Perspectives on Formulaic Language: Acquisition and Communication

Perspectives on Formulaic Language: Acquisition and Communication

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Perspectives on Formulaic Language Acquisition and Communication

Edited by David Wood

Continuum International Publishing Group The Tower Building 80 Maiden Lane 11 York Road Suite 704 London SE1 7NX New York, NY 10038 www.continuumbooks.com © David Wood and contributors 2010 All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage or retrieval system, without prior permission in writing from the publishers. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. ISBN:

978-1-4411-5047-9 (Hardback)

Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress.

Typeset by Newgen Imaging Systems Pvt Ltd, Chennai, India Printed and bound in Great Britain by the MPG Books Group

Contents

Notes on Contributors Acknowledgements 1. Formulaicity and Usage-based Language: Linguistic, Psycholinguistic and Acquisitional Manifestations Regina Weinert

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Part 1: Formulaic Language in Acquisition and Pedagogy 2. The Development of Collocation Use in Academic Texts by Advanced L2 Learners: A Multiple Case Study Approach Jie Li and Norbert Schmitt

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3. Idiomatically Speaking: Effects of Task Variation on Formulaic Language in Highly Proficient Users of L2 French and Spanish Fanny Forsberg and Lars Fant

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4. Effectiveness of Text Memorization in EFL Learning of Chinese Students Zhenqiong Dai and Yanren Ding

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5. Lexical Clusters in an EAP Textbook Corpus David Wood 6. An Investigation of Lexical Bundles in ESP Textbooks and Electrical Engineering Introductory Textbooks Lin Chen

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Part 2 : Identification and Psycholinguistic Processing of Formulaic Language 7. Formulaicity in Code-switching: Criteria for Identifying Formulaic Sequences Kazuhiko Namba 8. Holistic Processing of Regular Four-word Sequences: A Behavioural and ERP Study of the Effects of Structure, Frequency, and Probability on Immediate Free Recall Antoine Tremblay and Harald Baayen

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Contents

9. The Phonology of Formulaic Sequences: A Review Phoebe Ming Sum Lin 10. Processing MWUs: Are MWU Subtypes Psycholinguistically Real? Georgie Columbus

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Part 3: Communicative Functions of Formulaic Language 11. A Text in Speech’s Clothing: Discovering Specific Functions of Formulaic Expressions in Beowulf and Blogs Matt Garley, Benjamin Slade, and Marina Terkourafi 12. The Semantic Structure of Arabic Idioms Ashraf Abdou

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13. Formulaicity and Translation: A Cross-corpora Analysis of English Formulaic Binomials and Their Italian Translations Salvatore Giammarresi

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Index

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Notes on Contributors

Ashraf Abdou has obtained degrees in Arabic language and Islamic studies and in Linguistics from Cairo University. He also has an MA in Teaching Arabic as a Foreign Language from The American University in Cairo, and a PhD in Linguistics from the University of Manchester, where his dissertation was a corpus-based study of Arabic idioms. His teaching experience includes Arabic linguistics and Arabic as a foreign language at these three universities. Harald Baayen is a Professor at the Department of Linguistics at the University of Alberta. His research interests include quantitative linguistics, lexical statistics, exploratory data analysis, stylometry, mixed-effects modeling, morphology and morphological processing. Lin Chen worked as an electrical engineer for eight years in China before beginning her graduate studies in applied linguistics at Carleton University, where she is now a lecturer in English for Academic Purposes. Her research interests include formulaic language, corpus linguistics, and discourse analysis. Georgie Columbus is a phraseologist working in corpus linguistics and psycholinguistics. Her secondary interests lie in the variation in discourse markers between English varieties. Georgie is currently researching at the University of Alberta, Canada, on the processing of multiword units in native and non-native speakers. Yanren Ding is Professor of English, School of Foreign Studies, Nanjing University. His research interests include second language acquisition, discourse analysis and language teaching methodology. Lars Fant is a Professor in the department of Spanish and Portuguese at Stockholm University. He has taught Romance languages in a wide variety of contexts, and has researched and published on many aspects of second

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language use including cross-cultural communication, discourse analysis and pragmatics, and formulaic language. Zhenqiong Dai is an English instructor, School of Foreign Studies, Nanjing University. Her research and teaching interests centre around formulaic language and the role of memorization in language acquisition. Her article in this volume, co-authored with Yanren Ding, is based on her graduate work. Fanny Forsberg is a researcher and lecturer in French at Stockholm University’s department of French, Italian and Classical Languages. She has researched and published extensively on formulaic language and high-level proficiency in second language use. Matt Garley is a PhD candidate in Linguistics at the University of Illinois at Urbana-Champaign, where he serves as editor of Studies in the Linguistic Sciences. His research interests include sociolinguistics, language contact, the language of hip-hop, and computer-mediated communication. He is currently planning a dissertation project on linguistic borrowings and the construction of identity in the German hip-hop fan community. Salvatore Giammarresi holds a PhD in Synchronic and Diachronic Linguistics from the University of Palermo, Italy. He is the site creator and moderator of the Formulaic Language Research Network (www.eflarn.ning. com). His academic interests include formulaicity, translation technology, translation theory and localization. He is a lecturer at the University of Palermo, Italy, teaching localization, computer assisted translation tools and global marketing. Professionally Salvatore is currently serving as the Vice President of Products at a web-based company in San Francisco. Jie Li is a PhD student at the University of Nottingham. Her academic interests include vocabulary learning and teaching, formulaic language, corpus linguistics, and foreign/second language acquisition. Her thesis focuses on second language (L2) learner acquisition and use of formulaic language in academic writing. She has recently published an article on Chinese advanced L2 learner’s acquisition process of lexical phrases in the Journal of Second Language Writing. Phoebe Ming Sun Lin is a researcher at the School of English Studies of the University of Nottingham, UK. At the time of writing, she is completing

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a large study which provides a comprehensive description of the prosody of formulaic sequences. Her recent publications explore formulaic language from the perspectives of phonology, corpus linguistics and second language teaching and learning. Her wider research interests include formulaic language, intonation, corpus linguistics and spoken English. Kazuhiko Namba is Associate Professor of Applied Linguistics at Kyoto Sangyo University. His main research interest is the role of formulaic language in bilingual children’s language acquisition and the structural aspects of code-switching. He acquired his PhD and MA at Cardiff University. He taught English in Japanese secondary schools for over 20 years and is raising his two children as English-Japanese bilinguals. Norbert Schmitt is Professor of Applied Linguistics at the University of Nottingham. He is interested in all aspects of second language vocabulary, including vocabulary acquisition, formulaic language, vocabulary testing, the relationship between reading and listening and vocabulary learning, and implicit and explicit vocabulary knowledge. He has most recently completed a vocabulary research manual, to be published by Palgrave Press. Benjamin Slade is a PhD student at the University of Illinois, currently preparing a dissertation on the history of Sinhala interrogative constructions under the direction of Hans Henrich Hock. His earlier work was on the development of do-support in English and the evolution of Indo-Aryan compound verbs. Forthcoming work includes a study of dragon-slaying formulae in early Indo-European, to appear in Historische Sprachforschung. Antoine Tremblay obtained his BA in Hispanic Studies and MA in Spanish Morphology from Laval University, Quebec, Canada, and his PhD in Psycholinguistics from the University of Alberta, Edmonton, Canada. He is currently a postdoctoral fellow at Georgetown University Medical Center, Washington DC, in the Department of Neuroscience. His research focuses on the processing of compositional multi-word sequences in the auditory and visual modalities using behavioral and brain imaging methods. Marina Terkourafi is Assistant Professor in Linguistics, University of Illinois at Urbana-Champaign. She has research interests in post-Gricean pragmatics, theories of (im)politeness, language contact and change, language and ideology, and construction grammar(s). Her work in these areas has appeared in journals such as Cognition & Emotion, Diachronica, Journal of

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Historical Pragmatics, Journal of Pragmatics, The Journal of Politeness Research, and Journal of Greek Linguistics, as well as in edited collections. Regina Weinert is Reader in Germanic Linguistics at the University of Sheffield. Her main research interests are syntax and discourse-pragmatics, especially of spoken language, and usage-based approaches to language and language acquisition. Her work includes the analysis of clauses, clause complexes, focusing constructions, particles and pronouns, with an emphasis on German and English.

Acknowledgements

The editor wishes to acknowledge the support and inspiration of colleagues, mentors and friends in the development and realization of this project. Sincere thanks and appreciation go to Ito Harumi and the faculty in the Department of English at Naruto University of Education, in Tokushima, Japan. As well, special thanks to colleagues at Carleton University – Ellen Cray, Randall Gess. Mentors from the past, Mari Wesche and T. S. Paribakht at the University of Ottawa also deserve lasting gratitude. Those who have contributed to the building of the study of formulaic language are numerous, but Alison Wray, John Sinclair, A. P. Cowie, Andrew Pawley, Norbert Schmitt are among those who have made history. Additional thanks to the positive constants in my life, Jeremy Chee, Beryl Wood, and Deborah Wood-Salter and Donald Wood and their families. A round of applause goes to the contributors to this volume, who have done so much to further our knowledge of formulaic language and its vital role in language acquisition and in communication.

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Chapter 1

Formulaicity and Usage-based Language: Linguistic, Psycholinguistic and Acquisitional Manifestations Regina Weinert University of Sheffield

Introduction A single chapter cannot do justice to the myriad approaches and the detail of studies into formulaic language and usage-based accounts of language and language acquisition, which is a sure sign of a flourishing field of enquiry. The various strands also speak for themselves in this volume. What a synthetic chapter can demonstrate is that formulaicity and the close relationship between language use and language representation are now central concerns in the study of language, evident in a cluster of booklength publications and dozens of articles in the last ten years. Questions which I raised in Weinert (1995) and associated methodological challenges are being tackled vigorously with a wide range of tools, while some answers remain elusive. My own work has since focused on the syntax and discoursepragmatics of spoken language and the implications for linguistic theory, arguing for a usage-based approach. This chapter sets out some of the key arguments and findings in work on formulaic and usage-based language as well as highlighting issues for further research.

Formulaic Language and Usage-based Language As a non-technical term, the English word formulaic connotes a lack of originality and stasis in cultural or language expression, witness three recent examples from online reviews of literature, music and film: Renowned author Dan Brown staggered through his formulaic opening sentence; Kronos becoming formulaic; Mummy 3 was formulaic, corny, and predictable. Similarly, in linguistic

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traditions which place generative, syntactic rules at the centre of theories and inquiries, formulaic and also irregular language becomes a marginal or at best separate phenomenon and rule-governed, created language is accorded central, and often by implication a high status, considered to be indicative of the sophistication reached by human language (e.g. Pinker & Prince, 1991; Pinker, 1994). Wray (2002) was the first book-length treatment which gathered phenomena considered formulaic in adult language, first and second language acquisition and in language disorders, adopting an open-door policy and dispelling the notion that they are marginal in native language. Anyone looking for orientation in the field will find this and her subsequent book, Wray (2008), the most comprehensive guides. Wray (2002, p. 9) sets out to shed the baggage and associations of the label formulaic language accumulated through previous linguistic literature and to clear a path through the fifty or more alternative terms. She defines a formulaic sequence as follows: ‘ a sequence, continuous or discontinuous, of words or other elements, which is, or appears to be, prefabricated: that is, stored and retrieved whole from memory at the time of use, rather than being subject to generation or analysis by the language grammar.’ Subsequently Wray reserves the term formulaic sequence for her particular, theory-sensitive definition. The term formulaic language reappears as a ‘neutral mass (uncountable) noun’, including in the titles of her books, and formula ‘is used as the neutral count noun’ (Wray, 2008, p. 8). Most recent studies converge on the label formulaic as an umbrella term and refer to specific manifestations of the phenomenon with additional labels. These manifestations include (oral) narratives, prayers, proverbs, social routines, noncompositional idioms, (more or less) transparent idioms, collocations, lexical bundles, sentence stems, complex word forms, frequently used sequences of words and clauses, fixed sequences, sequences with open slots which can be filled subject to varying levels of constraints, community-wide sequences and idiosynchratic sequences. Studying formulaic language essentially involves two related tasks, data or corpus-based analysis and (psycholinguistic) experimentation, with both approaches also benefiting from being tied to theoretical argumentation. The first task is to uncover the extent and nature of formulaic language in healthy and impaired adult language use and in L1 and L2 acquisition. Computer searches of corpus data readily reveal the pervasiveness of re-current and co-occurrent word or other unit combinations. Yet selecting relevant sequences for analysis and interpreting and applying such findings requires a model of language and its psycholinguistic verification. The second task then is fraught with difficulties. Accounts of formulaic language do not only point to the

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phenomenon as a linguistic one, they assume or suggest that formulaic sequences are processed and produced as wholes, that is as single units, rather than being analysed or generated. This is said not only to apply to non-compositional language such as opaque idioms, but potentially also to sequences which can in principle be analysed. Formulaic language has tended to be examined as an aspect of the lexicon, and the obvious link to the extensive research under the label phraseology has helped to give it a coherent and substantial body of research. Wray (2002, p. 263) proposes the heteromorphic distributed lexicon, which contains different types of formulaic sequences, including sequences which at the level of the magna-language could be represented in terms of more general patterns or rules. Wray (2008, pp. 33–34) states that in her model the notion of formulaic language disappears as such. The heteromorphic lexicon contains simple as well as complex units which may be quite large and novelty lies in their combination, whether this involves many rules or simple selection from a small set of items. As Wray says herself, the specific characteristics of the units are nevertheless of major interest. However, there is a further point. While formulaic sequences are per definition ‘stored and retrieved whole’, they also per definition contain more than one unit and hence the issue of their internal structure arises, of patterns and of boundaries. Psycholinguistic verification is therefore also still necessary. One drawback of placing formulaic language within the lexicon, even if only metaphorically (Wray, 2008, p. 77), is the separation from syntax. While morphology naturally enters the arena through the inclusion of MEUs, that is, morphologically complex words may be formulaic and/or rule-generated, and while much of formulaic language is of limited generalisability, all kinds of combinatory phenomena are being studied within usage-based language models. It is in this context that the notion of formulaic language may also well disappear, that is, once a model of language uncovers and validates multiple levels of abstraction and representation. Formulaic language can in principle take its place in usage-based theories of language and is naturally aligned with such models since there is no claim or expectation of maximal analycity and minimal representation (e.g. Barlow & Kemmer, 2000; Bybee, 2006). Here we get, potentially, simple and complex forms, general rules, rules of limited generalisability, patterns with open slots, fixed expressions, multiple levels of categorisation and representation, particular exemplars, community wide sequences, and individual language users’ sequences. We get effects of locality, frequency, salience and recency, a relationship between sequentiality and hierarchical constituency, bi-directionality (from wholes to components, from components

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to wholes), interaction (rather than a hierarchy) between phonology, lexis, syntax, semantics and pragmatics and we get dynamism. We get what Langacker calls ‘a sea of particularity’ (Langacker, 1987, p. 46.). In addition, cognitive, usage-based approaches such as Langacker (2000) not only reflect the immense complexities of linguistic structure, they posit a unified account of cognition built on basic psychological principles, in preference to a dual-mechanism account which acknowledges the pervasiveness of irregularity but still goes exclusively for compositionality and rules wherever patterns can be discerned. Both written and spoken language can be characterized along usagebased lines and formulaicity has been demonstrated for a variety of written texts, yet it is in spontaneous spoken language that performance factors may be seen to relate more directly to linguistic form. Spontaneous spoken language is subject to processing and production constraints which are very different for much of written language. Furthermore, spoken language is primary in humans. The concept of formulaicity and usage-based models therefore become especially pertinent, given that they include both a linguistic as well as a psycholinguistic component. What then is the evidence of formulaic and usage-based language and how can they be characterized?

Memory and Analysis

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The cognitive unity of formulaic sequences and the usage-based nature of grammar are explained in terms of a greater memory than processing capacity of the human brain, in terms of size versus speed (e.g. Weismer, 2004). Dabrowska (2004a) compares the human brain with a desktop computer, the latter processing at a rate a million times faster than the former. The question is, what would be achievable with the human capacity for neurons to fire about 200 times per second, with their vast number and the connections between them? de Bot (1992) calculates that speakers typically have to make a word choice decision two to five times a second from a store of 30 000 words, which may well be a conservative estimate. One way of meeting this cognitive challenge could therefore be pre-assembly and storage in long-term memory. Sensitivity to frequency is considered an indication of memory storage (the more frequent an item is, the easier it is to access). Yet idioms, especially the classic opaque ones such as kick the bucket, are not necessarily frequent (Moon, 1998). Hence particularity, and/ or irregularity, are also criterial – although irregularity is rarely absolute.

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This includes broad idiomaticity where a particluar function is expressed conventionally by one form rather than the many potential alternatives (the Pawley & Syder ‘puzzle’ (1983)), for example, telling the time as it’s half ten (Scottish English, meaning 10.30). This brings us then to specific methodologies and findings.

Data and Corpus-based Research Corpus analysis has been used extensively to search the limitations in actual language use, manifest in co-occurrence and re-currence, in the substantial work on phraseology, collocation, lexical bundles and so on (e.g. Sinclair, 1991; Stubbs, 1995; Cowie, 1998). Erman and Warren (2000), much cited, estimate that well over 50 per cent of their spoken and written English data is formulaic as opposed to novel. Studies vary greatly in estimates, mostly as an effect of differences in methodology (see Wray, 2002, pp. 28–31 for a discussion), that is, some search for fixed expressions, others have a very low threshold of frequency and sequence length, others again work with a pre-selected list of sequences. ‘Novel’ does not necessarily mean ‘ungenerated’ since a frequently used sequence could in principle still be assembled with rules. Measurements therefore always have to be accompanied by a detailed analysis of the sequences themselves. Wray points out that we also need functionally tagged corpora in order to compute the ratio of formulaic expressions to the total number of times a particular function has been expressed. This approach is common in cross-cultural pragmatic research, although mostly with elicited rather than naturalistic data. For instance, Vollmer and Olshtain (1989) note that German speakers make use of a range of linguistic options for apologizing, with some set phrases. English speakers appear to operate with a more restricted set. Finally, there is the question of how functions could have been expressed, beyond those which actually occur, but this is tricky to investigate since the options are virtually infinite. This question should remain within our vision, however, so that we do not overestimate the power of generation. It would require psycholinguistic experiments, for example, production tasks which deprive speakers of commonly used expressions or comprehension tasks with grammatically possible alternatives which do not commonly occur. Computer searches are revealing interesting patterns within formulaic language, for example, Butler (1998) notes that many fixed formulas are adverbials, and those which allow preceding or following material are often part of nominal or prepositional groups. Garley, Slade and Terkourafi

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(this volume) show that formulaic sequences can serve to characterize different text genres. Attention to local effects is central to usage-based approaches and language users’ representation of language may well also be genre-bound. In addition, the need for examining dense corpora of individual speakers as opposed to cross-speaker corpora is becoming an urgent task in order to test usage-based models, especially of adult native usage. Sequences identified by computer searches may ‘intuitively’ not seem formulaic (e.g. and the) and these are often excluded from studies which attempt to compare formulaic and non-formulaic sequences and/or which compare native versus non-native use of formulaic sequences, for valid reasons (e.g. Underwood, Schmitt, & Galpin, 2004).‘Intuitively not formulaic’ typically means that there is no corresponding meaning/function attached. Yet if chunking is at least partially a processing phenomenon, and if formulaicity, frequency and particularity influence language, then even sequences which do not appear to be tied to a semantic or pragmatic function may still have unitary status. We should therefore not discount them irrevocably. Raupach (1984) is an early study which indicates that some syntactic stems such as what I mean is, I think that are formulae. Wray (2002) notes the potential formulaicity of similar sequences which do not conform to standard constituents in aphasic language (all around the). What counts as formulaic is therefore an empirical issue which links into the issue of formulaicity of syntax and mental representation more generally, to be discussed further below.

