of Russian speakers performing reading-related tasks in Russian and in Hebrew Russian Hebrew Measure M S.D. M S.D. t Decoding, percent accuracy – words Decoding, speed – words (sec per item) Decoding, percent accuracy – pseudowords Decoding, speed – pseudowords (sec per item) Reading comprehension (correct items)

98.9 0.7 98.8 0.7 4.8

2.03 0.11 1.87 0.16 0.40

96.0 1.3 91.5 1.7 2.8

2.60 0.40 4.00 0.44 1.06

4.08* 6.01** 9.13** 12.61** 7.44**

* p < 0.01, ** p < 0.001

their native language. They were significantly less accurate in reading Hebrew words and pseudowords and on the reading comprehension test. Moreover, the Russian speakers read significantly slower in Hebrew than in Russian on timed tests for words and pseudowords (Table 12.2).

12.4.2 Experimental Tasks In both groups of participants, P100, P200, P300, N400, and P600 ERP waves were identified for subject, predicate, and object in each sentence, in all reading items, and in both languages (see Figs. 12.1 and 12.2 for examples). Baseline adjustment was performed according to the average values, which were measured in the interval between 200 ms and stimulus appearance separately for each grammatical function. The most prominent ERP appeared in the Cz electrode. Mixed factorial ANOVAs were performed to compare brain activity between both groups of participants when reading sentences in their native languages. At the first stage, two ANOVAs were performed, separately for amplitudes and latencies. ERP component, grammatical role, and scalp region served as withinsubject factors, while group served as the between-subject factor. Additionally, mixed factorial ANOVAs were performed to compare brain activity among Russian speakers when reading sentences in Hebrew and Russian. Furthermore, mixed factorial ANOVAs were performed to compare brain activity among Russian speakers and Hebrew speakers when reading sentences in Hebrew. ERP component, language, grammatical role, and scalp region served as withinsubject factors, while group served as the between-subject factor.

12.4.3 Comparison of Brain Activity Between Two Groups of Participants When Reading Sentences in Their Mother Tongue After performing two ANOVAs, one on all ERP component amplitudes and one on all ERP component latencies, two significant effects were found. First, a main effect of group on latency (F1,23 ¼ 10.66, p < 0.01) occurred significantly

12

Identification of Grammatical Functions in Two Languages Hebrew Speakers

Cz

Russian Speakers

251

6 4

Subject Predicate Object

µV

Pz

2 0 −2 −4

−200 −100 0 100 200 300 400 500 600 700 ms

Fig. 12.1 ERP wave forms identified for subject, predicate, and object in Hebrew

later among Hebrew speakers than among Russian speakers. Second, a main effect of region on amplitude (F4.20,96.58 ¼ 38.29, p < 0.001) was found, with amplitudes significantly higher at anterior regions than at posterior ones. Additionally, a region group interaction effect on amplitude (F4.20,96.58 ¼ 7.45, p < 0.001) and latency (F3.07,70.57 ¼ 4.61, p < 0.01) was found. In the majority of cases both groups showed a gradual incline on amplitude from left-anterior to right-posterior regions and an inverse relation in latency magnitude. A grammatical role x group interaction effect on latency (F1.72,39.48 ¼ 5.10, p < 0.05) was also found. The results showed an inverse relation between the Hebrew and Russian groups in latency magnitude for grammatical role. Finally, a region grammatical role group interaction effect was found on amplitude (F4.18,96.18 ¼ 3.15, p < 0.05). In the majority of cases, Russian readers exhibited significantly higher amplitudes than Hebrew readers did. Following this initial analysis, separate ANOVAs were performed on the amplitudes and latencies of P100, P200, P300, N400, and P600 (a total of 12 ANOVAs). Grammatical role and scalp region served as within-subject factors and group as the between-subject factor. In order to control the overall probability of type I errors, only effects that had previously been found to