Morphology and Syntax

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Invoking formulaicity in morphology and syntax does not imply abandoning the notion of abstraction. But it allows us to re-adjust and re-size some generalizations. Morphology is often seen as a testing ground for dual versus single mechanism models of language and typically involves getting participants to create forms of nonce words, for example, to form plural nouns, past tense verbs and so on. Dabrowska (2004b) provides a tour de force discussion of the two types of models and shows that some of the common examples used in this context do not actually allow one to choose between them. For instance, using the English regular and irregular past tense confounds regularity with other factors such as the high token frequency, the lack of transparency of form and the narrow domains of application in irregular

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verbs as opposed to the regular verbs. Testing native speakers’ productivity with Polish genitive and dative inflections to study the effect of regularity per se, using nonce words, she found that type frequency and phonological heterogeneity were much better predictors of productivity than regularity. In other words, speakers did not operate with maximally productive rules which apply equally across all contexts. Dabrowska argues that these results are consistent with a view of a single mental mechanism dealing with schemas of varying degrees of generality. Formulaicity in syntactic constructions has been claimed for lexicalized sentence stems which have specific discourse functions (Nattinger & de Carrico, 1992), for example, it seems to me, what I’d like to show, it has to be said. Spoken English clefts in particular exhibit some clear patterns of use. Weinert and Miller (1996) showed that the majority of Reverse WH-clefts of the type [NP BE WH-Clause] (that’s what I mean) had in fact deictic cleft heads, the main patterns being that’s what, that is what, that’s where and that is where. Calude (2008) observes a similar trend for Australian English. O’Keefe, McCarthy, & Carter (2007) confirm this for their data and add that most of these clefts can be accounted for by the formula that’s what I + forms of say, tell, mean, think, wonder and want. In German, where Reverse WH-clefts are rare but carry a strong emphatic function, they are equally limited, occurring as das ist x (das) was (‘that is x that what’), for example, das ist genau das was ich immer sage (‘that is exactly that that I always say’). Weinert and Miller (1996) and O’Keeffe et al. (2007) note preferred WHclefts, for example, what I being a frequent opening sequence. Bybee (2002) argues that frequency in sequentiality affects constituency, evidenced by phonological fusions such as wanna, hafta. Some such fusions affect semantically linked items, or traditional constituents, for example, can’t in English or l’ami (’the friend’) in French. Many others do not and seem to ‘violate’ constituency, for example, I’ll, I’m, I’ve, or German hörma(l), sagma(l) [Imperative+Modal Particle] (‘listen’, etc). Halliday and Hasan (1976) suggest that the resulting constituents may then assume a functional unity as the interpersonal ‘Modal Element’ versus the ‘Propositional Element’ of a clause. This does not readily appear to work for other combinations such as [Preposition + Determiner] in German (e.g. zum, im, ‘to the’, ‘in the’), yet their functional status remains to be examined. The unitary status of sequences has further been shown for some expressions in experiments. Sosa and MacFarlane (2002) report that language users find it difficult to identify ‘of’ in sort of and kind of. While semantic unity often seems to match formal unity, frequency effects apparently also hold without a form being tied to a meaning (Saffran, Alsin, & Newport, 1996).

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Even the seemingly most rule-based and flexible syntactic phenomena illustrate boundedness, at least in spoken language. Let us take the examples of noun phrases and of word order in declarative main clause, the most basic and frequent of syntactic units. Miller and Weinert (1998) found that in informal spoken English and German noun phrases exhibit a small range of types and simple structure. Almost 50 per cent of the English noun phrases and over 60 per cent of the German ones are single pronouns. If we add to this the single nouns, ca 64 per cent of English and German NPs contain only one constituent. 16.3 per cent of English and 16.9 per cent of German NPs have the structure [Determiner + Noun]. This means that 80 per cent of NPs are accounted for in terms of Pronoun, Noun and [Determiner + Noun]. The remaining NPs include postmodified NPs (with prepositional phrases and relative clauses), some compound NPs and premodified NPs, but the latter amount to only 3.3 per cent in English and 3.6 per cent in German. The data came mostly from young adults, most of the German speakers had a university education. The question then arises as to the nature of the speaker’s mental representation of what a linguist could analyse as a noun phrase with its various pre- and postmodifying structures. At the very least this invites us to examine the level of abstraction language users operate with. Bybee (2002) sees the noun phrase as showing the strongest signs of being a constituent, based on the frequency with which nouns are preceded or followed by certain items. She suggests that various levels of abstraction are found, from very specific (word level), to partially general (e.g. my + Noun), to more general (Possessive + Noun), to fully general (Determiner + Noun). It could also be that grammatical function preferences affect such categorisations, for example, 80 per cent –90 per cent of German clause-initial pronouns are subjects (Weinert 2007), which brings me to my second example. Word order in main clauses is also a good testing ground for usage-based models, given the frequency and potential for variation inside main clauses (Weinert to appear). German is famously known for allowing virtually any constituent in clause initial position, in contrast to English. The difference is found especially with clause-initial object NPs, which in English are associated with strong focus, for example, to highlight a contrast or emphasize an NP, whereas in German they are mainly associated with thematic information. The distribution of elements in this slot is nevertheless not even. Durrell (2002) refers to an estimate that two thirds of initial elements in German in all registers are subjects. It appears that for spoken German especially we may have to revise the view of an entirely open clause-initial position. An examination of 2000 clause-initial NPs in my data revealed very

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confined usage. 1000 NPs each were taken from private, informal everyday conversations and from public semi-formal discussions and private academic student-lecturer consultations. The picture was strikingly similar for both data sets. Around 80 per cent of clause-initial NPs are pro-forms; of these ca 64 per cent are single pronouns and 16 per cent are deictic adverbs such as da and dann (‘there’ and ‘then’). Only ca 8 per cent are lexical adverbs and ca 12 per cent are full noun phrases. If we look only at noun phrases we find that ca 85 per cent are pronouns (compared with the figure of 60 per cent for all noun phrases referred to above in the section on noun phrases). In the informal data, 13.5 per cent are object NPs and in the formal data 9.7 per cent are object NPs (with one dative object, the others accusative in each data set; also included are 10 cases of dative mir (8 in the formal data) in constructions such as mir scheint (‘it seems to me’). To sum up, main clause initial NPs are 85 per cent pronouns and of these 90 per cent are subjects. Taking all clause-initial elements into account, 80 per cent are pro-forms, 64 per cent of these pronouns, the rest mostly da and dann. The similarity between the two data sets is rather surprising, especially given that in the formal data the noun phrases in other clause positions are much more complex. Again the question is, what type of word order generalizations do language users operate with? While the details remain to be investigated, in spontaneous spoken German an open rule for clause-initial position would seem rather too powerful, both for linguists as well as for language users.

Psycholinguistic Reality There is then plenty of surface linguistic evidence of formulaicity and constrained usage, that is, of limited distribution across constructions, even in the potentially most flexible and general ones such as noun phrases and main clauses. Some evidence of an accompanying psycholinguistic effect comes from the ‘fusion’ effects mentioned above, where phonological alternations, mostly reductions, and accompanying orthographic alternations (would of for would have) indicate that sequences are no longer subject to analysis. Usage-based effects have been shown by work on Polish nonce words, which suggest that morphological rules may well be local rather than maximally abstract and regular. The evidence regarding the processing of formulaic sequences and of their advantage over non-formulaic sequences is more sparse, not surprisingly, given how difficult this is to examine. Van Lancker, Canter, & Teerbeek, (1981) report that in a production task

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speakers inserted longer pauses between the words of literal versus metaphorical interpretations of idioms such as he was skating on thin ice. But work on idioms is inconclusive and regularly suggests that there is no difference in comprehension speed between literal and metaphorical interpretations (Gibbs, 1985), or between idioms and literal paraphrases (Gibbs, Bogadanovich, Sykes, & Barr, 1997). Schmitt, Grandage, & Adolphs (2004) remind us that corpus-derived recurrent clusters are not necessarily psycholinguistically real. Conversely, as pointed out above, corpus-based analysis may discard formulae which are psycholinguistically real. A lack of processing difference (whatever the method) does not necessarily mean that formulaic and non-formulaic sequences are not processed differently, we may simply be considering the wrong sequences. The pre-selection of formulaic sequences is far from straightforward. Namba (this volume) tackles the issue of identification with a complex set of diagnostic criteria and Lin (this volume) refines the examination of phonological coherence as an indicator of formulaicity. Most processing studies rely on measuring participants’ production speed or reaction times on pre-selected sequences. Bod (to appear) for instance, compared frequently used clauses such as I like it with less frequent ones such as I keep it. He found that native participants were able to decide more quickly that a sequence was a possible English sequence when it was a more frequent one. Columbus (this volume) provides some evidence for non-semantic, non-constituent sequences such as at the end of the being processed faster than ‘compositional’ [their label] control sequences such as to eat a sandwich. How any such frequent, apparently compositional and non-constituent sequences are processed is still an open question. Conklin and Schmitt (2008) used formulaic sequences whose initial elements made later ones highly predictable, for example, [beauty is in the] [eye of the beholder], verified by means of cloze tests on native speakers. A self-paced line-by-line reading task found that such formulaic sequences were read more quickly than non-formulaic ones. The value of self-paced reading is that it can potentially tap the representation of individual words or items in a sequence, which is precisely what is needed. Schmitt and Underwood (2004) examined the terminal words of sequences in such a task. They found no difference in reading times between words which occurred in formulaic versus non-formulaic sequences in native speakers, which they attribute partially to the word-by-word presentation or to having to press a space bar, as this may have disrupted the holistic processing. Eye-tracking has been used to show that the final word in a formulaic sequence is fixated less often and for a shorter time than the same final

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word in a non-formulaic sequence in the case of native speakers (Underwood et al., 2004). Speed is certainly a plausible indicator of holistic processing, given the general consensus on the limits to our processing capacity. Tremblay and Baayen (this volume) make a convincing case for level of absolute speed indicating holistic processing and a lack of assembly of four-word sequences (rather than comparative speed between sequences or between native and non-native speakers), based on commonly accepted lexical access speed for single words. In addition, they found evidence of a frequency effect of three-word sequences of words and of single words within the longer sequences, and suggest that multi-word strings are stored as parts as well as wholes. The notion ‘holistic’ becomes further relativized in Columbus (this volume), who teases out differences according to type of multi-word unit. Wray (1992, 2008) alerts us to the possibility that psycholinguistic tests may not tap formulaicity, given clashes in findings between test and non-test situations in clinical investigations. Some of the authentic and spontaneous tasks referred to above address this problem to some extent. Studies which attempt, scrupulously, to develop reliable criteria for identifying formulaic sequences, may in fact be forced into a corner, back to a relatively small group of non-compositional, opaque idioms and possibly phonologically fused items. On the other hand, holistically processed formulaic sequences may be found to exhibit a much greater range – including those based on form, not only on function – once we examine sequences in context and in naturally occurring language, and it is these contexts which may usefully be narrowed and controlled for in studies, rather than just pre-selected sequences. Yet the difficulties in demonstrating that formulaic sequences are processed differently from non-formulaic sequences may not only be a question of methodology. This is where considering formulaicity as an aspect of usage-based language knowledge may throw light on what the issue is. If language knowledge is usage-based then it should not be surprising that it is difficult to find consistent and absolute differences between formulaic and non-formulaic sequences. This is because all sequences will be subject to factors such as frequency, familiarity, recency, and context (e.g. genre, scripts), rules can be local as well as general, there are different levels of abstraction and sequences and units have a potential effect on each other. Just as not every generalization has to occur at the most abstract level, so not every formulaic sequence has to be entirely cast in concrete form. What this means in terms of the internal composition of sequences is not clear. For instance, observed general word frequency effects on the

Perspectives on Formulaic Language

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processing of formulaic sequences may not mean that such words are actually parts within the sequences, they may simply be bumps in the landscape, just as certain parts of words, such as the beginning and end, are more prominent, hence the ‘bathtub effect’ of lexical recall (Aitchson, 1987). Columbus (this volume) also observes non-linear frequency effects. One further intractable issue, which is implied but rarely stated explicitly in studies, is that a mental representation of a whole will in production at least, have to appear in linear order. Prior to being uttered, this whole may not necessarily be of linear form and the nature of the transition also deserves to be studied.

First Language Acquisition

˘

First language acquisition is clearly of immense, central relevance to a theory of language. Usage-based approaches allow for item-based learning and try to chart the relationship between exemplars and rules (e.g. Tomasello, 1992; 2002; 2003; Diessel, 2004; Brandt, Diessel, & Tomasello, 2008). This work regularly comments on children’s use of formulaic language and local schemas, rather than abstract, adult rules (whatever the adult rules may in fact be). Tomasello (1992) very extensively examines the verbs and the structures they occur in for one child from age 15–24 months. The analysis suggests that the child operated with structures associated with particular verbs rather than classes of verbs, that the structures were independent of each other and that recency in the child’s production also played a role. Diessel (2004) proposes how complex syntactic constructions may develop out of exemplars of simple ones, showing again that local restrictions go hand in hand with development, for instance descriptive relative clauses with main clause predicate complement heads or heads of presentational main clauses are the first to appear, which is consistent with the early appearance of such main clauses. Again, at the very least, such findings invite us to rethink where generalizations may be found, what they may be based on or look like. Furthermore, in terms of input, children have been shown to be exposed to highly repetitive lexical frames, for example, utterance initial item-based frames such as what, that, it, there, you and so on (Tomasello, 2002). Dabrowska and Lieven (2005) investigate the development of English syntactic questions, looking at the internal structure of the NPs and VPs, not only the position of the auxiliary and a WH-word. Questions were chosen since they are often seen as evidence of children’s abstract rules,

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13

˘

especially in generative accounts. The children were older, that is, 2 and 3 years of age. Dabrowska and Lieven were able to account for 90 per cent of the children’s utterances with a lexically specific grammar based on the child’s linguistic experience. While their corpus was dense, it still only comprised about 7 per cent of the total of this experience. Experimental study is then also much needed in this area, but this is still relatively sparse (Tomasello, 2000). Extensive work using nonce words has been done on verbs, with some work on morphology (Dabrowska, 2004b; 2006) and is gathering momentum. These studies are highly supportive of the exemplar-based leaning view, at least in young children. Akhtar and Tomasello (1997), Tomasello and Brooks (1999) and Akhtar (1999) found that 2–3.5-year old children do not readily produce or comprehend transitive constructions with novel verbs in terms of patterns abstracted from known verbs and learn about new verbs just in terms of these verbs. Childers and Tomaselleo (2001) found that 2.5-years olds were best at generalizing transitive constructions to new verbs in stabilising frames with pronouns such as he’s VERB-ing it, regardless of their level of familiarity with the verbs. Overgeneneralization on the other hand, often cited as evidence of abstract rules, hardly occurs before age 2.5–3. (Pinker, 1989). Overgeneralization also appears to be favoured by familiarity and constrained by lack of familiarity and the availability of alternatives, that is, it does not apply across all possible structures (Brooks, Tomasello, Lewis, & Dodson, 1999). In addition, previous studies have shown how specific communicative needs or crisis points can lead learners towards analysis, revealing what was previously a unit (Iwamura, 1980, p. 85). Such detailed analysis of communicative situations therefore continues to hold vital clues. The full extent to which first language acquisition involves formulaic sequences is not yet known, although evidence for a substantial role is being put forward. Yet we cannot ignore children’s demonstrated use of simple forms and words and their (own) subsequent construction of two, three, four word utterances. In addition, specific languages also yield different learning tasks. More comparative research with children acquiring languages which differ in terms of formulaicity, regularity and irregularity are needed to show when and how abstraction emerges. At the same time, a theory which links formulaic language to the evolution of language offers an intriguing set of questions (Wray, 2008). But just as we should not assume that once analycity is possible it replaces formulaicity, so it may be premature to suppose that just because formulaicity may have been evolutionary prior, it remains a default ontogenically. ˘

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Perspectives on Formulaic Language

Second Language Acquisition Since the revival of interest in formulaic language in the mid-nineties, studies have examined its role in non-native language as communicative, production and processing, and learning strategy, but not to equal degrees. Myles, Hooper & Mitchell (1998) and Myles, Mitchell, & Hooper (1999) report some evidence for a relationship between formulas and the development of rules among classroom learners and Weinert (1994) notes some classroom-induced negative effects. But most prominent has been the issue of native-like idiomaticity in the broad sense, that is, including non-compositional idioms, collocations and other conventional formmeaning pairings, their development and how learners may be helped towards their use (e.g. Granger, 1998; Howarth, 1998; de Cock, 2000; Schmitt, 2004; Siyanova & Schmitt, 2008; Li & Schmitt and Dai & Ding, this volume). Such work includes comparisons of actual language use with the language of textbooks, for example, complex academic texts have been shown to consist of conventionalized combinations, ranging from discourse organisers to stance bundles and a variety of referential expressions (Chen & Wood, this volume). Research which aims to establish the extent of idiomatic language use among non-natives as well as compare the processing of formulaic sequences in native and non-native language reports both quantitative and qualitative differences between native and non-native speakers, with non-natives generally not operating with the appropriate range and function of formulas or not experiencing the same processing advantage when they do. As I have suggested elsewhere (e.g. Weinert, 1995), the (understandable) aim to develop non-native speakers’ knowledge and use of formulaic language through appropriate teaching may run counter to their own processes. Wray (2002) proposes that post-school and especially adult learners are driven more towards analysis than formulaicity. She sees the difficulty of achieving native-like idiomaticity as arising out of the need to develop strong associations between components, something which is not easy to achieve when faced with their particular social, intellectual and learning experience. One might say that it is difficult to become fully socialized, in a broad sense, a second time around, without the stable linguistic, developmental and motivational environment normally afforded first language learners. Kecskes (2002), adds to this the notion of conceptual socialisation, requiring the development of a common underlying conceptual base for the two languages. A further important aspect which is raised only sporadically is the use of non-native formulaic language, both as a communicative as well as a processing strategy (e.g. Rehbein, 1987;

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Bolander, 1989). Rehbein talks about migrant speakers’ formulae constituting a ‘self-imposed reduction of their own system of needs’. The learner’s lack of native-like formulaic use may also be due to affective variables and an investigation into which areas are particularly associated with a learner’s identity and goals seems timely. Studies into intercultural communication and competence (e.g. Woodin, 2007) have long acknowledged the complexities of development in both conceptual structure and pragmatic conventions, questioning the aim for learners of achieving native command of a second language (indeed an oxymoron). Socialisation research, including in L2 contexts, has become a field of its own (e.g. Kitzinger, 2000; Kasper, 2001).

Society and Culture Wray (2002, 2008) suggests that formulaic language is a mechanism for the promotion of self. This cannot readily be maintained, both as an explanation and as a single motivating factor. Created language can serve the self equally, and this is implied both by the Wray’s NOA (needs of analysis) hypothesis (i.e. there will be times when analysis is needed to promote the self). In addition, Wray herself (2008) points out that the language of esoteric societies may be characterized by a high level of formulaicity, whereas those of exoteric societies may have a lower level. So-called Western societies value originality, creativity and effort of thought, at least in some areas. What type of formulaic language attracts critical responses or prompts novelty is itself an interesting social phenomenon. Taking exception to you know what I mean can express prejudice against Americans, you know may be considered an unnecessary filler indicative of an empty head and refusing to use the phrase push the envelope a vestige of rebellion in an ever more corporate climate of educational establishments. Creative adaptions of the officialese used in the former GDR was considered a sign of subversion and liberation (v. Polenz, 1993). Even in related languages and cultures differences can be observed. This has long been recognized in relation to classic idioms (see also Abdou, this volume) as well as in work on cross-cultural pragmatics, but there are likely to be further, less obvious effects. Forsberg and Fant (this volume) show differences between Chilean Spanish and French in relation to grammatical and discursive versus lexical formulaic sequences, which they see as being related to structural differences between the languages. To what extent cultural differences are implicated in other differences will require

16

Perspectives on Formulaic Language

detailed and sensitive study. In the case of translation (Giammarresi, this volume), this opens up the question of the effect of a change from formulaic to non-formulaic, from the conventional to the novel. Finally, individuals may vary in their attachment to conventions or their thirst for the novel, not only as experience but also as meaningful activity.

Conclusion The relationship between memory and analysis and the conventional and the novel will continue to keep researchers busy in the areas of language acquisition, language use, language representation and processing and as a socio-cultural phenomenon. Three areas in particular seem to me pivotal: the nature of spoken language (child, adult, child-directed, native and non-native), the psycholinguistic status of linguistic units (interpretation of processing speed, unit internal structure, linearity/non-linearity, functionalisation of formal unity, level of abstraction, redundancy in representation, transition from representation to production, production vs. comprehension) and the socio-cultural parameters which influence the level of formulaicity and the balance between convention and novelty (in communities and for individuals, effect on acquisition, implications for translation). Recent research shows a vigorous engagement with the challenges inherent in studying formulaicity and in verifying usage-based accounts of language. In fact, considering formulaic language as an aspect of usage-based language alerts us to the possibility, likelihood even, that we may never find the perfect methodology for demonstrating the difference between formulaic and non-formulaic sequences per se. Instead, as shown by the studies in this volume, fine-grained analyses of formal and functional aspects of re-current and co-occurrent sequences, carried out for a wide range of purposes, are revealing just how immensely complex language use is and how variously language knowledge may be represented. To adapt a friend’s phrase, there is no time to sleep on our bay leaves.

References Aitchison, J. (1987). Words in the mind. Oxford: Basil Blackwell. Akhtar, N. (1999). Acquiring basic word order: Evidence for data-driven learning of syntactic structure. Journal of Child Language, 26, 339–56. Akhtar, N., & Tomasello, M. (1997). Young children’s productivity with word order and verb morphology. Developmental Psychology, 33, 952–65.

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Barlow, M,. & Kemmer, S. (2000). (Eds.), Usage-based models of language. Stanford CA: Centre for the Study of Language and Information. Bod, R. (to appear). Exemplar-based syntax: How to get productivity from examples. The Linguistic Review, Vol. 23, Special Issue on Exemplar-Based Models of Language. Bolander, M. (1989). Prefabs, patterns and rules in interaction? Formulaic speech in adult learners’ L2 Swedish. In K. Hyltenstam & L. Obler (Eds.), Bilingualism across the lifespan: Aspects of acquisition, maturity and loss (pp. 73–86). Cambridge: Cambridge University Press. Brandt, S, Diessel, H., & Tomasello, M. (2008). The acquisition of German relative clauses. Journal of Child Language, 35 (2), 325–48. Brooks, P., Tomasello, M., Lewis, L., & Dodson, K. (1999). Young children’s overgeneralisations with fixed transitivity verbs. Child Development, 70, 1325–37. Butler, C. (1998). Multi-word lexical phenomena in Functional Grammar. Revista Canaria de Estudios Ingleses, 36, 13–36. Bybee, J. (2002). Sequentiality as the basis of constituent structure. In T. Givón & B. F. Malle (Eds.), The evolution of language out of pre-language (pp. 107–34). Amsterdam/Philadelphia: John Benjamins. Bybee, J. (2006). Frequency of use and the organization of language. New York/ Oxford: Oxford University Press. Calude, A. (2008). Demonstrative clefts in spoken English. Doctoral Thesis, University of Auckland. Childers, J. B., & Tomasello, M. (2001). The role of pronouns in young children’s acquisition of the English transitive construction. Developmental Psychology, 37, 739–48. Conklin, K., & Schmitt, N. (2008). Formulaic sequences: Are they processed more quickly that non-formulaic language by native and nonnative speakers? Applied Linguistics, 29 (1), 72–89. Cowie, A. P. (1998), (Ed.). Phraseology: Theory, analysis and application. Oxford: Oxford University Press. Dabrowska, E. (2004a). Language, mind and brain. Edinburgh: Edinburgh University Press. Dabrowska, E. (2004b). Rules or schemas? Evidence from Polish. Language and Cognitive Processes, 19, 225–71. Dabrowska, E. (2006). Low-level schemas or general rules? The role of diminutives in the acquisition of Polish case inflections. Language Sciences, 28, 120–35. Dabrowska, E., & Lieven, E. (2005). Towards a lexically specific grammar of children’s question constructions. Cognitive Linguistics, 16, 437–74. de Bot, K. (1992). A bilingual production model: Levelt’s ‘speaking’ model adapted. Applied Linguistics, 13, 1–25. De Cock, S. (2000). Repetitive phrasal chunkiness and advanced EFL speech and writing. In C. Mair & M. Hundt (Eds.), Corpus linguistics and linguistic theory. (pp. 51–68). Amsterdam: Rodopi. Diessel, H. (2004). The acquisition of complex sentences. Cambridge: Cambridge University Press. Durrell, M. (2002). Hammer’s German grammar and usage. Fourth edition. London: Arnold. ˘

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Erman, B., & Warren, B. (2000). The idiom principle and the open choice principle. Text, 20, 29–62. Gibbs, R. (1985). On the process of understanding idioms. Journal of Psycholinguistic Research, 14 (5), 465–72. Gibbs, R., Bogadanovich, J., Sykes, J., & Barr, D. (1997). Metaphor in idiom comprehension. Journal of Memory and Language, 37, 141–54. Granger, S. (1998). Prefabricated patterns in advanced EFL writing: Collocations and formulae. In A. P. Cowie (Ed.), Phraseology: Theory, analysis and application (pp. 145–60). Oxford: Oxford University Press. Halliday, M. A. K., & Hasan, R. (1976). Cohesion in English. London: Longman. Howarth, P. (1998). The phraseology of learners’ academic writing. In A. P. Cowie (Ed.), Phraseology: Theory, analysis and application (pp. 161–86). Oxford: Oxford University Press. Iwamura, S. G. (1980). The verbal games of pre-school children. London: Croom Helm. Kasper, G. (2001). Four perspectives on L2 pragmatic development. Applied Linguistics, 22 (4), 502–30. Kecskes, I. (2002). Situation-bound utterances in Ll and L2. Berlin: Mouton de Gruyter. Kitzinger, C. (2000). How to resist an idiom. Research on Language and Social Interaction, 33 (2), 121–54. Langacker, R. W. (1987). Foundations of cognitive grammar, Vol 1. Theoretical prerequisites. Stanford, CA: Stanford University Press. Langacker, R. W. (2000). A Dynamic usage-based model. In M. Barlow & S. Kemmer (Eds.), Usage-based models of language (pp. 1–63). Stanford CA: Centre for the Study of Language and Information. Miller, J., & Weinert, R. (1998). Spontaneous spoken language: Syntax and discourse. Oxford: Oxford University Press. Moon, R. (1998). Fixed expressions and idioms in English. Oxford: Clarenden Press. Myles, F., Hooper J., & Mitchell, R. (1998). Rote or rule? Exploring the role of formulaic language in classroom foreign language learning. Language Learning, 48 (3), 223–363. Myles, F., Mitchell, R., & Hooper, J. (1999). Interrogative chunks in French L2. A basis for creative construction? Studies in Second Language Acquisition, 21, 49–80. Nattinger, J. R., & DeCarrico, J. S. (1992). Lexical phrases and language teaching. Oxford: Oxford University Press. O’Keeffe, A., McCarthy M., & Carter, R. (2007). From corpus to classroom: language use and language teaching. Cambridge: Cambridge University Press. Pawley, A., & Syder, F. H. (1983). Two puzzles for linguistic theory: nativelike selection and nativelike fluency. In J. C. Richards & R. W. Schmidt (Eds.), Language and communication (pp. 191–226). New York: Longman. Pinker, S. (1989). Learnability and cognition: The acquisition of verb-argument structure. Cambridge, MA: Harvard University Press. Pinker, S. (1994). The language instinct. Harmondsworth: Allen Lane, Penguin Press. Pinker, S., & Prince, A. (1991). Regular and irregular morphology and the psychological status of rules in grammar. Proceedings of the 17th Annual Meeting of the Berkeley Linguistics Society (pp. 230–51). Berkeley, CA: BLS.

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Raupach, M. (1984). Formulae in second language speech production. In H. Dechert, D. Möhle, & M. Raupach (Eds.), Second language productions (pp. 114–37) Tübingen: Gunter Narr. Rehbein, J. (1987). Multiple formulae. Aspects of Turkish migrant workers’ German in intercultural communication. In K. Knapp et al. (Eds.), Analysing intercultural communication (pp. 215–48). Berlin: Mouton de Gruyter. Saffran, J. R., Alsin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274, 1926–1928. Schmitt, N. (2004). (Ed.) Formulaic sequences: Acquisition, processing and use. Amsterdam/ Philadelphia: John Benjamins. Schmitt, N., Grandage, S., & Adolphs, S. (2004). Are corpus-based recurrent clusters psycholinguistically valid? In N. Schmitt (Ed.), Formulaic sequences: Acquisition, processing and use (pp. 127–51). Amsterdam/Philadelphia: John Benjamins. Schmitt, N., & Underwood, G. (2004). Exploring the processing of formulaic sequences through a self-paced reading task. In N. Schmitt (Ed.), Formulaic sequences: Acquisition, processing and use (pp. 173–72). Amsterdam/Philadelphia: John Benjamins. Sinclair, J. McH. (1991). Corpus, concordance, collocation. Oxford: Oxford University Press. Siyanova, A., & Schmitt, N. (2008). L2 learner production and processing of collocation: A multi-study perspective. Canadian Modern Language Review, 64 (3), 429–58. Sosa, A. V., & MacFarlane, J. (2002). Evidence for frequency-based constituents in the mental lexicon: Collocations involving the word of. Brain and Language, 83 (2), 227–36. Stubbs, M. (1995). Collocations and cultural connotations of common words. Linguistics and Education, 7 (4), 379–90. Tomasello, M. (1992). First verbs: A case study of early grammatical development. Cambridge: Cambridge University Press. Tomasello, M. (2000). Do young children have adult syntactic competence? Cognition, 74, 209–53. Tomasello, M. (2002). The emergence of grammar in early child language. In T. Givón & B. F. Malle (Eds.), The evolution of language out of pre-language (pp. 309–28). Amsterdam/Philadelphia: John Benjamins. Tomasello, M. (2003), Constructing a language. Cambridge, MA and London: Harvard University Press. Tomasello, M., & Brooks, (1999). Early syntactic development: A construction grammar approach. In M. Barrett (Ed.), The development of language (pp. 161–90). Hove: Psychology Press. Underwood, G., Schmitt, N., & Galpin, A. (2004). The eyes have it. An eye-movement study into the processing of formulaic sequences. In N. Schmitt (Ed.), Formulaic sequences: Acquisition, processing and use (pp. 153–72). Amsterdam/Philadelphia: John Benjamins. v. Polenz, P. (1993). Die Sprachrevolte in der DDR im Herbst 1989. Zeitschrift für Germanistische Linguistik, 21, 127–49. Van Lancker, D., Canter, G. J., & Teerbeek, D. (1981). Disambiguation of ditropic sentences: Acoustic and phonetic cues. Journal of Speech and Hearing Research, 24, 330–35.

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Vollmer, H. J., & Ohlstain, E. (1989). The language of apologies in German. In S. Blum-Kulka, J. House, & G. Kasper (Eds.), Cross-cultural pragmatics: Requests and apologies. Norwood: Ablex. Weinert, R. (1994). Some effects of a foreign language classroom on the development of German negation. Applied Linguistics, 15 (1), 76–101. Weinert, R. (1995). The role of formulaic language in second language acquisition: A review. Applied Linguistics, 16 (2), 80–205. Weinert, R. (2007). Demonstrative and personal pronouns in formal and informal conversations. In R. Weinert (Ed.), Spoken Language Pragmatics: An analysis of form-function relations (pp. 1–28). London/New York: Continuum. Weinert, R. (to appear). German free word order – reality or myth? The front-field in spoken main clauses. Weinert, R., & Miller, J. (1996). Cleft constructions in spoken language. Journal of Pragmatics, 25, 173–206. Weismer, S. E. (2004). Memory and processing capacity. In R. M. Kent (Ed.), MIT encyclopedia of communication disorders (pp. 349–52). Cambridge, MA: MIT Press. Woodin, J. (2007). Intercultural positioning: tandem conversations about word meaning. In R. Weinert (Ed.), Spoken Language Pragmatics: An analysis of formfunction relations (pp. 208–28). London/New York: Continuum. Wray, A. (1992). The focusing hypothesis. Amsterdam: John Benjamins. Wray, A. (2002). Formulaic language and the lexicon. Cambridge: Cambridge University Press. Wray, A. (2008). Formulaic language: Pushing the boundaries. Oxford: Oxford University Press.

Part 1

Formulaic Language in Acquisition and Pedagogy

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Chapter 2

The Development of Collocation Use in Academic Texts by Advanced L2 Learners: A Multiple Case Study Approach Jie Li and Norbert Schmitt University of Nottingham

Introduction It is now generally agreed that the native-like use of collocations (word combinations such as heavy smoker, make a speech, bitterly cold) is an important element of proficient language use (e.g. Sinclair, 1991; Wray, 2002). However, researchers have found that L2 learners rely heavily on creativity so as to produce expressions which are simply not used by native speakers (Pawley & Syder, 1983; Wray, 2002). Skehan (1998) and Foster (2001) claim that non-native speakers, unlike native speakers, generate a great proportion of their language from rules instead of lexicalized routines. Native speakers use conventional expressions to convey meaning, while learners often express meaning with unidiomatic combinations of words. A number of studies (Granger, 1998; Howarth, 1998; Nesselhauf, 2003) have shown that even advanced L2 learners often experience problems with collocations in written English. For example, Granger (1998) used a corpus-based approach to look at -ly intensifier + adjective collocations automatically extracted from advanced French learners’ academic essays and similar essays written by native English students. She found that one type of intensifier, that is, ‘boosters’ (e.g. deeply, strongly, highly) were underused by French learners compared with the frequency (i.e. the number of types and tokens) of those used by natives. She then concluded that advanced French learners of English did use collocations, whereas they tended to underuse native-like expressions but overuse those unidiomatic word pairs which have direct L1 translation equivalents. Using a frequency-based statistic approach, Lorenz (1999) also investigated intensifier-adjective collocations in “expository-argumentative” texts

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produced by advanced German learners and native British students. By calculating association measures of collocations and type-token ratios, he found that advanced German learners of English had smaller repertoires of collocations (as measured by type-token ratio) and overused a limited number of high frequency collocations (as measured by t-score and MI). Building on Lorenz’s statistical approach, one of Siyanova and Schmitt’s (2008) three studies used corpus-based frequency data and mutual information statistics (MI) to investigate adjective-noun collocations in advanced Russian learners’ and native university students’ written English. By consulting the BNC for counting frequency and calculating the MI value of each collocation, they found that only 45 per cent of the collocations used by advanced Russian learners in their writing texts were appropriate (i.e. frequent and strongly associated English word combinations). Following a phraseological approach, Howarth (1998) focused on restricted verb-noun collocations (e.g. make a claim, reach a conclusion) identified from native and advanced non-native academic written corpora. Based on the norms established in native speaker writing, he reported that advanced non-native MA students employed about 50 per cent fewer restricted collocations than natives. He also found that approximately 6 per cent of collocations produced by advanced learners are non-conventional. Based on Howarth’s analysis, it seems that among the three collocational groups (i.e. restricted collocations, free collocations, and idioms), restricted collocations are most problematic for advanced non-native learners. Another more comprehensive study which explored advanced German speaking learners’ verb-noun collocation (e.g. take a break, shake one’s head) is that of Nesselhauf (2003). Like Howarth, she also adopted a phraseological approach and classified collocations into three groups, namely, free combinations (e.g. want a car), collocations (e.g. take a picture) and idioms (e.g. sweeten the pill). She found that learners made the greatest proportion of errors with collocations (79 per cent), followed by free combinations (23 per cent) and idioms (23 per cent). As can be seen, the existing studies all used a corpus-based native versus non-native comparison to investigate learners’ collocation use and identify gaps between these two populations. In general, three main approaches have been employed to define and identify collocations in written texts. One has studied all word combinations of a particular grammatical form (e.g. –ly amplifier + adjective), regardless of whether they are ‘idiomatic’ or not (Granger, 1998). A second is the so-called phraseological approach, represented by Howarth (1998) and Nesselhauf (2003, 2005). Borrowing the Russian School’s definition and classification of phraseology (Cowie,

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1998), collocations are typically identified according to two defining criteria: semantic opacity – the degree to which words are used with their ‘dictionary’ meanings, and fixedness – the degree to which elements of a phrase can be substituted. A final approach uses occurrence frequency of word combinations within the investigated corpus as identification criteria. Thus, Lorenz (1999) and Siyanova and Schmitt (2008) compared word pairs in non-native and native equivalent corpora and used statistical ‘association measures’ to identify which pairs were characteristically idiomatic. Although different approaches have been employed to identify and define collocations, they point to the same conclusion: L2 learners have difficulties with collocation use in their language production. However, existing studies have largely been descriptive in nature, and tend to focus on one-off compositions produced by learners. Little research has focused on an empirical analysis of L2 learners’ collocations over time, which could inform about how collocational knowledge develops. A small number of longitudinal studies have been undertaken to investigate the role of formulaic language improvement in young L2 learners’ language acquisition (e.g. Wong-Fillmore, 1976; Huang & Hatch, 1978). Apart from Adolphs and Durow’s (2004) longitudinal study of two L2 postgraduates’ three-word formulaic language improvement in spoken English, few studies have done the same for advanced L2 learners’ improvement of formulaic language. The only truly reliable way to identify patterns of development in the use of collocations by L2 learners is to conduct longitudinal studies of the same learners over time. This study attempts to do this using a multiple case-study approach. The purpose is to provide a rich and detailed description of several individual learners’ use of collocations over a period of one academic year. We are also interested in how the individual results combine into group results. As our goal is descriptive, we begin with no formal research questions. However, the following general questions helped to focus the investigation: 1. Will advanced Chinese L2 learners improve their collocation use in academic writing assignments over a one-year study abroad postgraduate programme? Are the collocations used by Chinese students similar to those used by published authors? 2. Are the statistical measures of collocations we use valid for the investigation of collocation improvement over an academic year? To what extent we can put our faith in the statistical results of group patterns of collocation development?