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Cz

Russian Speakers

6

Subject Predicate Object

4

Pz

2 0 −2 −4 −200

−100

0

100

200

300

400

500

600

700

ms

Fig. 12.2 ERP wave forms identified for subject, predicate, and object in Russian

be significant across ERP components were examined. In all ANOVAs Greenhouse-Geisser correction was applied for sphericity values lower than 0.75, and Huynh-Feldt correction for sphericity values greater than 0.75 (Field, 2005). In this case, the following significant effects were found: 1. Main effect of group on latencies N100 (F1,26 ¼ 8.80, p < 0.01), P100 (F1,26 ¼ 14.97, p < 0.01), P200 (F1,29 ¼ 6.44, p < 0.05), N400 (F1,27 ¼ 13.55, p < 0.01), and P300 (F1,29 ¼ 5.74, p < 0.05). In all cases latencies among native Hebrew speakers were longer than among Russian speakers. A similar effect was found in Leikin’s (2008) study, which investigated syntactic processing in Hebrew and English by native and bilingual adult speakers, with the Hebrew L1 group showing longer latencies than the English L1 group reading in their native languages. 2. Main effect of region on P100 (F2.08,54.19 ¼ 19.14, p < 0.001), P200 (F2.75,79.70 ¼ 58.99, p < 0.001), N400 (F2.92,78.91 ¼ 32.39, p < 0.001), and P300 (F3.00,86.98 ¼ 48.42, p < 0.001) amplitudes. In all cases higher amplitudes were found in posterior than in central regions and in central regions than in anterior ones. Lower amplitudes were found in the left hemisphere, particularly in central and posterior regions. 3. Region group interactions effects on N100 (F1.48,38.41 ¼ 3.97, p < 0.05), P200 (F2.75,79.70 ¼ 16.49, p < 0.001), N400 (F2.92,78.91 ¼ 3.13, p < 0.05), P300

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253

Fig. 12.3 Region group interaction effect on N400 amplitude

(F3.00,86.98 ¼ 6.46, p < 0.01) and P600 (F2.50,72.38 ¼ 6.70, p < 0.01) amplitudes. Both groups showed higher amplitudes in right-posterior than in central regions and in central regions than in left-anterior ones (Fig. 12.3). In addition, a marginally significant effect on N400 latency (F2.50,67.38 ¼ 2.53, p ¼ 0.075) was found. 4. Grammatical role group interaction effects on N400 (F2,54 ¼ 5.57, p < 0.01) and P300 (F2,58 ¼ 10.54, p < 0.001) latencies. The results showed an inverse relation between the Hebrew and Russian groups in latency magnitude for grammatical role. In the Hebrew L1 speaking group the longest latencies were elicited by the object and the lowest ones by the subject, whereas Russian speakers showed the opposite latency activation order: subject > object > predicate (see Leikin, 2008 for details). 5. Region grammatical role x group interaction effects on P600 amplitude (F4.66,135.20 ¼ 3.90, p < 0.01), and a marginally significant interaction on P200 amplitude (F3.19,92.47 ¼ 2.51, p ¼ 0.06). In the majority of cases, Russian readers exhibited significantly higher amplitudes than Hebrew readers did. In the majority of cases both groups showed a gradual incline on amplitude from left-anterior to right-posterior regions.

12.4.4 Comparison of Brain Activity Among Russian Speakers When Reading Sentences in Russian and Hebrew Two ANOVAs performed separately for amplitudes and latencies revealed two significant effects. First, a marginally significant effect of language on latency

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(F2,26 ¼ 2.99, p ¼ 0.068) was shown. The latencies were significantly longer while reading sentences in Hebrew than in Russian. Second, a main effect of region on amplitude (F2.54,33.02 ¼ 5.27, p < 0.01) was found. In the majority of cases, amplitudes in the posterior regions were greater than those in central regions, and these were greater than amplitudes in anterior regions. A marginally significant effect on latency was also found (F3.15,40.89 ¼ 2.33, p ¼ 0.086). Latencies in the posterior regions were longer than those in central regions, which were longer than those in anterior regions. Following this initial analysis, separate ANOVAs were performed on the amplitudes and latencies of P100, P200, P300, N400, and P600 (a total of 12 ANOVAs). Language, grammatical role, and scalp region served as withinsubject factors. The following significant effects were found: 1. A main effect of language on N400 latency (F1.53,19.94 ¼ 6.15, p < 0.05) was found. Latencies in the processing of Russian sentences were shorter than those in the processing of Hebrew sentences. 2. A main effect of region on P100 (F2.69,24.22 ¼ 6.37, p < 0.01), P200 (F1.62,19.45 ¼ 3.84, p < 0.05), N400 (F2.41,31.36 ¼ 4.02, p < 0.05), P300 (F2.57,33.38 ¼ 9.24, p < 0.001), and P600 (F1.60,20.73 ¼ 9.61, p < 0.01) amplitudes was found. P100, P200, N400, and P300 amplitudes in posterior regions were greater than those in central regions, and these were greater than those in anterior regions (Fig. 12.4), whereas P600 amplitudes were