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Methodology Participants The four participants were female Chinese postgraduates, on a one-year MA programme in English Language Teaching (here after ELT) in the School of Education at the University of Nottingham. All of them were English majors from China, with ages ranging from 26 to 29. Their English language learning experiences in China were similar in that their exposure to target language was mainly from non-native teacher-dominated classroom instruction, which was generally grammar-based and input-poor. The participants had similar career plans and expectations, namely returning to China to start teaching in colleges or universities. Overall, the four participants were advanced English language learners, who received similar English language training in China, and were exposed to the same L2 environment at a British university. Details of the individual participants are shown in Table 2.1 as follows: Table 2.1

Participant’s Personal Details

Participant Age Education background Teaching experience IELTS/TOEFL score LH

29

Technical College

5 years

6.5, Writing: 6.0

TT

26

Bachelor’s Degree

4 years

640 (TOEFL), Writing: 5.5

WL

27

Technical College

5 years

6.5, Writing: 6.0

YJ

27

Bachelor’s Degree

5 years

6.5, Writing: 6.0

Since the scores of IELTS and TOEFL are not directly comparable, it is impossible to compare TT’s English language competence to the other three participants. Nevertheless, similar to the other members of the participant group, she is a proficient English language user on the basis of her TOEFL marks.

The learner corpus The learner corpus consisted of 36 academic writing assignments (including eight essays and one dissertation for each participant) written over a period of one academic year (i.e. three terms). Since the four participants are all from the one-year MA programme in ELT, their writing requirements were the same except for the coursework for elective modules. This MA course is

Collocation Use in Academic Texts

27

comprised of two core modules: Applied Linguistics and Syllabus Design & Methodology; four elective modules and a final dissertation requirement. Each module requires a 3,000 word essay for coursework apart from core modules, which require 6,000 words (i.e. two essays of 3,000 words each). The word count requirement for the dissertation in Term 3 is 12,000 words. Overall, each participant is required to produce 12,000 words in each of three terms over the course of 12 months. Developing the corpus involved collecting each text in electronic form, cleaning it (i.e. removing unnecessary parts: titles, headers, footers, captions, and reference list), and categorizing it according to the term it was written. The resulting corpus contained 149,587 running words (tokens) and 7,259 types, which was divided into three subcorpora: Term 1 – 50,376 running tokens, Term 2 – 48,530, and Term 3 – 50,681. The three subcorpora are, therefore, directly comparable in terms of text length and text style.

The BNC academic written corpus The academic written sub-set of the BNC World Edition (2000) was used as the ‘proficient writer’ comparison corpus. It consists of 501 texts totaling over 16 million words, selected from books and journal articles in the six disciplines proposed by Lee (2001): humanities/arts, medicine, natural science, politics/law/education, technical/engineering, and social science.

Procedure All adjective-noun combinations were extracted from the learner corpus in the following manner. The corpus was searched for the 187 nouns from Sublist 1 of Coxhead’s (2000) Academic Word List (AWL), and those selected which were used by at least one participant over time (at least in two of the three terms). Then WordSmith 5.0 was used to locate adjacent adjective collocates for each of these recurring academic nouns. Collocations were excluded from analysis if they included one of the following constituents: hyphenated adjectives (e.g. corpus-based approach), pronouns, possessives, determiners, numbers/ordinals, adjectives to signify nationalities (e.g. Chinese, English), and terminology (e.g. Lexical Approach, Universal Grammar). This selection procedure produced 41 nouns, leading to 147 different adjective-noun collocation types in Term 1, 95 in Term 2, and 107 in Term 3, a total of 494 collocation tokens and 299 collocation types.

28

Perspectives on Formulaic Language

The number of collocate types (i.e. different collocations) and tokens (i.e. occurrences of each type) produced by each participant across terms was counted and recorded. For example, the node noun role was used with different adjectives by participant WL in her academic texts across three terms, that is, important in Term 1, central in Term 2, and key, potential, critical, significant in Term 3. Based on these frequency counts, the type-token ratio (TTR) of each collocation type was calculated for all of the four participants. The t-score and MI value for each collocation type was also calculated. Since it is claimed that low-frequency collocations jeopardize the reliability of all association measures (Manning & Schütze, 1999; Evert & Krenn, 2001), all the extracted collocations with less than four occurrences in the BNC academic corpus were excluded from MI and t-score calculations. Various researchers define their cut-off points differently: Manning and Schütze (1999) suggest a minimum of three occurrences; Stubbs (2001) five occurrences; Church and Hanks (1990) five occurrences. We used a cut-off point of four to include as large a set of learner collocations as possible. To explore the four participants’ collocational development pattern over the period of 12 months, the TTR, t-score, and MI values for each participant were then averaged within each term and these averages compared across terms. Finally, to explore the development of the strongly-associated collocations preferred by expert writers, the adjective-noun collocations were ranked into different bands according to their MI values.

Results The value of case-studies is the elicitation and analysis of rich data, and so we will report both the group results and the results of each individual participant.

Participants’ overall collocation use Group 494 adjective-noun collocation tokens were identified from the learner corpus, made up of 299 types. Of these 299 types, over 40 per cent can be considered frequent and strongly-associated (which we will term robust in this section), at least according to the criteria of appearing four or more

Collocation Use in Academic Texts Table 2.2

29

Participant Group’s Overall Collocation Use

Adjective-noun Tokens Types Tokens Types Tokens Types Tokens Types collocations (total) (total) (Term 1) (Term 1) (Term 2) (Term 2) (Term 3) (Term 3) F<4

143

128

65

62

35

33

43

38

F≥4 & MI>3 & t-score>2

283

123

112

67

81

42

90

54

Total

494

299

198

147

142

95

154

107

% of robust collocations

57.3

41.1

56.6

45.6

57.0

44.2

58.4

50.5

times in the 16 million-word BNC academic subcorpus and having association figures of MI>3 and t-score>2 (Table 2.2). On the other hand, there was a similar percentage of rarely-occurring combinations, that is, appearing less than four times in the BNC subcorpus. However, in terms of instances of use (tokens), the participants used the robust collocations considerably more often than the infrequent ones: TTR of 0.43 for robust collocations in comparison to 0.90 for infrequent ones. On average, each robust collocation type occurred more than twice in the 36 academic writing texts. The table also shows how the participants’ use of robust collocations developed over the academic year. Although the number of types used declined after Term 1, the percentage of robust types used remained essentially the same from Term 1 to Term 2, and then increased slightly by the time the dissertation was written up in Term 3. In terms of tokens, the number of robust collocations used over the three terms showed a similar pattern as that of types, while the percentage of robust tokens only ranged from 56.6 per cent to 58.4 per cent during the academic year, and so was relatively stable. Overall, after the one-year exposure to an English academic environment, it appears that the participant group as a whole displayed little if any improvement in the number of robust adjective-noun collocation types or tokens produced in their academic writing.

Individual participants Although the group results showed little improvement, an analysis of the individual participants’ results shows quite varied behaviors. Table 2.3 shows that although all participants used about 40 different collocation types in Term 1, LH and WL used steadily fewer over the year, while TT dropped in

Perspectives on Formulaic Language

30 Table 2.3

Participants’ Use of Robust Collocations over Three Terms

Participant

Adjective-noun collocation

Term 1 Term 1 (tokens) (types)

Term 2 (tokens)

Term 2 (types)

Term 3 (tokens)

Term 3 (types)

LH

F≥4 & MI>3 & t-score>2

20

17

16

13

9

8

Total

44

40

36

32

32

27

% of robust collocations

45.5

42.5

44.4

40.6

28.1

29.6

F≥4 & MI>3 & t-score>2

18

17

18

12

22

19

Total

43

41

32

22

38

33

% of robust collocations

41.9

41.5

56.3

54.5

57.9

57.6

F≥4 & MI>3 & t-score>2

36

19

20

13

17

11

Total

57

39

29

21

25

17

% of robust collocations

63.2

48.7

69.0

61.9

68.0

64.7

F≥4 & MI>3 & t-score>2

38

28

27

19

42

27

Total

54

43

45

37

59

42

% of robust collocations

70.4

65.1

60.0

51.4

71.2

64.3

TT

WL

YJ

Term 2, but recovered somewhat in Term 3. YJ remained relatively stable in the number of types she used through the year. Regarding the number of collocation tokens used by the four participants across three terms, it displays a rather similar development trend to that of collocation types apart from that of YJ. She tended to use more collocation tokens (59 in Term 3 compared with 54 in Term 1) by the end of the academic year, largely due to frequent repetition (with TTR 0.71 in Term 3, and 0.80 in Term 1). It is also interesting to note the percentage of robust collocations used. In conjunction with her reduced diversity of collocation types/tokens, LH also dropped in the percentage of robust collocations, both types and tokens. Overall, her mastery of these collocations seems to have deteriorated over the year. Conversely, although WL declined in the number of collocation types/tokens used, her percentage of robust collocation types increased over the year, while her percentage of robust collocation tokens reached the peak in Term 2, then dropped slightly in Term 3. She therefore used

Collocation Use in Academic Texts

31

fewer types over time, but a greater percentage of those types were similar to those used by proficient English writers. YJ had a dip in Term 2, but ended up in Term 3 essentially where she began in Term 1, both in number of types and percentage of robust types/tokens. Thus, her usage of collocations was relatively stable over the year. TT also had a dip in numbers of types/tokens produced in Term 2, but her percentage of robust collocations (both types and tokens) steadily increased over the three terms. Overall, her figures indicate gradual improvement in collocation mastery.

Development in the diversity of adjective-noun collocations produced The average number of adjective types used to describe academic nouns provides a general measure of the diversity of adjective-noun collocations produced. The group mean result in Table 2.4 exhibits U-shaped behavior, with the Term 3 figure not recovering to the Term 1 figure. However, this group average does not show the substantial differences between the individual participants. In fact, the group profile only serves to disguise the very

Table 2.4

Average Number of Adjective Types per Noun across Three Terms

2.70 2.50 2.30 2.10 1.90 1.70 1.50 Term 1

Term 2

Term 3

LH

2.00

1.68

1.59

TT

1.67

1.57

1.83

WL

2.60

1.62

1.89

YJ

2.15

2.18

2.33

Mean

2.11

1.76

1.91

32

Perspectives on Formulaic Language

real differences in the participants’ individual development of adjective variation. LH started with an average of two adjective types in the first term of her academic year, followed by a consistent decrease from 1.68 to 1.59 in the next two terms afterward. This continuous decline in the mean number of adjective types over the course of three terms indicates that LH used less diverse adjective-noun collocations (about 20 per cent less) by the end of her study abroad programme. In contrast, participant YJ showed an opposite developmental trend in the use of adjectives to describe academic node nouns in her academic writing tasks over the course of three terms. At the beginning of the academic year, an average of 2.15 adjective types were used. This figure rose to 2.18 and 2.33 respectively in the following two terms. The steady increase suggests that YJ used slightly more diverse (approximately 8.4 per cent more) adjective-noun collocations by the end of her MA course. Both TT and WL experienced a decrease in the number of adjective types from Term 1 to Term 2, and a substantial increase from Term 2 to Term 3, although their developmental profile is very different. WL’s employment of adjective types dropped sharply from 2.6 to 1.62 (about 37.7 per cent less), followed by a substantial rise of nearly 17 per cent from 1.62 to 1.89. This left her using less diversity of adjective-noun collocations over the course of the year. On the other hand, TT initially experienced a slight decline of approximately 6 per cent from 1.67 to 1.57, followed by a rise of 16.6 per cent from 1.57 to 1.83. Unlike WL, by the end of the academic year, TT used more various adjective-noun collocations (9.6 per cent more) compared with those used in Term 1. Changes in the repetition of adjective-noun collocation TTR value can provide indication of the repetition frequency of collocation use. Table 2.5 shows the TTR value of target adjective-noun collocations for each participant and for the participant group as a whole. The TTR pattern for the group shows a rather stable and subtle decline from 0.91 to 0.87 over the academic year. This steady drop in TTR value over time suggests slightly more repetition of collocation by the four participants as a whole. However, as the decrease is less than 4.5 per cent, it is probably not particularly meaningful. Of more interest is the individual behavior, which again varies substantially among the participants. The only participant with a profile which in

Collocation Use in Academic Texts Table 2.5

33

Type-Token Ratios of Adjective-Noun Collocations across Three Terms

1.00

0.95

0.90

0.85

0.80

0.75

Term 1

Term 2

Term 3

LH

0.98

0.94

0.86

TT

0.98

0.81

0.95

WL

0.78

0.90

0.81

YJ

0.89

0.94

0.85

Mean

0.91

0.90

0.87

any way resembles the group profile is LH, and even here the rate of decrease is much more extreme than the group profile. She started with a TTR of 0.98 in Term 1, dropping to 0.94 and 0.86 in Terms 2 and 3 respectively. This steady decline (nearly 12 per cent decrease) in the TTR suggests that LH tended to repeat collocations more often at the end of the academic year. Unlike LH, participant TT’s TTR value underwent a noticeable fluctuation over the course of three terms. Her TTR value began at 0.98 in Term 1, followed by a considerable drop to 0.81 in Term 2, and ending up nearly where she started at 0.95 by the end of her MA course. It is difficult to say what caused the drop in Term 2, other than to note that it was not based on a single aberrant paper, as TT submitted four papers in this term, as did all the participants. Participants WL and YJ share a similar trend, both experiencing a rise of TTR in Term 2, and a drop afterward in Term 3. Overall, WL showed slightly more repetition of collocations than YJ throughout the year.

Perspectives on Formulaic Language

34

Development of high-frequency and typical collocation use We have seen changes in the participants’ diversity and repetition of adjective-noun collocation use, and now focus on their production of the type of collocations frequently used by native professional writers in their academic publications, as measured by the t-score statistic and the BNC Academic reference corpus (Table 2.6). The group result indicates no change in t-score from Term 1 to Term 2 (5.30), and then a slight improvement to 5.44 in Term 3. This suggests that the four participants as a group used more frequent/typical adjective-noun collocations in their dissertations than in their earlier assignments. However, in this case, this profile accurately represents none of the individual participants’ profiles. LH’s average t-score in Term 1 was 5.20, which rose to 5.47 and then dropped to 5.10 in Term 3. Thus, over the year, there was no improvement in LH’s higher-frequency collocation use. It suggests that LH did not use more native-like adjective-noun collocations which are commonly used by professional expert writers in academic texts. WL’s

Table 2.6

T-scores of Adjective-Noun Collocations across Three Terms

6.00 5.90 5.80 5.70 5.60 5.50 5.40 5.30 5.20 5.10 5.00 Term 1

Term 2

Term 3

LH

5.20

5.47

5.10

TT

5.09

5.40

5.68

WL

5.60

5.29

5.94

YJ

5.36

5.05

5.04

Mean

5.31

5.30

5.44

Collocation Use in Academic Texts

35

developmental trend is almost a mirror image of LH’s with t-score averages of 5.60, 5.29 and 5.94 for Terms 1, 2, and 3 respectively. It seems that by the end of the MA programme, when WL wrote up her high-stakes dissertation, she tended to use collocations with higher frequency levels, compared with those used in her earlier assignments. YJ produced a declining profile, dropping from an initial t-score of 5.36 to 5.04/5.05, which indicated a tendency to use adjective-noun collocations which were less frequent and typical by the end of the academic year. Finally, TT produced the type of profile which one might expect given the rich linguistic environment, consistently rising throughout the three terms. She started with an average t-score of 5.09, which thereafter rose to 5.40 and 5.68 in the following two terms. This steady increase suggests that the collocations which occurred in TT’s academic writing assignments over the course of the 12-month postgraduate programme were, generally speaking, increasingly more typical of proficient writers. Development of strongly-associated collocation use Since MI value is known to emphasize a rather different set of collocations from t-score (Schmitt, in press), a similar analysis was carried out using the MI statistic. It highlights collocations which are typically not very frequent, but which are strongly associated when they do occur (e.g. tectonic plates). The group averages (Table 2.7) show a very shallow U-shaped profile, which can probably be best interpreted as no meaningful change across the different terms. But again, the group averages do not accurately represent any of the individual profiles. LH’s collocation use showed a continuous decline in MI values from 4.33 to 3.95 over the course of three terms. This consistent decrease suggests that participant LH tended to use adjective-noun collocations with less association strength in her dissertation, compared with those used in her writing tasks completed in Term 1. By contrast, TT’s collocation use displayed an opposite developmental direction. Her MI averages increased over time (4.51, 4.51, 5.48), which indicates TT’s use of adjective-noun collocation by the end of her study abroad programme was more nativelike, since such strongly-connected collocations characterized the professional writers’ academic texts in the BNC sub-corpus. Although participants WL and YJ underwent completely different developmental trends over the year, they both ended up with lower MI scores in comparison with their initial levels in Term 1. Despite the fluctuations which took place within the length of 12-month postgraduate programme,

Perspectives on Formulaic Language

36 Table 2.7

MI Scores of the Adjective-Noun Collocations across Three Terms

5.60 5.30 5.00 4.70 4.40 4.10 3.80

Term 1

Term 2

Term 3

LH

4.33

4.09

3.95

TT

4.51

4.51

5.48

WL

4.50

4.80

4.46

YJ

5.06

4.42

4.75

Mean

4.60

4.46

4.66

both WL and YJ showed little growth in the employment of adjectivenoun collocations with stronger association strength. This suggests that the collocations used by participants WL and YJ did not become more expert-writer-like after the one-year exposure to the academic target language environment.

Differences in the distribution of collocations according to MI banding In order to investigate the participant group’s collocation patterns in terms of the distribution of strength of association over time, we classified all the adjective-noun collocations used by the four Chinese MA students into five bands on the basis of their MI score values and raw frequency counts obtained from the reference BNC sub-corpus. The MI statistic tends to highlight collocations which are not frequent, but which are highly associated, and are thus likely to be very salient to native speakers (and perhaps proficient non-natives as well). It is thus useful to explore whether the participants began using more of the higher MI collocations, as these may be particularly important in providing a sense of native-likeness to written

Collocation Use in Academic Texts

37

compositions (Durrant & Schmitt, 2009). We use the term ‘non-associated’ to represent those two-word combinations which are either unattested or with raw frequency of below four in the BNC academic texts. (We recognize that these very infrequent combinations may well be associated, but use this terminology in order to clearly differentiate these combinations from our other categories.) ‘Weak-strength collocations’ are those which occur more than four times in the BNC reference corpus with a MI score of less than 3. ‘Moderate-strength collocations’ have MI scores of 3<MI<5, ‘stronger collocations’ have MI strengths of 5<MI<7, and ‘extremely strong collocations’ have MI over 7. (All with frequencies of four or more in the BNC sub-corpus.) When we look at the four participants as a group, the developmental pattern measured by MI values across three terms is shown in Table 2.8. The combined percentage of ‘non-associated’ and ‘weak-strength’ collocation types decreased from nearly 50 per cent in Term 1 to 44.6 per cent in Term 3. This subtle drop indicates that the four participants as a whole used a somewhat lower percentage of less native-like lower-strength collocation types in their academic writing. On the other end of the scale, the participants used only small percentages of ‘extremely strong’ collocation types, and the amount of usage remained about the same over the year. The ratios for both ‘moderate-strength’ and ‘stronger’ collocation categories Table 2.8 Types)

Participant Group’s MI Distribution across Three Terms (Collocation

100.0% 90.0% 80.0% 70.0% MI>7 60.0%

5<MI<7

50.0%

3<MI<5

40.0%

MI<3 Frequency<4

30.0% 20.0% 10.0% 0.0% Term 1

Term 2

MI>7

5.4%

1.9%

Term 3 3.6%

5<MI<7

20.1%

31.9%

24.7%

3<MI<5

24.5%

22.5%

27.0%

MI<3

11.6%

16.9%

12.2%

Frequency<4

38.3%

26.9%

32.4%

Perspectives on Formulaic Language

38

rose slightly from 24.5 per cent to 27 per cent, and from 20.1 per cent to 24.7 per cent respectively. Overall, the group produced slightly less non-associated combinations, and slightly more weak/moderate/stronger strength collocations, although the amount of the most strongly associated collocations (extremely strong collocations) decreased slightly. This group summary can be compared against the individual results. Table 2.9 shows that LH’s combined use of ‘non-associated’ and ‘weakstrength’ collocation types has increased over the course of the academic year, from a total of 57.5 per cent in Term 1 to 70.4 per cent in Term 3. The consistently rising figures indicate that LH used increasingly larger proportions of less strongly associated collocation types over the course of the year. As for those collocations with an MI value of above 3, the drop in percentage of ‘moderate-strength’ collocation types is largely offset by the increase in the ‘stronger’ collocation types, which would suggest some shift towards the use of more strongly associated collocations. However, working against this conclusion is the disappearance of all collocations with an MI over 7. Table 2.9

LH’s MI Distribution across Three Terms (Collocation Types)

100.0% 90.0% 80.0% 70.0% MI>7 60.0%

5<MI<7 3<MI<5

50.0%

MI<3

40.0%

Frequency<4 30.0% 20.0% 10.0% 0.0% Term 1

Term 2

MI>7

5.0%

0.0%

Term 3 0.0%

5<MI<7

10.0%

18.8%

18.5%

3<MI<5

27.5%

21.9%

11.1%

MI<3

10.0%

12.5%

18.5%

Frequency<4

47.5%

46.9%

51.9%

Collocation Use in Academic Texts Table 2.10

39

TT’s MI Distribution across Three Terms (Collocation Types)

100.0% 90.0% 80.0% 70.0% MI>7 60.0%

5<MI<7

50.0%

3<MI<5

40.0%

MI<3 Frequency<4

30.0% 20.0% 10.0% 0.0% Term 1

Term 2

Term 3

MI>7

7.3%

0.0%

12.1%

5<MI<7

14.6%

40.9%

21.2%

3<MI<5

19.5%

22.7%

27.3%

MI<3

14.6%

27.3%

9.1%

Frequency<4

43.9%

9.1%

30.3%

TT’s MI distribution profile is completely different from that of LH. As shown in Table 2.10, TT used a smaller percentage of ‘non-associated’ and ‘weak-strength’ collocation types in her course assignments written up in Terms 2 (36.4 per cent) and 3 (39.4 per cent) compared to Term 1 (58.5 per cent). Over the same period, she used a larger proportion of the ‘extremely strong’ adjective-noun collocation types. The most noticeable feature of the graph is the great increase in ‘stronger collocations’ in Term 2, and then equally dramatic decreases in Term 3. Overall, TT increased in her percentage of collocations with the scores of 3 or above from Term 1 to Term 2, and then remained relatively stable in this regard from Term 2 to Term 3, with just the distribution among the three strongest bands varying. A similar overall summary also describes WL’s profile (Table 2.11), although the increase of collocation use in the 3<MI<5 band is noticeable in her profile. Table 2.12 displays YJ’s changes of collocation use measured by MI values over the three terms. If we look at the combined ‘non-associated’ and ‘weakstrength’ percentages, we find that although there was a peak in Term 2, the Term 3 figure (33.3 per cent) was essentially the same as at Term 1 (32.5 per cent). Likewise, the moderate-strength percentages remained nearly

Perspectives on Formulaic Language

40 Table 2.11

WL’s MI Distribution across Three Terms (Collocation Types)

100.0% 90.0% 80.0% 70.0% MI>7 60.0%

5<MI<7

50.0%

3<MI<5

40.0%

MI<3 Frequency<4

30.0% 20.0% 10.0% 0.0% Term 1

Term 2

0.0%

4.8%

0.0%

5<MI<7

25.6%

38.1%

23.5%

3<MI<5

23.1%

23.8%

41.2%

MI<3

10.3%

14.3%

11.8%

Frequency<4

41.0%

19.0%

23.5%

MI>7

Table 2.12

Term 3

YJ’s MI Distribution across Three Terms (Collocation Types)

100.0% 90.0% 80.0% 70.0%

MI>7

60.0%

5<MI<7

50.0%

3<MI<5

40.0%

MI<3

30.0%

Frequency<4

20.0% 10.0% 0.0% Term 1

Term 2

MI>7

9.3%

2.7%

Term 3 2.4%

5<MI<7

30.2%

29.7%

35.7%

3<MI<5

27.9%

21.6%

28.6%

MI<3

11.6%

13.5%

9.5%

Frequency<4

20.9%

32.4%

23.8%

Collocation Use in Academic Texts

41

the same in Terms 1 and 3. The increase in the percentage of ‘stronger collocations’ (+5.5 percentage points) is mostly accounted for by the decrease in ‘extremely strong collocations’ (–6.9 percentage points). Overall, there was a spike in the percentage of ‘non-associated’ and ‘weakstrength’ collocations in Term 2, but by Term 3 this had been rectified, and YJ ended up the academic year largely where she started in Term 1.

Discussion The multiple case-study approach used in this study produced a rich set of data, which was analysed in a number of ways: the number of types and tokens produced, the diversity of adjectives used with each academic noun, the amount of repetition of each adjective-noun collocation, how the collocations produced compared to those in the BNC academic reference corpus according to t-score (largely frequency-based) and MI score (largely based on strength of association), and the degree of strength of association according to a five-band MI rating scale. Overall, the participant group used fewer adjective-noun collocations (both types and tokens) over the course of the academic year, although the percentage of ‘robust’ collocations (types and tokens) increased slightly. The diversity of collocation (average number of adjective types per academic noun) decreased across the year, during which the collocations were repeated slightly more often in later academic writing tasks. This indicates that the group of four Chinese postgraduates as a whole demonstrated a tendency to use a somewhat smaller group of collocations more repetitively by the end of the 12-month MA programme. In terms of how ‘native-like’ the collocations were, the group produced a modest increase in t-score over the year, while the MI scores remained relatively static. When the strength of association was explored by MI banding, the group profile was largely similar in Terms 1 and 3. In sum, the statistical approach used in this study was able to show relatively little substantial change in the production of adjective-noun collocations over the course of an academic year. The MI bandings showed some improvement from Term 1 to Term 2 in the decreased use of MI<3 collocations, but this plateaued out and there was no further improvement at Term 3. However, for most of the measures, the group results fail to adequately represent the individual participants. LH showed fairly consistent decreases in the ability to use collocations on all of the measures. Conversely, TT produced

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Perspectives on Formulaic Language

improved figures on most of the indices. YJ showed fluctuations through the year, but largely ended up in Term 3 near where she started in Term 1, with some indices slightly up and others slightly down. WL produced a mixed set of results, with fewer types produced, but a great percentage of robust collocations. Her diversity of collocations decreased over the year, although so did the amount of repetition, albeit slightly. She used a higher percentage of collocations with higher t-scores, but those same collocations were about the same at the beginning and end of the year in terms of MI score. Indeed, perhaps the most interesting result of the study is the demonstration that the group figures painted a misleading picture of all the participants. The group results showed little real change, yet the study had one declining student, one improving student, and one with mixed results. There was also one student who ended up nearly where she started, but even here the group figures disguised the amount of variation in YJ’s results. Learners typically have a great deal of variation in their acquisition and use results, and this is particularly true of vocabulary (Meara, 1996). The small number of participants in this study also makes it hard for the variation to be ‘evened out’. Nevertheless, these results provide a warning to researchers of formulaic language to be careful about generalizing individual behavior from group averages. It may be that the acquisition and use of formulaic language is so idiosyncratic that group averages will have difficulty in making useful statements about any of the individuals within the group. In other words, the group scores may serve only to average out all of the variation inherent in the group, and thus provide a misleadingly ‘smooth’ representation of what might be quite different behaviors for all of the participants involved. This is clearly seen in this study, where the participants were very similar to each other. They were all Chinese, female, and of a similar age. They went through the same school system, and attended mainly the same MA courses during their stay in Nottingham. They (with the exception of TT who took the TOEFL) had the same IELTS overall score (6.5) and the same writing score (6.0). Thus we might expect that they would develop the adjective-noun collocations in similar ways. Yet in spite of this, they usually ended up with four quite different profiles in each of the measures. If such a small and homogeneous group as this demonstrates such varying behavior, then it appears that researchers will need to be cautious in their approach to group data in formulaic language research. This point has already been acknowledged by Howarth (1996), who argues that researchers

Collocation Use in Academic Texts

43

can lose opportunities for identifying significant differences among learners’ processing mechanisms by extracting an average performance from a corpus of various non-native writers. He also goes one step further, and claims that non-native language proficiency is best researched by means of small-scale manual analysis (such as carried out in this study). This raises the interesting issue of how much variation is inherent in the acquisition and use of formulaic language by second language learners, compared to the amount of consistency among learners. On all of our measures there was variation, but without firm benchmarks, it is difficult to interpret those variations. For example, the average t-scores of the collocations moved between 5.00 and 6.00 for our participants. But is this just normal fluctuation and not meaningful? Perhaps it takes 2–3 full points movement to indicate a truly meaningful change in collocation behavior? Without such benchmarks, researchers can describe the variation, but it is difficult to know if the variation represents real change. Unfortunately, to our knowledge, there are no established benchmarks for t-score, MI, or types and tokens which show the degree of change which indicates real improvement or decline for those measures. Indeed, for t-score and MI, the advice seems to be that they are best used for ranking collocations against each other, rather than providing absolute measures of strength of association (Stubbs, 1995; Manning & Schütze, 1999). Most of the measures in this study have been widely used in the study of formulaic language, but it has largely been descriptive up until now. If we are to use them to inform about the acquisition of formulaic language, the field will either need to somehow establish benchmarks to work against, or to move to alternative methodologies. One of these methodologies that worked well in a single case study of the acquisition of formulaic language was expert rating panels (Li & Schmitt, 2009). The present study has attempted to use a statistical approach to investigate a longitudinal learner corpus in order to identify the learners’ improvement in collocation use over the course of one academic year. This is different from previous research which used statistical measurements to explore the differences in the collocation use between native and non-native speakers (e.g. Lorenz, 1999; Durrant & Schmitt, 2009). Such research has successfully used association measurements of collocation (i.e. t-score and MI) as valid discriminators between the two populations with different proficiency levels, but this study seems to suggest that they are less efficient in identifying improvement in collocation of advanced L2 learners over a relatively short period of time. For example, Lorenz

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(1999) and Durrant and Schmitt (2009) found that proficient writers prefer collocations with high MI values but relatively low t-scores, but that the reverse is true for less proficient non-native writers. The present study cannot clearly distinguish Chinese L2 postgraduates’ developmental phases of collocation use within the 12-month period of investigation. This is not surprising when we take into account the relatively short-term investigation undertaken. One academic year may simply not be long enough for advanced level Chinese MA students to show meaningful improvement in collocation use. The present study is not without its limitations. Firstly, the BNC academic sub-corpus is not a parallel reference corpus, which consists of research articles, books, and book sections from all disciplines. Since a number of studies (e.g. Cortes, 2004; Biber, 2006; Hyland, 2008) have shown that there are considerable variations in the frequency of forms and structures across different types of academic writing texts, the use of adjective-noun collocations may vary from discipline to discipline. If a reference native corpus containing the specific texts from students’ MA reading list were compiled, it would be a more parallel comparison. In addition, it should be noted that the size of the longitudinal learner corpus is relatively small, consisting of only four participants’ writing tasks written within an academic year. This case-study approach has allowed a detailed exploration of individual progress, but a larger-sized longitudinal learner corpus built up over a longer period may yield a more insightful account of L2 learners’ collocation development over time.

References Adolphs, S., & Durow, V. (2004). Social-cultural integration and the development of formulaic sequences. In N. Schmitt (Ed.), Formulaic sequences (pp. 107–26). Amsterdam: John Benjamins. Biber, D. (2006). University language: A corpus-based study of spoken and written registers. Amsterdam: John Benjamins. Church, K., & Hanks, P. (1990). Word association norms, mutual information and lexicography. Computational Linguistics, 16 (1), 22–29. Cortes, V. (2004). Lexical bundles in published and student disciplinary writing: Examples from history and biology. English for Specific Purposes, 23 (3), 397–423. Cowie, A. P. (1998). Phraseological dictionaries: some East-West comparisons. In A. P. Cowie (Ed.), Phraseology: Theory, analysis and applications (pp. 145–60). Oxford: Oxford University Press. Coxhead, A. (2000). A new academic word list. TESOL Quarterly, 34 (2), 213–38.

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Durrant, P., & Schmitt, N. (2009). To what extent do native and nonnative writers make use of collocations? International Review of Applied Linguistics, 47, 157–177. Evert, S., & Krenn, B. (2001). Methods for the qualitative evaluations of lexical association measures. Paper presented at the 39th Annual Meeting of the Association for Computational Linguistics, Toulouse, France. Foster, P. (2001). Rules and routines: A consideration of their role in the task-based language production of native and non-native speakers. In M. Bygate, P. Skehan, & M. Swain(Eds.), Language tasks: Teaching, learning and testing (pp. 74–93). Harlow: Longman. Granger, S. (1998). Prefabricated patterns in advanced EFL writing: Collocations and formulae. In A. P. Cowie (Ed.) Phraseology: Theory, analysis, and applications (pp. 79–100). Oxford: Oxford University Press. Howarth, P. (1996). Phraseology in English academic writing: Some implications for language learning and dictionary making. Tübingen: Niemeyer. Howarth, P. (1998). The phraseology of learners’ academic writing’. In A. P. Cowie (Ed.), Phraseology: Theory, analysis, and applications (pp. 161–86). Oxford: Oxford University Press. Huang, J., & Hatch, E. (1978). A Chinese child’s acquisition of English. In E. Hatch (Ed.), Second language acquisition: A book of readings (pp. 118–31). Rowley, MA: Newbury House. Hyland, K. (2008). Academic clusters: Text patterning in published and postgraduate writing. International Journal of Applied Linguistics, 18 (1), 41–62. Lee, D. (2001). Genres, registers, text types, domains and styles: Clarifying the concepts and navigating a path through the BNC jungle. Language Learning & Technology, 5 (3), 37–72. Li, J. & Schmitt, N. (2009). The acquisition of lexical phrases in academic writing: A longitudinal case study. Journal of Second Language Writing, 18, 85–102. Lorenz, G. (1999). Adjective intensification – learners versus native speakers: A corpus study of argumentative writing. Amsterdam and Atlanta: Rodopi. Meara, P. (1996). The classical research in vocabulary acquisition. In G. Anderman & M. Rogers (Eds.), Words, words, words (pp. 27–40). Clevedon: Multilingual Matters. Retrieved December 20, 2008, from http://www.lognostics.co.uk/vlibrary/ index.htm. Manning, C. D., & Schütze, H. (1999). Foundations of statistical natural language processing. Cambridge, MA: MIT Press. Nesselhauf, N. (2003). The use of collocations by advanced learners of English and some implications for teaching. Applied Linguistics, 24 (2), 223–42. Nesselhauf, N. (2005). Collocations in learner corpus. Amsterdam/Philadelphia: John Benjamins. Pawley, A., & Syder, F. H. (1983). Two puzzles for linguistic theory: Nativelike selection and nativelike fluency. In J. C. Richards & R. W. Schmidt (Eds.), Language and communication (pp. 191–226). New York: Longman. Schmitt, N. (in press). A vocabulary research manual. Palgrave Press. Sinclair, J. (1991). Corpus, concordance, collocation. Oxford: Oxford University Press. Siyanova, A., & Schmitt, N. (2008). L2 learner production and processing of collocation: A multi-study perspective. The Canadian Modern Language Review, 64 (3), 429–58.

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Skehan, P. (1998). A cognitive approach to language learning. Oxford: Oxford University Press. Stubbs, M. (1995). Collocations and semantic profiles: On the cause of the trouble with quantitative studies. Functions of Language, 2 (1), 23–55. Stubbs, M. (2001). Texts, corpora, and problems of interpretation: A response to Widdowson. Applied Linguistics, 22 (2), 149–72. Wong-Fillmore, L. (1976). The second time around: Cognitive and social strategies in second language acquisition. Doctoral dissertation: Stanford University. Wray, A. (2002). Formulaic language and the lexicon. Cambridge: Cambridge University Press.

Chapter 3

Idiomatically Speaking: Effects of Task Variation on Formulaic Language in Highly Proficient Users of L2 French and Spanish1 Fanny Forsberg and Lars Fant Stockholm University

Introduction Formulaic language in second language use Formulaic language (FL) is commonly defined as consisting of multiword structures which carry a conventionalized ‘holistic’ meaning and which have not been generated in any sense by the grammar component of the language to which they belong (i.e. they are considered to be ‘non-productive’; cf. Erman & Warren, 2000; Wray, 2002). In second language acquisition (SLA) research, holistic and non-productive multiword structures have been discussed from various perspectives, for instance as communicative strategies for early learners (Krashen & Scarcella, 1978), as a basis for creative rule development (Wong-Fillmore 1976; Myles, F., Mitchell, R., & Hooper, J., 1998; Myles, F., Mitchell, R., & Hooper, J. 1999) or as indexes of idiomaticity (Yorio, 1989; Wray, 2002; Ellis 2002a, 2002b; Schmitt et al., 2004; Forsberg, 2008). A natural consequence of this diversity of approaches is the fact that different researchers have come to focus on quite different kinds of sequences, depending on the level of the learners studied and on which specific functions are attributed to the sequences. A second language (L2) beginner, for instance, may have learned sequences such as ‘my name is’ or ‘I like’ as non-productive chunks, understood by the analyst to be formulaic; this is the perspective taken by for example, Krashen & Scarcella (1978). Other researchers such as Schmitt, Grandage et al. (2004), Lewis (2008) and Bardovi-Harlig (2008) are more interested in expressions which are shared by an entire speech community, for example, ‘as a matter of fact’ or ‘you’re welcome’.

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An encompassing view, then, would be to regard formulaic language as a concept covering holistic non-productive strategies that range from an individual and often transitory usage to a collective and stable usage. However, only sequences used by an L2 learner which correspond to preferred patterns of an entire speech community will convey true idiomaticity, and this kind of sequence, that is, formulaic sequences which reflect nativelike selection (Pawley & Syder, 1983), is the focus of the present study. A basic assumption, then, is that L2 learners’ use of FL is a valid yardstick for measuring the idiomaticity of their language production as a whole.