Fig. 12.4 Main effect of region on P100 amplitude

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greater in anterior than in central regions and in central regions than in posterior ones. Additionally, P200 amplitudes in left central and posterior regions were smaller than those in medial regions. A main effect of region on P200 latency (F2.30,27.61 ¼ 5.00, p < 0.05) was also found. Latencies in posterior regions were greater than those in central regions, which were greater than those in anterior regions. Additionally, latency in the right posterior region was significantly greater than in the left posterior region.

12.4.5 Analysis of the Sources of Activity To describe the experimental conditions and timings in which there were differences in the sources of brain activity, comparisons of scalp maps were performed (TANOVA – Strik, Fallgatter, Brandeis, & Pascual-Marqui, 1998) using the LORETA-Key computer program. Separate comparisons were carried out between Russian and Hebrew speakers for subject, predicate, and object. Moreover, within-subject comparisons were carried out for reading sentences in Hebrew and Russian. Finally, comparisons of brain activity during the reading of words with different grammatical functions (e.g., subject vs. predicate) were performed. Altogether, 21 comparisons were performed. To control the general probability of type I error, significance of greater than 0.0024 was needed. Significant differences (or differences with borderline significance) were found in 8 comparisons with 18 timings. Maps of current density produced with the LORETA-Key computer program were compared with timings in which differences in scalp maps were found (Strik et al., 1998). An analysis revealed several significant differences. First, comparing subject and predicate in native Hebrew speakers reading Hebrew sentences, a stronger activation was found when reading a predicate than a subject in two timings (Fig. 12.5). There were differences in the medial frontal gyrus (168 ms after stimulus onset) and in the left inferior frontal gyrus (285 ms).

(a)

(b)

Fig. 12.5 Comparison of brain activity in native Hebrew speakers processing subjects and predicates in Hebrew. (a) 168 ms after stimulus onset. (b) 285 ms after stimulus onset

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Fig. 12.6 Comparison of brain activity in native Russian speakers processing subjects and predicates in Russian

Second, comparing subject and predicate in native Russian speakers reading Russian sentences, a stronger activation was found when reading a subject than a predicate in the left superior frontal gyrus, between 270 and 277 ms after stimulus onset (Fig. 12.6). On the one hand, the timing shown in two above-noted cases (between 168 and 285 ms) seems to resemble time intervals that are known as P200 and P300 ERP components. Although the P200 component is generally thought to reflect late sensory and early perceptual processes, it is also sensitive to different grammatical classes (Pulvermuller, Preissl, Lutzenberger, & Birbaumer, 1996) and lexical-morphological distinctions (Breznitz, Oren, & Shaul, 2004; Leikin, 2002). In turn, P300 appears to be associated with stimulus classification and updating in short-term memory (Donchin, 1981). However, it can also be elicited by morphosyntactic violations (Coulson, King, & Kutas, 1998) and processing of grammatical functions (Leikin, 2002). On the other hand, the regions found to be sources of differences are known to be associated with syntactic processing (e.g., Brauer & Friederici, 2007; Dapretto & Bookheimer, 1999; Friederici et al., 2000) and even with semantic processing (Friederici et al., 2000; Seghier et al., 2004; Vitacco, Brandeis, Pascual-Marqui, & Martin, 2002). Third, comparing subject in Russian speakers reading Russian and Hebrew sentences, a stronger activation was found reading a subject in Russian in the time window that started at 188 ms after stimulus onset and continued up to 434 ms. Within this time slice, there were several small windows in which significant differences were found: between 188 and 285 ms it was generally shown in the right frontal medial and pere-sylvian areas and in the left supramarginal gyrus, angular gyrus, and post-central medial areas. The same sources of differences were found between 313 and 434 ms, with the differences being more prominent in posterior areas (SMG, AG), in the medial postcentral areas, and in the right posterior middle temporal gyrus (Fig. 12.7). It should be noted

12

Identification of Grammatical Functions in Two Languages 188−285 ms

313−434 ms

188−285 ms

313−434 ms

257

Fig. 12.7 Comparison of brain activity in native Russian speakers processing subjects in Russian and in Hebrew

that not all phenomena found in our study may be easily explained. For example, it is right in regard to the lack of late time interval (something like P600) and to the contradictory existence of significant involvement of Right Hemisphere areas in the processing, though in the literature there are a few references concerning the contribution of right STG, temporal median gyrus, and posterior cingular gyrus to sentence processing (Lauro, Tettamanti, Cappa, & Papagno, 2008; Mercure, Ska, & Yves, 2006). Fourth, comparing predicates in native Russian speakers reading Russian and Hebrew sentences, a stronger activation was found when reading in Russian in the anterior cingulate (231–242 ms after stimulus onset) and in the cingulate gyrus (273–270 ms). Fifth, comparing subject and object in Russian speakers reading in Russian, a stronger activation was found when reading a subject than an object in the left supramarginal gyrus, in the angular gyrus, and in the anterior cingulate (285–297 ms after stimulus onset).

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12.5 Discussion The present study examined brain activity by means of ERP amplitudes and latencies, and areas of brain activation in adult monolingual and bilingual readers processing the grammatical functions of words read in sentences in two languages: Hebrew and Russian. Behavioral data indicated that Russian L1 readers were more accurate and faster on most reading related tasks in their native language than were Hebrew L1 speakers reading in Hebrew. This finding confirms that the Russian speakers were proficient L1 readers despite having immigrated to Israel at least 5 years earlier. The finding is also consistent with previous studies that found Russian to be more complicated phonologically than Hebrew (Akhmanova, 1971; Shimron, 1993). This phonological complexity has a positive influence on the development of phonological awareness at the phoneme level in Russianspeaking children (Zaretsky, 2002). Therefore, it may be suggested that enhanced phonological awareness helped the Russian speaking group read more fluently and more accurately than the Hebrew L1 group. But Russian L1 speakers performed more poorly on most of the reading and reading-related tasks in Hebrew than they did in their native language. These results are also consistent with previous literature on bilingualism (e.g., Fabbro, 2001) that supports the hypothesis that one language, usually the native one, is more effective and fluent than the other. The most important outcome of the study was the revelation of significant differences in ERP measures between Russian and Hebrew readers. All our hypotheses were supported by the research findings. The results showed that different languages elicit different brain responses in bilingual (Russian/ Hebrew) and monolingual (Hebrew) speakers. There were also differences in ERP measures and brain localization (see the results of the LORETA-Key analysis) as well as in cognitive strategies employed in the processes of identifying the grammatical functions of words in the first and second language. Furthermore, the results confirmed previous findings suggesting that grammatical processing in L2 is fundamentally different from grammatical processing in one’s L1 (Clahsen & Felser, 2006a, 2006b). Comparison between the two groups reading in their native languages already revealed significant differences. Hebrew speakers exhibited consistently higher amplitudes and longer latencies of P300, N400, and P600 in all Hebrew sentence elements than did the Russian speakers. As mentioned earlier, a similar effect was found in Leikin’s (2008) study, which compared syntactic processing in Hebrew and English by native and bilingual readers. It has been shown that the Hebrew L1 group demonstrated higher amplitudes and longer latencies than the English L1 group reading in their native languages (Leikin, 2008). Higher amplitudes are thought (Taylor & Keenan, 1990) to represent greater brain effort during information processing. In turn, longer latencies are believed to reflect slower processing speed (Breznitz, 2006). Thus, the results