What is ‘Advanced’ second language use? Although there is a well-established belief that FL could constitute a stumbling block for L2 learners, few researchers have set out to investigate in which ways highly proficient L2 speakers actually cope with these sequences. Another problem is that the learners considered in most studies to be ‘advanced’ do not, in fact, seem to have reached a very high level of integration with the target community, let alone to have acquired a degree of proficiency that would qualify as near-native. The subjects of these studies are often higher education language students who studied in language classrooms (e.g. Nesselhauf, 2005) or during a stay abroad (e.g. Schmitt Grandage et al., 2004). It seems to be the case that FL requires more target language exposure and integration than many other linguistic phenomena (Dörnyei, Z, Durow, V., & Khawla, Z., 2004). Considering the actual level of proficiency of the subjects in most studies addressing this issue, it is hardly surprising that their authors conclude that the differences to be found between natives and non-natives in their use of FL, whether in speech or writing, are considerable indeed. In the present study, non-native subjects will be considered in their capacity as L2 users (cf. Cook, 2002) rather than L2 learners. Furthermore, the L2 users studied are people who have lived in the target community for many years, having used the L2 as their prevailing communication code. In fact, Forsberg (2008), looking at this type of learner of French L2, has suggested that there are no significant differences at all between this category of L2 French users and native speakers of French as regards the quantity of FL produced, or the category distribution or even the type frequencies. However, her results were based on data drawn from a limited number of participants and produced in a semi-structured self-presentation interview. Since this may be considered a relatively easy task to perform, the question

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49

arises whether the same tendency will hold in more difficult tasks, which is why the present study is based on task variation.

Activity types and task variation The perceived difficulty of a task could arguably be seen as depending on how familiar an individual is with the corresponding activity type. Since formulaic sequences (FSs) emerge in and depend on context (MacWhinney, 2001), it can be assumed that all language users, native or non-native, master formulaic sequences associated with ‘common’ situations better than those occurring in unfamiliar situations (cf. Tavakoli & Skehan, 2005, on the notion of ‘familiarity’). Accordingly, ‘familiar’ activities would have to be contrasted with ‘non-familiar’ activities in order to obtain a clearer picture of possible differences between highly proficient L2 users and native speakers. The importance of performance differences across tasks has been acknowledged and thoroughly discussed over more than a decade by proponents of the ‘task-based language teaching paradigm’. Most of this body of research is interested in how complexity, accuracy and fluency (the so-called CAF parameters) are affected by task variation. Robinson and Gilabert (2007) have put forward the ‘cognition hypothesis’ according to which, among other things, the learner’s linguistic output will be more complex if the task is also a cognitively more complex one. A different position is taken by Skehan (1998), whose ‘limited attentional capacity model’ suggests that learners find difficulties in attending to all three CAF features at the same time, so that an increased focus on one will entail a diminished focus on the other two. This also implies that some tasks are more suited for testing complexity or accuracy and others more suitable for assessing fluency. Foster (2001) provides the only study to our knowledge that links FSs with task completion. The author finds that time does not affect (intermediate level) learners’ use of FSs, in contrast to native speakers, who use more formulaic sequences when they are not given any planning time. Foster’s findings suggest, first of all, that intermediate learners’ repertoire of FSs is not very large and therefore planning time is of little importance. More importantly, however, the study suggests that native speakers tend to use more formulaic sequences in time-constrained situations when they have to rely on automaticity. An ensuing question is to what extent high-proficient users will behave like natives in this regard. It should be added that even less advanced learners vary their choice of linguistic expression across different tasks, as shown by Tyne (2005). It is by

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no means a far-fetched assumption that people do not speak in the same way in all situations, regardless of whether they are native speakers, L2 learners or high-proficient L2 users.

Aims and research questions The first aim of this study concerns the effects that task properties may have on highly proficient L2 speakers’ formulaic language as compared to native use. To this effect, two different communicative tasks were designed, one of which is dialogic and represents an activity type based on common experience, while the other is monologic and represents a less ‘natural’ activity type2.The second aim regards the choice of L2s. Most SLA studies on formulaic language to date have focused on English3. Apart from providing an opportunity to compare the degree and nature of formulaicity in different languages, it can be assumed that taking several languages into consideration will yield a clearer and more generalisable picture of L2 use and acquisition. In this study, two L2s, French and Spanish − both of them Romance languages − are involved4, and there are four groups of participants: high-proficient L2 users of French, high-proficient L2 users of Chilean Spanish, native speakers of French and native speakers of Chilean Spanish. Since this contribution should be considered a first approach to the study of very advanced non-native use of FL, the research questions are quite generally stated as follows: The first and most comprehensive question is whether it is possible to discern any significant differences at all between non-native speakers’ and native speakers’ use of FSs. At least some contrasts are to be expected, considering that in other domains of linguistic behaviour there are divergences even between extremely proficient (near-native) and native speakers (Abrahamsson & Hyltenstam, 2009). If the answer to this is yes, an ensuing question is to what extent the nonnative use of FL can be seen as influenced by the communicative task. A plausible answer to this question would be that non-natives are better off on an interactive task oriented towards an everyday-life situation, and will therefore produce a higher proportion of FSs, than on a non-interactive task which involves less frequent vocabulary. Another possible answer would be that even highly proficient non-natives do not attain the pragmatic competence of native speakers and for that reason produce fewer FSs than the natives on an interactive task. The third research question is whether any differences can be found between Swedish non-native speakers of French and of Spanish respectively

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51

as regards their mastery of FSs and preferences in use. A hypothesis would be that, given the similarity between the two non-native groups in terms of length of residence and educational background, and given the typological proximity of the two languages, no greater differences will be found. Cultural differences between the two target communities involved could, however, play in another direction, since non-natives having resided for a long time in the target community can be expected to accommodate to a great extent to the L1 patterns they have been exposed to.

Approaches to Formulaic Language in SLA Research Psycholinguistic perspectives on FL Following Wray (2002), humans have access to two different modes of language processing: the analytic mode and the holistic mode. While in L1 acquisition and use holistic processing and ‘needs-only analysis’ are the preferred options5, the dominant mode in L2 use, according to Wray (2002), is analytic processing. This is mainly due to the impact of literacy and exposure to writing: L2 learners – especially adults – are practically always literate and they are exposed to the new language in its written shape prevailingly or at least to a considerable extent. The learners will therefore tend to segment speech in the way this is done in writing, in other words, with ‘minimal’ graphic words as basic units. When producing language in writing or speech, they will consequently have to figure out which words go together, an effort which L1 users are mostly spared since they already have the word combinations stored in memory. Wray believes that the only possibility for non-native speakers to obtain nativelike command of FL is through residing and interacting for a longer period of time in the target community (Wray, 2002, pp. 199–213). She also suggests that children and adults follow different paths towards fluency and idiomaticity. In the L1, fluency is obtained through chunking from the start, whereas L2 learners need to go through phases of automatization in order to attain, if at all possible, a comparable degree of fluency. After Wray (2002) had launched her definition of FSs as holistically stored and retrieved, researchers set out to test the psycholinguistic validity of her claim using various kinds of experiments. Two closely related questions have been addressed: are holistic sequences processed faster than ‘analytic’ sequences and, if this is the case, do native speakers and non-natives benefit from the same processing effects? Conklin and Schmitt (2008), in a study based on a self-paced reading task, have shown that both natives and

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non-natives processed formulaic language faster than non-formulaic language, and that natives did so even faster than non-natives. It should be kept in mind, however, that the FSs of their study were exclusively fixed idioms, and not transparent structures. Schmitt Grandage et al. (2004), on the other hand, have found that not all formulaic sequences seem to be processed as wholes. Processing benefits seemed to decrease on a continuum ranging from entirely fixed forms to more open combinations. Nick Ellis’s (2002a, 2002b) proposals partially coincide with Wray’s (2002) and also provide experimental support for Wray’s claim. Ellis’s ideas on FL are part of his more general explanatory model for frequency effects in language processing. According to this view, the natural sequence of acquisition runs from formulas (non-analysed units) via low-scope patterns to truly ‘creative’ constructions, and the extraction of regularly occurring patterns across formulas is what affords the development of a creative capacity. But do FSs necessarily have to break down and evolve into creative rules? Ellis holds that ‘formulas can break down’ (Ellis, 2002b), although there is a huge processing gain in keeping them as chunks. The question then is: can the learning of FSs be seen as a process of learning chunks and extracting regularities from them while striving towards keeping as many chunks as possible unanalysed for processing gains? In answer to this, Nick Ellis suggests that FSs need gradual strengthening in order to become automatized and entrenched in the mental lexicon. This means that initial chunk learning will not suffice in the long run, or in his own words, ‘nativelike idiomaticity takes an awful lot of figuring out which words go together’ (Ellis, 2002a, p. 157). In this perspective, FSs are seen as acquired in second language learning by means of two separate processes: holistic chunking and incremental automatization. Forsberg (2008, pp. 262–65) suggests that holistic chunking prevails in early L2 learning, whereas incremental automatization is more typical of later phases of acquisition. Low automatization due to lack of incremental learning would also explain the differences that may be found between native and high-proficient non-native users.

FL in highly proficient L2 users Although little research has been carried out to date as regards the FL of highly proficient L2 users’ in natural settings6, more studies are to be found concerning university students who are regarded as ‘advanced’ in a wider sense (for an operational definition, see e.g. Bartning, 1997). The use of FL

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53

in this type of data has mainly been examined with regard to written production, reception and performance in psycholinguistic experiments. When it comes to spoken production, the few studies that exist have mainly addressed the role of FSs as fluency devices. Raupach (1984) has found that German L2 learners of French overused certain formulas after a stay in France, contending that the subjects were using these formulas as a production strategy, or as ‘islands of reliability’. Hancock (2000) has come to a similar conclusion in a study on Swedish learners of L2 French. The fluency aspect of formulaic sequences has been thoroughly investigated by Wood (2006), who concludes that the use of formulaic sequences contributes highly to L2 fluency. It should be kept in mind, however, that researchers who talk of formulas do not always refer to the same phenomena. The type of speaker studied (the early learner/late learner/native speaker) influences the kinds of FSs in focus. In fluency studies, discourse markers tend to be dealt with, whereas studies on written production more often address collocations. In connection with spoken discourse, the only studies we know of that link FL and idiomaticity are Forsberg (2008) and Boers, Eyckmans, Kappel, Stengers, & Demecheleer (2006), all of which come to the conclusion that the learners’ general proficiency level seems to coincide with the degree of their mastery of FSs. With regard to writing, there is a considerably higher number of studies on FL, at least as far as L2 English is concerned. Some FL features in advanced learners’ written production seem to be generally recognized, such as the systematic overuse, or underuse, of specific FS types in learners’ written production (cf. Granger, 1998; Jaglinska, 2006; Bolly, 2008). Granger (1998), Nesselhauf (2005) and Lewis (2008) all regard cross-linguistic influence as an important factor in writing in L2, while Howarth (1998), Nesselhauf (2005) and Bolly (2008) claim that the degree of restriction or fixedness influences the learners’ mastery of FSs. Bardovi-Harlig (2008), whose main research question is whether the lack of pragmatic formulas in L2 English is a reception or a production problem, reports that although her learners seem to recognize formulas, they fail to produce them in discourse completion tests. Observations in the same direction were also made by Abrahamsson and Hyltenstam (2009) in an idiom cloze-test included in a test battery designed for near-native speakers of Swedish. This task was found to be one of the most difficult in the set and also one in which the age of onset was a determining factor. None of the above-mentioned studies can be used for direct comparison with the present study, since they do not include the same type of participants

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nor tasks. To our knowledge, no earlier studies have examined the production of formulaic sequences in the speech of long-residency L2 users, let alone with a multi-task research design. However, existing studies enable some predictions about our data. Differences are to be expected, considering that both Ekberg (2003) and Abrahamsson and Hyltenstam (2009) have found divergences between native and near-native speakers with regard to certain types of formulaic sequences. Divergences of this kind could at least partly be due to processing constraints, as suggested by Conklin and Schmitt (2008). Finally, differences due to cross-linguistic transfer may surface as both over- and underuse. In spite of all this, since the linguistically and culturally immersed L2 users of the present study constitute a type that has hardly been investigated to date, clear-cut predictions are difficult to make.

Data and Method Subjects The participants are split into two study groups and two control groups. The subjects who constitute the study groups are highly proficient and ‘immersed’ users of L2 French residing in Paris, and of L2 Spanish residing in Santiago de Chile, 10 subjects for each country. The control groups are of the same size as the study groups and consist of native speakers (NS) of French and Chilean Spanish who live in the same cities as the non-natives. The Swedish L1 non-native speakers (NNS) were selected according to two main criteria: they should have lived at least five years in the target language country and they should have completed at least upper secondary studies. In fact, a majority had experience of academic studies and all had gone through a period of formal instruction in the target language, although the extent of this instruction varied considerably among the participants. Differences with regard to exposure to formal instruction did not yield any differences with regard to FS use, which corroborates Forsberg’s (2008) earlier findings that formal study does not seem to promote the use of FS. The French non-native speaker group is more homogeneous than the other groups: it includes females only, all around 30 years of age, and with similar educational backgrounds. Most of them have lived in France since their early 20s, came originally to study and are now working. The French native control group is well matched to the non-natives as far as age and

Effects of Task Variation on Formulaic Language Table 3.1

55

Sociological Parameters of the Participants (SD = standard deviation)

Group/ parameter

French NNS (Paris) = 10

French NS (Paris) = 10

Spanish NNS (Santiago) = 10

Spanish NS (Santiago) = 10

Average age

29 (range 25–33, SD 2.9)

27.3 (range 23–34, SD 3.5)

39.8 (range 27–59, SD 10.6)

38.8 yrs (range 22–71, SD 14.4)

Mean length of stay (NNS)

10.3 years (range 5–14, SD 9.2)

−

9.9 years (range 4–16, SD 6.4)

−

Gender

10F

6F, 4M

6F, 4M

4F, 6M

educational background is concerned, though not with regard to gender: the group consists of six females and four males. The non-native speakers of Spanish are more heterogeneous than the non-natives in France. In average, they are about ten years older, with a wider age range and a higher degree of dispersion. With regard to educational background and professional activities both non-native groups are fairly similar. The native Spanish-speaking control group is well matched to the non-natives as regards age and educational profile. Both the native and the non-native group are of mixed gender: four females versus six males in the non-native group and six females versus four males in the native control group.

Tasks The present study is based on elicited, though spontaneously produced, spoken data. Two different tasks were included7, which will be referred to as ‘Boss’ and ‘Charlie’. The first task, ‘Boss’, is a role-play, in which the subject is asked to phone her/his manager to ask for a two-day leave (the ‘manager’ who answers the call is a native speaker hired for this purpose). The situation is complicated by the fact that an important business meeting is scheduled for one of the days and the subject is expected to play an important part in that meeting. In the second task, ‘Charlie’, the subject is asked to perform an online retelling of a 14.5-minute clip from the Charlie Chaplin movie ‘Modern Times’. The participants, who were not allowed any planning time, were instructed to tell what happens on the screen to someone who is unable to see it, and to try to capture as many details as possible.

Perspectives on Formulaic Language

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Table 3.2 Communicative Task Characteristics (based on Tavakoli & Skehan 2005) Task/ Task Familiarity of DialogicDegree of Degree of Concretecharacteristics information monologic structure routine abstract

Number of elements

‘Boss’

High

Dialogic

‘Charlie’

Low

Monologic High

Low

High

Concrete

Low

Low

Concrete

High

As can be seen, the tasks are very different in nature. ‘Boss’ is a dialogic task representing an activity which the subjects can be expected to be familiar with. It is similar to one of the tasks used by Taguchi (2007) in the sense that one party has more power than the other, there is a considerable hierarchical distance, and the request made by the less powerful party implies a high degree of imposition (high PDR values, see Brown & Levinson 1987, pp. 74–83). The ‘Charlie’ task, in turn, is monologic and does not represent any activity that could be thought of as familiar to the subjects (acting as a sports commentator would come closest and none of the participants had any such experience). It may be considered that two equally difficult8 tasks have been chosen: one can be regarded as pragmatically challenging and the other seen as a complex task in more general terms, due to its real-time processing demands, high number of elements involved and relatively infrequent lexis. In Table 3.2 the characteristics of the two tasks are listed according to the criteria proposed by Tavakoli and Skehan (2005), to which has been added ‘degree of routine’, a factor that could be expected to affect the degree to which formulaic sequences will be used.

Identification of FSs in the data The point of departure for identifying FSs in the present data is Erman and Warren’s (2000) definition of what these authors refer to as ‘prefabs’, in other words, ‘a combination of at least two words favoured by native speakers in preference to an alternative combination which could have been equivalent had there been no conventionalization’ (Erman & Warren 2000, pp. 31–32). Apart from a good definition, however, the identification of FSs in empirical data requires the application of heuristic procedures. In recent years, corpus linguistics have opened up for quantitative (and presumably objective) methods such as automatic extraction of frequent multiword sequences, used for example, by De Cock (2004) or Schmitt, Grandage and

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Adolphs (2004). A statistical device for measuring the strength of the connection between the parts of a multi-word combination was used for instance by Siyanova and Schmitt (2008) and consists of calculating a so-called MI (mutual information) score. A basic condition, however, for the meaningful use of this or other corpus linguistics methods is the existence of very large corpora. In view of the fairly modest size of our corpus (94,000 words) and the objective of extracting all FSs occurring in the data, manual procedures were preferred. The main criterion used for teasing true FSs out from from non-formulaic multi-word combinations has been the principle of restricted exchangeability (Erman & Warren, 2000, pp. 31–32) in combination with the researchers’ own intuition.9 As a subsidiary tool, database (in particular Google) searches were carried out in cases of doubt in order to ascertain the formulaic status of a given multiword expression. Furthermore, in order to strengthen reliability, the FSs of the present data were manually detected and listed by each author separately and the results were subsequently matched for intersubjectivity.

Categories of FSs The identified FSs were classified along two dimensions, one concerning their transferability between the non-natives’ Swedish L1 and the French or Spanish target language (see below), and the other concerning their linguistic function. With regard to the latter dimension, a primary distinction was made between lexical and non-lexical expressions (see below) and a secondary distinction was made between phrasal and clausal expressions (see below). Non-lexical items were furthermore subdivided into a grammatical and a discursive category (see below).

Transferable versus non-transferable In this study, only such FSs as can be seen as non-transferable from the nonnative speaker’s L1 to the L2 have been considered. This choice was made on the assumption that the L1 (and possibly also other L2s previously acquired) plays an important part in the acquisition of a new language, in the sense that learners will find it easier to identify and appropriate FSs that coincide structurally and semantically with FSs of their native tongue (or of an earlier acquired L2). A considerable proportion of FSs are, in fact,

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transferable across many languages, such as ‘find a solution’, which is equivalent to French ‘trouver une solution’, Spanish ‘encontrar una solución’ and also Swedish ‘hitta en lösning’. If non-transferable FSs in the L2 will be more of a challenge to the learner than transferable FSs, they will also constitute a more interesting object for analysis. These assumptions, which are in line with findings reported by for example, Cieslicka (2006), will also lead to an increase in focus on targetlike idiomaticity. A consequence of this methodological choice is that not only will transferable FSs be excluded in the non-native data, but also all such FSs will be excluded in the native data as can be considered transferable to the nonnative speakers’ L1. All instances of for example, ‘encontrar una solución’ (‘find a solution’, cf. above) will therefore be discarded, regardless of whether they are produced by a non-native or native speaker of Spanish. It could be suspected, however, that the elimination of transferable FSs will skew the proportion between the natives’ and the non-natives’ overall production of FL. In order to investigate this possible effect, a random sample covering approximately 10 per cent of the total quantity of words produced by each of the four groups (French and Spanish NNSs vs. French and Spanish NSs) was drawn and the proportion of transferable FSs was calculated for each group. Differences turned out to be fairly slight, with a somewhat lower proportion for the natives (French NSs 25.1 per cent, Spanish NSs 23.1 per cent) than for the non-natives (French NNSs 27.8 per cent, Spanish NNSs 29.3 per cent), which means the non-native speakers’ production of FSs can be said to be underestimated in the count by 10–11 per cent as a consequence of the choice to eliminate transferable FSs. Lexical versus non-lexical This distinction is a common one in semantics and lexicology (although the terminology may vary), which separates ‘content words’ from ‘function words’.10 Provided FSs are understood as items stored as wholes in speakers’ mental lexicons, no difference between single-word and multi-word items should be seen in this regard. Lexical FSs are thus regarded as expressions which have a denotative meaning, such as Fr. ‘faire du sport’ (‘practice a sport’) or Sp. ‘pedir permiso’ (‘ask for a leave’), or a denotative and pragmatic meaning, such as Fr. ‘merci bien’ or Sp. ‘muchas gracias’ (‘thanks a lot’). Non-lexical items, on the other hand, are understood as items which do not carry any own denotative meaning but function as operators on words, phrases and clauses and only thereby contribute to sentence (and pragmatic) meaning.

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Lexical-phrasal versus lexical-clausal Lexical FSs are seen as subdivided into phrasal structures (NPs, VPs, AdjPs, AdvPs, PrepPs) and clausal structures. Apart from the fact that these subcategories represent syntactic units of a different hierarchical order, there is another important feature distinguishing them. Phrasal FSs will have to go through syntactic processes such as inflection, determination, insertion in word order or voice transformations on their way from lexical storage to use in actual utterances, whereas clausal FSs can be inserted directly, or almost, into a syntagm. Thus, a phrasal FS such as Sp. ‘horario laboral’ (‘work hours’) will appear in the singular or in the plural, and with or without definite or an indefinite determiners, and a phrasal expression such as Fr. ‘mettre NP-PERS au courant’ (‘keep someone informed’) is likely appear inflected with regard to tense, mode, number and person and show up in the active, middle or passive voice. On the other hand, clausal expressions such as Fr. ‘je vous remercie de votre compréhension’ (‘thanks for being so understanding’) or Sp. ‘me queda absolutamente claro’ (‘it is perfectly clear to me’) are already there, ready for use in an utterance. As are verbless, though still clausal, expressions such as the above-mentioned Sp. ‘muchas gracias’ and Fr. ‘merci bien’ (‘thanks a lot’).

Non-lexical FSs: grammatical versus discursive Non-lexical FSs are regarded as analogous to function words, which means their meaning is procedural rather than denotative or referential. Depending on whether a non-lexical FS operates on a syntactic unit such as words, phrases or clauses, or whether they operate on whole utterances, they will be categorized as grammatical and discursive, respectively. Discursive FS are, in fact, multi-word discourse markers. Clear-cut examples of grammatical FSs are Fr.’un peu’/ Sp. ‘un poco’ (‘a bit’), or Fr. ‘pas du tout’ / Sp. ‘para nada’ (‘not at all’), whereas equally unequivocal examples of discursive FSs would be Fr. ‘c´est vrai que S’/ Sp. ‘la verdad es que S’ (‘as a matter of fact S’), or Fr. ‘par contre’/ Sp. ‘por el contrario’ (‘on the other hand’). As can be deduced from the two last pairs of examples, the distinction ‘phrasal/clausal’ are relevant also for discursive FSs, although that subclassification has not been implemented in the present data analysis. The grammatical/discursive distinction implies a twilight zone, for instance as regards conjunctional expressions which also function as pragmatic operators on whole utterances or stretches of utterances. In such

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cases, for example, Sp. ‘a no ser que S’ or Fr. ‘a moins que S’ (‘unless’), the choice was made to register the FS as grammatical.

Results Word production In order for meaningful comparisons to be made on the use of FL, the amount of words produced by each group in each of the tasks needs to be attested. In Table 3.3, these figures are presented together with figures that indicate speech rate in terms of words per minute. In the case of the ‘Charlie’ task, the duration of which is constant (14.5 minutes), the average speech rate for each group is directly calculable. Considering the variable duration of the individual phone calls in the ‘Boss’ task, however, the average duration for each group has to be given in order to obtain the corresponding figures for speech rate. Admittedly, comparing word production between French and Spanish is not an unproblematic issue since it is not obvious that speakers of one language will express an identical conceptual content with the same number of words. The typological similarity between the languages leads us to conclude, however, that no significant differences of the kind are to be encountered.11 Table 3.3 shows considerable differences in some respects, and fewer differences in others. With the exception of the column for speech rate in the ‘Boss’ task, the French speakers (NS or NNS) yield higher figures than the Spanish speakers and this difference is statistically significant at 0.005 level on the ‘Charlie’ task. Also, the non-native speakers tend to resemble the corresponding natives more than they resemble each other. Furthermore, no significant differences can be found in any of the native/ non-native comparison pairs, a result which precludes the attribution of divergences in FS production to word amount.

Table 3.3

Word Production, Duration and Speech Rate; Means for Each Group

Group/Task

‘Boss’, words

‘Boss’, minutes

‘Boss’, words/ ‘Charlie’, words ‘Charlie’, words/ minutes minutes

French NNS

568

7.67

74.1

2,130

146.9

French NS

611

6.79

90.0

2,120

146.2

Spanish NNS 518

6.22

83.3

1,419

97.9

Spanish NS

5.02

94.6

1,525

105.2

475

Effects of Task Variation on Formulaic Language

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The results of Table 3.3 raise a number of interesting questions. Why is the word production of the French speakers (NS and NNS) so much higher than that of the Spanish speakers on ‘Charlie’, but not on ‘Boss’? Why is the native speakers’ speech rate clearly higher than the non-natives’ on ‘Boss’ when their word production is not? Why is the natives’ speech rate higher than the non-natives’ on ‘Boss’, and not on ‘Charlie’? In connection with ‘Boss’ it should be kept in mind that this is a dialogic task in which another party than the subject participates (viz. the ‘boss’), and that the degree to which this other party dominates the conversation is liable to affect the subject’s performance in terms of both prolixity and speech rate.

Degree of formulaicity A general overview of the use of FL in the four groups is given in Table 3.4, with figures indicating the amount of FSs produced per 100 words. First of all, Table 3.4 shows that on ‘Boss,’ both the French-speaking and the Spanish-speaking natives produced significantly more FSs than do the non-natives. No such significance, however, can be found on ‘Charlie’, which means that ‘Boss,’ a dialogic and pragmatic task, seems to yield a greater distance between natives and non-natives than ‘Charlie’, a monologic and narrative task. This result runs counter to the hypothesis suggested at the beginning of the paper according to which the non-natives would perform in a more nativelike way with regard to FL on a familiar, everyday-life-oriented task than on a task which corresponds to an activity which the subjects can be expected to be less familiar with. On the other hand, Table 3.4 does show that all participant groups tended to be more

Table 3.4

Degree of Formulaicity (FS means per 100 words)

Group/Task

‘Boss’, FS/100 words

‘Charlie’ FS/100 words

French NNS

9.0 SD 1.4

9.3 SD 1.3

French NS

11.2* (p<0.02 in unpaired t-test) SD 1.8

8.9 (not significant)

Spanish NNS

8.1 SD 2.0

6.8 SD 2.0

Spanish NS

11.6* (p<0.002 in Mann-Whitney U) SD 1.2

8.0 (not significant)

SD 1.3

SD 1.0

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formulaic (though not to a statistically significant degree) on ‘Boss’ than on ‘Charlie’.

Category distribution The distribution of FS categories, as defined earlier is provided across the four groups. Table 3.5 accounts for this distribution, which is also represented graphically in Figures 3.1 and 3.2. In both languages and on both tasks, the native speakers produced significantly more lexical-phrasal FSs than the non-natives. This was also the case for lexical-clausal FSs on the ‘Boss’ task, whereas on ‘Charlie’, none of the groups produced enough clausal FSs to make comparison meaningful. Furthermore, when comparing the tasks, we can see that in all groups, more lexical items in general, and more lexical-phrasal items in particular, were produced on ‘Charlie’ than on ‘Boss’, which is an expected outcome, considering that a greater amount of denotative-referential lexis will be activated in the former task. The fact that natives turn out to be better producers of lexical FSs than non-natives is congruent with the findings in Forsberg (2008), with one Table 3.5

Distribution of FS Categories in ‘Boss’ and in ‘Charlie’ Lexical-clausal Lexical-phrasal

Grammatical

Discursive

Tot. FS

French NNS

0.2 SD 0.42

2.4 SD 0.7

2.1 SD 1.3

4.3 SD 1.1

9.0 SD 1.4

French NS

1.4 SD 1.27

3.2 SD 1.4

2.2 SD 0.7

4.4 SD 1.1

11.2 SD 1.8

Spanish NNS

0.7 SD 0.82

3.0 SD 0.8

1.2 SD 1.0

3.2 SD 0.8

8.1 SD 2.0

Spanish NS

1.5 SD 0.7

5.4 SD 1.6

1.1 SD 0.6

3.6 SD 0.7

11.6 SD 1.2

French NNS

0.2

3.8 SD 1.3

3.6 SD 0.8

1.7 SD 0.9

9.3 SD 1.25

French NS

0.3

5.3 SD 1.2

2.5 SD 0.7

0.8 SD 0.4

8.9 SD 1.28

Spanish NNS

0.1

4 SD 0.9

1.9 SD 0.6

0.8 SD 0.9

6.8 SD 2.0

Spanish NS

0.1

5.6 SD 0.7

1.9 SD 0.6

0.4 SD 0.3

8.0 SD 1.0

‘Boss’ Group/task

‘Charlie’ Group/task

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63

14 12 10 French NNS 8

French NS Spanish NNS

6

Spanish NS 4 2 0 Lex claus

Lex phras

Gram

Disc

Tot FS

Figure 3.1 Distribution of FS Categories in ‘Boss’

important exception: the most advanced group in that study, whose proficiency level was comparable to the French-speaking NNSs’ of the present data, produced a proportion of lexical FSs which equalled the native speakers of the control group. The reason why the non-native subjects did not perform as well in the present data is most likely to do with the degree of difficulty of the tasks involved. In Forsberg (2008), the subjects were

10 9 8 7 French NNS

6

French NS

5

Spanish NNS

4

Spanish NS

3 2 1 0 Lex claus

Lex phras

Gram

Disc

Tot FS

Figure 3.2 Distribution of FS Categories in ‘Charlie’

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Perspectives on Formulaic Language

respondents in a self-presentation interview, a task which should be regarded as a clearly less challenging than either ‘Boss’ or ‘Charlie’. The figures yielded for the grammatical and discursive categories open up a number of questions. Grammatical FSs are consistently more frequent on ‘Charlie’ than on ‘Boss’, while the reverse is true of discursive FSs. A plausible explanation for this incongruence would be that the argumentative nature of ‘Boss’ requires a more extensive use of discourse markers in general. This could possibly happen at the expense of grammatical formulas, although there is no clear answer as to why. A cross-linguistic comparison yields higher figures for the French-speaking than for the Spanish-speaking groups with regard to both non-lexical categories, which may be due to structural differences between the languages in the sense that grammatical and discursive markers more often correspond to multi-word expressions in French and to single words in Spanish. Further research is needed on this point. Finally, as far as the native/non-native dimension is concerned, hardly any differences can be found on ‘Boss’ with regard to either non-lexical category. On ‘Charlie’, however, the French-speaking non-natives used significantly more non-lexical FSs than the natives12, which may be explained by the fact that markers of this kind tend to be used as a production strategy in order to enhance fluency (Raupach 1984).

Concluding Remarks Not surprisingly, a number of contrasts have been found in this study between native and non-native performance with regard to FL, some of which can be proven statistically significant and others not. Both non-native groups converged with regard to many parameters. On ‘Boss’, they produced fewer words, a lower speech rate, fewer FSs overall and fewer lexical FSs in particular, than did the natives, whereas on ‘Charlie’ a corresponding divergence could be found only with regard to lexical FSs (fewer, as on ‘Boss’, in the non-native groups). This high degree of convergence between L2 users of different languages is interesting in that it actually demonstrates something which hitherto was only an expectation, namely that highly proficient L2 users tend to perform quite similarly regardless of which is the target language. Task and activity characteristics seem to affect the subjects’ production of FSs in various ways. All groups except the French-speaking non-natives

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65

produced more FSs overall on ‘Boss’ than on ‘Charlie’. Furthermore, ‘Charlie’ favoured the production of grammatical FSs, and ‘Boss’ that of discursive FSs, in all groups. In both tasks the results regarding lexical FSs are less nativelike than in the self-presentation interviews used by Forsberg (2008). An interesting detail is the high non-native figures for discursive FSs on ‘Charlie’ (though not on ‘Boss’) in comparison with those of the native speakers, which may be interpreted as a production strategy and a sign of stress in a situation which could easily be perceived as more challenging for a non-native than for a native speaker. Finally, there are some general divergences to be found between the languages, regardless of whether the speakers are native or non-native. Speakers of Chilean Spanish produce fewer words on both tasks than speakers of French, a result which can be interpreted in light of cultural preferences. The speech rate on ‘Charlie’ is also higher in the French than in the Spanish groups, although this does not happen on ‘Boss’, a result for which there is no obvious explanation. The French-speaking groups also produce a considerably higher proportion of non-lexical (grammatical plus discursive) FSs than the Spanish speakers, which may be attributed to structural differences between the languages. The findings of this study are, of course, to be regarded as preliminary. First of all, very little data for comparison has been available for the simple reason that highly proficient and immersed L2 users have been, to date, a rare object of study in SLA research. The results are also preliminary in the sense that the data needs to be examined not only by quantitative measures such as ‘degree of formulaicity’ and ‘category distribution’, but also through a more fine-grained analysis. As regards the ‘Boss’ task, pragmatic aspects need to be examined in greater detail by means of argumentation analysis; linking FL with a speech act-based analysis could reveal considerable divergences between native and non-native speakers. As for the ‘Charlie’ task, it would be desirable to investigate the individual types of sequences used. Even though no significant differences could be ascertained with regard to degree of formulaicity, differences were found between natives and nonnatives in the amount of lexical FSs produced. Important aspects of the lexical FS category, such as the use of infrequent vocabulary, require closer comparison. Hopefully, the present study will contribute not only to research on FL in general, but also to a more fine-tuned description of differences between native and non-native speakers, even at very high levels of L2 proficiency.

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Notes 1

2

3

4

5

6

7

8

This study is part of the project ‘Formulaic sequences and communicative proficiency in advanced L2 use’ (involving French, Spanish and English as L2), which in turn is part of the programme High-level Proficiency in Second Language Use, funded by the National Bank of Sweden. The authors also wish to express their gratitude to STINT (the Swedish Foundation for the Internationalisation of Higher Education and Research) for enabling the collection of Chilean data through an institutional grant given the Pontifical Catholic University of Chile and Stockholm University. In a study on L2 use and age of acquisition, Abrahamsson and Hyltenstam (2009.) used as many as 25 different tests to measure their informants’ nativelikeness. The two tests of the present study were chosen in order to represent as different a set of genres as possible. Galkowski and Masiejczyk (2007) made an attempt to compare Polish and English formulaicity and actually claimed that Polish was less formulaic in nature than English. There seems to exist some kind of received wisdom that English is a particularly formulaic language. This is why it is so important to study other languages, apart from English and preferably using the same methodology, in order to allow for comparisons. This type of project is currently being carried out at Stockholm University, where parallel corpora of English, French and Spanish L1 and L2 have been collected and analysed. The present study being the first pilot study of this project, it accounts for results from comparisons of two typologically close languages. A needs-only-analysis means that the speaker will do online parsing and composing of structures only when this, for whatever reason, is necessary, the default mode being holistic interpretation and retrieval. This view, it should be underscored, is discrepant with the generative paradigm, where emphasis is put on the speaker’s creative capacity. One study that addresses higher proficiency levels is Ekberg (2003), who investigates near-native speakers of Swedish in a multilingual setting in Sweden and concludes that near-native speakers use less conventionalised lexical and grammatical patterns than monolingual Swedes. Although these results have implications for the present study, the subjects studied – teen-age near-native speakers in a multilingual setting – are quite different. These two tasks are part of a larger test battery including other pragmatic and narrative tasks and also a self-presentation interview. This study is intended as a first sub-study in investigating the task variation effect. As reported in Tavakoli and Skehan (2005), defining the difficulty that a task represents for the participants is a complex endeavour – probably even more difficult in the case of the highly proficient participants of this study than for the subjects used in the task-based learning paradigm. Narrative tasks are often considered difficult (as reported by Tavakoli and Skehan 2005) insofar as they imply the encoding of a large number of elements and spatial-temporal relations. They are also regarded as more constraining in the sense that the speaker has little freedom as regards choice of lexis.

Effects of Task Variation on Formulaic Language 9

10

11

12

67

In much earlier work on FL, such as Bahns, J., Burmeister, H., & Vogel T. (1986), the researchers’ own intuition has been used as the only or main identification tool. See also Peters (1983) and Hickey (1993) as regards methods used in L1 acquisition studies, and Myles et al. (1998) or Bardovi-Harlig (2002) as regards SLA research. This distinction is far from being uncontroversial. One question regards the concepts ‘denotative’ versus ‘referential’. Pronouns, and with them pronominal FSs, should be regarded as referential but not denotatative. In this study, pronominal FSs count as grammatical (= non-lexical) in spite of the fact that they do not function as operators on other units. However, deictic or pseudo-deictic expressions like En. ‘in a different way’, ‘somewhere else’ or ‘last week’, although they could be regarded as more or less equivalent to pronominal expressions, have been registered as lexical(-phrasal) FSs. Although the common way of indicating speech rate is in terms of syllables per time unit, this measure is less suitable for cross-linguistic purposes, due to phonetic differences between languages. Because of its simpler phonetic syllable structure, Spanish will systematically yield more syllables per time unit than French. On the other hand, the structural-typological similarities between the two languages will ensure that the ‘same’ conceptual-structural content will be expressed by roughly the same number of words in each language. The differences that do exist do not seem to endanger comparability. The increase in word number caused by the obligatory subject pronoun in French, as compared to the Spanish pro-drop, will, for instance, be greatly compensated by the reducing effect of French elision (elided items such as j’ai, c´est or m’a are represented in the word count as single words). The Spanish-speaking non-natives produced more discursive (but not more grammatical) FSs than the natives on the ‘Charlie’ task, though not to a statistically significant degree.

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Wong-Fillmore, L. M. (1976). The second time around: Cognitive and social strategies in second language acquisition. Unpublished doctoral thesis. Stanford University. Wood, D. (2006). Uses and functions of formulaic sequences in second language speech: An exploration of the foundations of fluency. Canadian Modern Language Review, 63(1), 13–33. Wray, A. (2002). Formulaic language and the lexicon. Cambridge: Cambridge University Press. Yorio, C. (1989). Idiomaticity as an indicator of second language proficiency. In K. Hyltenstam & L. Obler (Eds.), Bilingualism across the lifespan (pp. 55–72). Cambridge: Cambridge University Press.