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seem to demonstrate that in Hebrew processing of words according to their grammatical functions is slower even among Hebrew L1 speakers and requires greater effort. Thus our study produced surprising results. It seems reasonable to expect more effective performance requiring less effort in one’s native language than in a foreign one. But these unexpected results (slow processing in the Hebrew language) can be explained by the fact that Hebrew has a rich derivational morphology. In general, Hebrew words can be decomposed into two morphemes, the root and the word pattern, but these morphemes are not appended to one another linearly; rather the phonemes of each morpheme are intertwined. Roots and word patterns are abstract structures, and only their joint combination forms specific words. Although these morphemes carry some semantic and syntactic information, their meaning is often obscure and changes for each root-pattern combination (Berman, 1985). The slower cerebral processing manifested in ERP latency in Hebrew than in Russian was observed at the initial phase of stimulus processing (P200), that is, at the stimulus classification stage, and continued into the updating in working memory stage (P300). Moreover, the higher N400 amplitude and longer N400 latency among Hebrew L1 speakers in reading Hebrew than in reading English sentences (Leikin, 2008) suggest considerable lexical-semantic processing (e.g., Breznitz & Leikin, 2000; Leikin, 2008; Osterhout, 1997). Our findings are consistent with the results obtained by Deutsch and Bentin (2001), who examined the on-line processing of semantic and syntactic information during agreement analysis using converging evidence from eye movements and ERP. Deutsch and Bentin argued that, consistent with findings obtained in other inflected languages (such as Italian, Spanish, French, and Dutch), and unlike English, the process of computing syntactic agreement in highly inflected languages is affected by semantic or conceptual factors, or both. The researchers concluded that the linguistic properties of a language, rather than differences between production and comprehension, account for discrepancies between various studies on the interrelation between semantic and syntactic processing of agreement. Thus, morpho-syntactic and lexical-semantic information in Hebrew plays an important role in processing a sentence and understanding its meaning. It may be suggested, therefore, that these multiple lexical factors decelerate cerebral processing in Hebrew. The study found a main effect of region on P100, P200, P300, and N400 amplitudes. A comparison made between groups and within each group revealed higher amplitudes in posterior than in central and in central than in anterior regions. If we accept the hypothesis that amplitude shows evidence of cerebral effort, it may be suggested that processing words with different grammatical functions requires greater effort in posterior regions. Various researchers have suggested that semantic and morphological features are processed in temporal middle and inferior regions and in left inferior frontal areas (see Heim, 2005 for a review). But the results for the processing of morpho-syntactic information are not entirely conclusive. Recent clinical findings suggest involvement of the cerebellum in syntactic and other higher cortical processing

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(e.g., Dogil et al., 2002). Deutsch and Bentin (2001), studying the ability to distinctively measure the manifestation of semantic and syntactic processes in ERPs, found a pattern of interactions between markedness, animacy, and syntactic congruity effects that were relatively obscure in eye movements. Whereas in eye movements both animacy and markedness influenced the effect of syntactic incongruity on first-pass duration, each of these factors affected a different ERP component: the congruity effect interacted only with markedness for the syntactically associated P600 and only with animacy for N400. Consequently, the ERP data disentangled the semantic and syntactic processes that interacted during the initial reading of the word in context, as reflected by firstpass duration. The absence of P600 sensitivity to animacy corroborated the view that the linguistic process indexed by this component is not sensitive to semantic information. Note that the data we obtained from P600 amplitudes revealed that higher amplitudes were evident in anterior regions than in posterior ones. A biphasic ERP pattern with an early anterior negativity followed by a P600 has been reported in several sentence processing studies (see Friederici et al., 2002, for review). P600 has been interpreted to reflect controlled rather than automatized processing (Friederici et al., 2002; Hahne & Friederici, 2001), specifically effortful syntactic integration processes at the sentence level. The P600 we obtained suggests that L1 and L2 speakers also use later sentence-based processes. Therefore, the P600 may also be responsive to processes related to word recognition that are required for its immediate integration into the local syntactic structure, such as morphological analysis. We suggest that our participants employed early processes of word-internal semantically based automatized processing that appeared in posterior brain regions, and at a later stage employed at least partially controlled syntactic processing that took place in anterior regions. The second research hypothesis postulated differences in ERP measures and in cognitive strategies between processes of identification of the grammatical functions of words in L1 and L2. A comparison between Russian- and Hebrewspeaking groups reading in their native languages registered the highest activation by N400 amplitude and the longest N400 latency, revealing a different processing profile. Moreover, the present study found different activation patterns in L1 Hebrew readers than did previous research. In previous experiments different grammatical functions influenced sentence processing differently, as reflected in ERP amplitudes and latencies (Breznitz & Leikin, 2000; Leikin, 2002). This effect was explained to indicate processes of identification of the grammatical functions of words. The patterns of brain activation among the Hebrew L1 group obtained in the present study were neither predicate-oriented nor entirely word-order types. In the Hebrew group this related to significantly longer N400 and P300 latencies for the object (object > predicate > subject). In the Russian group the N400 and P300 latencies reflected another pattern (subject > object > predicate). Thus, the patterns of brain activation were partly different in Hebrew and Russian speakers. In turn, these data confirm

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the assumption (Breznitz & Leikin, 2000) that normal readers of Hebrew identify the grammatical functions of words at least partly by means of the words’ lexical-morphological properties, while they are simultaneously affected by word order as well. In the Russian speaking group the results showed morphologically based, noun-oriented strategies, as we had hypothesized. The modification of activation patterns was yet another interesting result of the study. We speculate that this result is due to the character of the stimulus sentences in the new experiment (see also Leikin, 2008). Previous results (Leikin & Breznitz, 1999) were obtained by means of stimulus sentences that included verbs functioning as predicates as well as various prepositions. In the present study, as in Leikin (2002, 2008), one-third of the sentences was verbless. Verbless sentences are not common in Russian and are not accepted in Hebrew. Moreover, the lexical-morphological characteristics of the words that played different grammatical roles were equalized to a certain degree. In addition, in the Hebrew sentences only the preposition ett appeared as the object marker. Thus, the obtained activation pattern may be explained by the reduction of lexical-morphological differences between the three sentence elements. This seems especially critical for verbless sentences. Absence of the verb can cause a relative decrease in brain activation in response to the predicate, and equalization of intensity and timing measures for the predicate and the object. This appears to confirm the significance of the verb for processing Hebrew sentences (Leikin & Breznitz, 1999). Furthermore, in the present study, unlike in Leikin (2002), the paradigm included one-third more of the experimental stimuli, and the stimuli (the sentences) were easier and clearer from a grammatical point of view. Region x grammatical role x group interactions revealed higher 600 amplitudes in the Russian L1 group than in the Hebrew L1 group. This may suggest that syntactic processing for the Russian L1 group required greater effort for the same task in their native language than it did for Hebrew L1 speakers. Less effortful syntactic processing may be an indication of more natural and more language-directed processing. We suggest therefore that changes in ERP amplitudes and latencies in Hebrew did not relate to ordinal word position and wordclass differences between target words but were associated with the grammatical functions of the words, whereas in Russian the grammatical functions of the words played a less prominent role. Finally, note that the between-group comparison of reading in Hebrew revealed considerable differences in processing measures and brain localization. Recent studies, which investigated morphological and syntactic processing in adult native and non-native speakers who acquired their L2 after childhood, showed that grammatical processing in L2 was fundamentally different from that in one’s native language (see Clahsen & Felser, 2006b for a review). A recent study found that, although participants showed bidirectional lexical transfer, they displayed only L1-to-L2 grammatical transfer (Hohenstein et al., 2006). To account for the observed L1/L2 differences in processing, Clahsen and Felser (2006b) proposed the shallow structure hypothesis (SSH), according to which the representations that adult L2 learners produce during

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processing contain less syntactic detail than those of native speakers. In turn, adult L2 learners were seen to rely more on lexical–semantic cues for interpretation during sentence processing. As the N400 is believed to index lexical– semantic processing, the fact that L2 (Russian/Hebrew) speakers in our study showed N400 and P600 responses is fully consistent with SSH. The differences found between native Hebrew speakers and native Russian speakers reading in Hebrew are also with SSH. Acknowledgement This work has been supported by the Israel Scientific Foundation (ISF), grant (9812).

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