Chapter 4

Effectiveness of Text Memorization in EFL Learning of Chinese Students Zhenqiong Dai and Yanren Ding Nanjing University

Introduction The role of text memorization in second language (L2) learning is controversial. Repetition and learning by heart are regarded as two ‘outlaws’ (Cook, 1994, p. 133), and Chinese students studying abroad are often seen as ‘rote learners’ (Biggs, 1991, cited in Pennycook 1996, p. 222). Within China proper, the traditional literacy method of learning texts by heart seems to have fallen out of fashion since Chinese learners and teachers of English as a foreign language (EFL) favour a communicative approach today as they have more exposure to English than they had twenty or thirty years ago. At the same time, however, researchers (e.g. Ting, 2004) note that many teachers continue to use the old method of text memorization and many students hold it to be a ‘good medicine that tastes bitter’ (Ting, 2004). Pennycook (1996) argues that the strategy of text memorization used by Asian students should be looked at in a more positive light, and Parry (1998) suggests that ‘literate Chinese have well-developed strategies for appreciation and memorization that they could well turn to the purpose of learning English’ (p. 65).

Literature Review Theoretical background The dual-nature view of language Skehan (1998) points out that linguists often see language as a rule-based analytical system. While not denying the importance of this model, he proposes

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a language user’s model of language, which is an exemplar-based memory system; to him, language is both rule-based and exemplar-based. This dualnature view implies that learning language involves both learning rules and learning exemplars, which may or may not be immediately explained by rules. To Skehan, however, development of the knowledge of exemplars seems to be a natural result of language use; the language user ‘chunks free processing resources during communication so that planning for the form and content of future utterances can proceed more smoothly’ (1998, p. 3). Here, no room is left for conscious effort, and Skehan does not discuss what second language learners should do to learn those exemplars.

The noticing and frequency hypotheses Second language acquisition (SLA) literature does not contain much discussion on text memorization, but some theories have important implications in that regard. While Schmidt (1990, 2001) emphasizes the role of noticing (i.e. noticing an L2 feature to the point of being able to report it verbally) in the development of the interlanguage system, N. Ellis (2003, 2006) emphasizes the role of frequency of exposure and usage. Looked at together, their hypotheses seem to suggest that the more frequently a form occurs in input, the more likely it is to be noticed and then integrated into learner language. In this respect, the practice of text memorization can not only focus learners’ attention on language form but also make use of the form more frequent. SLA researchers are primarily interested in acquisition processes where learners are engaged in meaningful language use (Ding, 2007). They do not answer questions as to how, under the pressure of real time communication, learners can overcome the difficulty with noticing and rehearsing the features they should learn. Neither are they specific as to what these features are.

The learning of formulaic sequences One role of text memorization is that it helps with the learning of formulaic sequences (FSs), a term Wray (2002) suggests using to include various types of multi-word units and collocations such as idioms, lexical bundles, and lexical phrases. Researchers call FSs by many different names. Bolinger (1975) proposes that much language processing relies upon familiar, memorized material. Pawley and Syder (1983) claim that the average native

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speaker knows hundreds of thousands of lexicalized sentence stems. Lewis (1993) states that language consists of grammaticalized lexis. Nattinger and DeCarrico (1992) claim that the degree of fluency is not decided by learners’ command of grammar rules but by the amount of formulaic language stored in their memory. The FSs stored in the mind of language users seem to be what Skehan (1998) means by exemplars, which are not grammatically analysed at the time of use or sometimes not analysable in the first place. It is the memory system that provides learners with formulaic sequences to retrieve and use. By nature, these FSs have to be learned through repeated exposure and memorization. They have to be noticed and consciously learned. Nesselhauf (2003) points out that although rote learning has fallen into disrepute along with Behaviourism, it is vitally important that a number of collocations be taught and learnt explicitly.

Empirical research Studies on text memorization There is a scarcity of studies on the effects of text memorization. The few studies available (Dong & Fu, 2003; Ting, 2004; Ding, 2007) are largely based on qualitative analysis of student work and reflection. These studies found that text memorization or recitation leads to the learning of formulaic chunks, which in turn helps improve the quality and fluency of learners’ L2 writing and translation and, most of all, helps build their confidence in language use. One difficulty with quantitatively measuring the effects of text memorization is controlling the amount of time spent on language learning outside the classroom. It is assumed that students assigned the task of text memorization would spend more time on learning than those not assigned the task; therefore, the gains of these students may be attributed to the extra time spent learning.

Studies on the learning of formulaic sequences There is no shortage of research on the importance of FS knowledge in second language learning. Wong-Fillmore studied six Hispanic children acquiring English and concluded that ‘the strategy of acquiring formulaic speech is central to the learning of language’ (1976, as cited in Nattinger & DeCarrico, 1992, p. 25). Ting and Qi, (2005) compared the number of

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FSs used in oral and written texts, the grammatical accuracy, and oral and written test scores of Chinese English majors and claimed that the number of FSs serves as a better predictor of the quality of student texts than grammatical accuracy. That is to say, the learners’ ability to use FSs in writing or speech is related to their achievement in composition or oral skills; the better L2 writers/speakers are also better users of formulaic sequences. In terms of how L2 learners use FSs, Qi’s (2006) study provides a comprehensive picture. She investigated how 56 Chinese English majors improved the frequency, variation and accuracy of the FSs they used in their monologues over a period of four years. Her analysis of the corpus suggests, among other things, that over the years, the learners made limited progress in their use of what she classified as interpersonal and textual FSs, but made significant progress in the use of ideational FSs, especially in that of nominal and prepositional FSs. In Qi’s study, frequency served as an index of fluency in producing FSs; variation was an index of diversity in the FSs used in the text; accuracy was an index of the quality of FS uses. The present study borrows her method of analysing learner use of FSs.

Research questions Given the controversies over the practice of text memorization, studies are called for that can tease out the effects of such practice on L2 learning. This study followed a quasi-experimental design and attempted to tackle the following questions: 1. Does text memorization have any effects on L2 learners’ proficiency and writing ability? That is, how do learners make progress from the beginning to the end of the experiment? 2. Does text memorization have any effects on L2 learners’ use of FSs in writing? 3. Does text memorization produce the same or different effects on highand low-achieving learners in the use of FSs in their L2 writing?

Methodology Settings The study was set in the undergraduate English programme of a military academy. Although students enter this academy through the national college matriculation examinations just like students in other schools, they

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live the life of a military camp. All of them take the same classes at the same time. Outside the classes, they all study during designated periods of time; every evening (at 6 p.m.) they are assembled and led to the classroom for ‘self-study,’ which means doing homework assignments and preparing for upcoming classes and exams. At the end of this self-study period (at 9:20 p.m.), they are gathered and led back to the dormitories. No one is allowed not to study during the self-study period, and no one could study outside of this period either since they had other tasks and assignments. Such a unique setting made it possible to control the amount of time spent on learning outside class and therefore compare a group given the task of text memorization with a group not given the task.

Participants Two intact sophomore classes (average age 18.5) were chosen from the English Department. One class contained 26 students (23 males and 3 females) and served as the experimental group. Another contained 29 students (25 males and 4 females) and served as the control group. The two classes were taught by the same teacher. Like other English majors in China, these students were all taking courses in intensive reading (eight hours a week), extensive reading (two hours a week), oral English (four hours a week) and listening comprehension (two hours a week). They used the same textbooks. In this study, the final exam of the intensive reading in the semester before the study started was used as the pre-test since intensive reading was a major course and the final exam in this course measures proficiency rather than reading skills alone. The result of an independent-samples t-test of the scores of this pre-test revealed no significant difference between the two groups (t = –1.527, p = 0.133). Five high achievers and five low achievers were chosen from the experimental group for the purpose of exploring the differences in their practice of text memorization. They were selected according to (1) their English scores in the national college matriculation examinations and (2) their scores from the intensive reading course for the three semesters after they entered the academy (see Appendix A for the specific scores).

Instruments The study employed three instruments in collecting quantitative and qualitative data, pre- and post-tests of proficiency, pre- and post-tests of composition, and interview questions.

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1. Pre- and post-tests of proficiency. The post-test used the same format as the pre-test. It consisted of four parts, reading comprehension (20 per cent), paraphrasing (30 per cent), cloze (20 per cent) and translation (30 per cent). The time limit for each test was 90 minutes. Admittedly this might not be an ideal proficiency test since it did not measure speaking and writing skills. It was therefore supplemented by the test of English composition. 2. Pre- and post-tests of composition, which used the same topic: comment on whether it is good or not for college students to get married. The time limit for writing was 40 minutes. 3. Interviews after the experiment was over. The interview questions included: How did you memorize the text in each unit? What difficulties did you encounter when trying to memorize a text? In your opinion, how did such practice affect your English learning? The interviews were conducted in Chinese.

Data collection The experimental period lasted for about three months (about one semester). In the intensive reading course, the two groups, taught by the same teacher, used the same textbook. The teacher covered eight units during this period. Each unit consisted of a text, that is, a short essay, and a series of exercises. The text in each unit was 1,000 to 1,500 words long. Similar to most intensive reading courses in China’s university English programmes, for each unit, the teacher spent six to seven class hours on expounding the sentences in the text and two to three hours on exercises. Some of the FSs that occurred in these texts are given in Appendix B. The intensive reading and writing pre-tests were administered at the beginning of the experiment. The students were not informed of the essay topic in advance. During the experimental period, the experimental group was assigned to memorize the text from each of the eight units. The students in this group were often asked to recite the text in class, and under the pressure of performance in class, all of them worked hard to memorize the text during the ‘self-study’ period after the class. The control group was not assigned this task. The students of this group studied on their own during the ‘self-study’ period; they might go over the lessons they had learned, complete the exercises in the unit, read English novels and practice listening

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comprehension. The students of the experimental group, presumably, had much less time for these learning activities. It might also have happened that some students of the control group did some text memorization on their own, but they were never asked to recite any text in class. At the end of the experimental period, the two groups were given the proficiency and writing post-tests. The writing was on the same topic as that in the pre-test. After the tests, the ten students were interviewed individually.

Data analysis The proficiency tests were scored according to the set criteria by all teachers of the intensive reading courses in the university, including the one who taught the two classes that participated in this study. With each writing test, the student essays were marked by two experienced teachers with similar educational and teaching backgrounds. The scores were keyed in on the computer. The identification of FSs used in student essays followed the practice in previous studies (Howarth, 1998; Nesselhauf, 2003; Qi, 2006): using as reference an authoritative dictionary, in this study, Longman Dictionary of Contemporary English (2006), and manually identifying in student essays all the idioms, phrases and collocations that were included in the dictionary. Each time an FS was used was counted as a token but not as a type unless it was used for the first time in an essay. If an FS was used inappropriately (e.g. ‘it was interfere with my study’) or contained an error in the use of function words (e.g. ‘the teacher prevented us to look up textbooks’), it was counted as an erroneous token. The numbers of the correct and erroneous FS tokens and types for each essay were also keyed in on the computer. These numbers and scores were analysed with SPSS (Statistical Package for Social Sciences, Version 11.5). FS development was measured using three indices: frequency, variation and accuracy. The calculation of these indices followed Qi (2006): z z z

Frequency: dividing the total number of FS tokens in an essay by the total number of words of that essay and then multiplying by 1000 Variation rate: dividing the square of the number of FS types by the number of FS tokens per essay Accuracy rate: dividing the total number of error-free FS tokens by the total number of FS tokens per passage

To explore whether or not text memorization produces different effects on high and low achievers in the use of formulaic sequences, five high

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78

achievers and five low achievers were compared in terms of the frequency, accuracy and variation of the FSs they used in their pre- and post-test compositions.

Results and Discussion Learners’ progress in English proficiency and writing ability The results of the proficiency tests and writing tests administered before and after the experiment showed that both the experimental and control groups made improvement in English proficiency and writing ability. However, the independent samples t-tests show that the experimental group made significantly greater progress in proficiency than the control group (Table 4.1). The two groups did not show any significant difference in the pre-test (t = –1.527, p = 0.133) although the mean score of the control group (M = 67.5517) was slightly higher. However, they showed significant difference in the post-test (t = –2.650, p = 0.012); at the end of the experimental period, the experimental group (M = 80.4231) outperformed the control group (M = 77.2759). It can be concluded that text memorization appears to have helped these learners improve their English proficiency. The independent-samples t-tests also show that the experimental group made significantly greater progress in composition than the control group (Table 4.2). The two groups showed no significant difference in the pre-test (t = 0.039, p = 0.969) but significant difference in the post-test (t = 2.391, p = 0.020); the experimental group (M = 11.0385) outperformed the control group (M = 9.8793). Text memorization appears to have enabled these learners to improve their writing ability.

Table 4.1 Independent-samples T-tests of the Scores of Pre- and Post-tests of Proficiency Comparing the Experimental and Control groups Test

Group

N

Mean

Proficiency test (pretest)

1

26

65.6538

12.66473

2

29

67.5517

11.12778

Proficiency test (post-test)

1

26

80.4231

9.90827

2

29

77.2759

5.65620

Notes: 1 = the experimental group; 2 = the control group.

Standard deviation

T-value

P

–1.527

0.133

–2.650

0.012

Effectiveness of Text Memorization

79

Table 4.2 Independent-samples T-test of the Scores of Pre- and Post-tests of Composition Comparing the Experimental and Control Groups Test

Group

N

Pretest writing

1

26

8.6923

2.11224

2

29

8.6724

1.70752

1

26

11.0385

1.72002

2

29

9.8793

1.85960

Post-test writing

Mean

Standard deviation

T-value

P

0.039

0.969

2.391

0.020

Notes: 1 = the experimental group; 2 = the control group.

Table 4.3

Correlation Analysis between Writing Scores and the Use of FSs

Pretest writing score Pearson Correlations Post-test writing score

FS types in the pretest

FS tokens in the pretest

0.454**

0.463**

FS types in the post-test

FS tokens in the post-test

0.369**

0.368**

Notes: ** = significant at the 0.01 level.

Changes in FS use over the experimental period The relationship between writing scores and the use of FSs Table 4.3 summarizes the results of the correlation analysis of FS types/ tokens and the writing scores. As shown in the table, all the correlation coefficients were significant at the 0.01 level. It can be concluded that the scores of the learners’ L2 compositions were positively correlated with the numbers of FS types and tokens used in those compositions. The learners who wrote well also tended to use more FSs than others. This finding provides support for the finding of Ting and Qi (2005) that the learners’ ability to use formulaic language is a better predictor of their written English scores than is their grammatical accuracy.

General development in the use of FSs The findings about FS use in terms of frequency, accuracy and variation are shown in Table 4.4. These indices demonstrate the progress made by the two groups over the period of three months except for the index of variation. To be specific, the standardized frequencies of FS tokens per

Perspectives on Formulaic Language

80 Table 4.4

Overall Description of FS Use by All Learners in Both Groups

Index

Frequency

Experimental group

Mean SD

Accuracy Variation

Control group

Pretest

Post-test

Pretest

143.1

150.8

136.2

Post-test 139.7

23.11

21.34

23.82

Mean

0.90

0.95

0.86

0.89

SD

0.05

0.03

0.12

0.09

13.56

15.57

13.11

13.01

4.56

4.40

5.08

4.57

Mean SD

32.94

Table 4.5 Paired-samples T-test of Between-test Differences for the Overall Sample Index

Experimental group

Control group

Pretest – post-test

Pretest – post-test

Mean difference

Trend

P

Mean difference

Trend

P

Frequency

7.7

–

0.144

4.5

–

0.432

Accuracy

0.05

↑

0.000

0.03

–

0.214

Variation

2.01

↑

0.037

–

0.922

–0.1

Notes: ↑ = statistically significant increase; – = no statistically significant change.

essay for the experimental group increased from 143.1 to 150.8, 5.38 per cent, and for the control group increased from 136.2 to 139.7, 2.57 per cent. The accuracy rate of FS tokens for the experimental group rose from 0.90 in the pre-test to 0.95 in the post-test, 5.56 per cent, and for the control group, from 0.86 to 0.89, 3.49 per cent. However, for the index of variation, the mean of variation per passage for the experimental group increased from 13.56 to 15.57, 14.82 per cent, and for the control group decreased from 13.11 to 13.01, –0.76 per cent. In addition, between-test differences of the two groups in these three indices were distinguished with the help of paired-samples T-tests. The results are shown in Table 4.5. The accuracy and variation for the experimental group both significantly increased (p = 0.000 for accuracy and p = 0.037 for variation). On the whole, the experimental group made more improvement than the control group.

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Table 4.6 Differences in the Frequency of FS Use between the High and Low groups Pretest

Post-test

Mean

SD

Mean

SD

High

152

17.89

166

20.74

Low

124

19.49

146

16.73

MD Between-group difference High-low Between-tests difference Pretest – post-test

Pretest

–28

Post-test

–20

High

14

Low

22

Discrepancy between high- and low-achievers in the use of FSs A comparison of high and low achievers suggests that on the whole, low achievers benefited more from the practice of text memorization than high achievers; that is, the practice produces more positive effects for low achievers in the use of formulaic sequences.

Changes in frequency The low achievers made greater progress than the high achievers in the frequency of the FSs used in their compositions (Table 4.6). As expected, the high achievers used more FS tokens than the low achievers in both pre- and post-tests. However, the low achievers made greater progress than the high achievers (22 vs. 14); the difference between them narrowed from 28 in the pre-test to 20 in the post-test.

Changes in variation The low achievers made greater progress than the high achievers in the variation of the FSs used in their compositions. As shown in Table 4.7, the mean of the variation ratio of the low achievers (M = 9.7160) was much smaller than that of the high achievers (M = 17.6640) in the pre-test, indicating that the low achievers were only able to use a narrow range of FSs. However, at the end of the three-month experimental period, the low achievers achieved a variation ratio (M = 18.2060) that was even slightly higher than the high achievers’ (M = 17.4380); the high achievers made no progress in this aspect.

Perspectives on Formulaic Language

82 Table 4.7

Differences in Variation of FS Use between the High and Low groups Pretest

Post-test

Mean

SD

Mean

SD

High

17.6640

3.15377

17.4380

1.29239

Low

9.7160

2.11110

18.2060

3.08046

MD Between-group difference High-low Between-tests difference Pretest – post-test

Pretest

7.948

Post-test

–0.768

High

–0.226

Low

8.49

Table 4.8 Differences in the Accuracy of FS Use between the High and Low groups Pretest

Post-test

Mean

SD

Mean

SD

High

0.9120

0.05541

0.9660

0.03209

Low

0.9260

0.02702

0.9220

0.02775

MD Between-group difference High-low Between-tests difference Pretest – post-test

Pretest

0.014

Post-test

–0.044

High

0.054

Low

0.004

Changes in accuracy Unlike what happened to frequency and variation, in the accuracy of the FSs used in the compositions the high achievers made greater progress than the low achievers (Table 4.8). As shown in Table 4.8, the high achievers (M = 0.9120) started out lower than the low achievers (M = 0.9260) in their accuracy rate, but at the end of the study in the post-test they (M = 0.9660) did much better than the low achievers (M = 0.9220).

Possible reasons for the discrepancies The interview data showed that the five high achievers had sometimes practiced text memorization since high school. They said that the practice

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was a ‘piece of cake’ to them (High-2), and even without the teacher’s instructions, they would go ahead to memorize a passage if they found it ‘contained beautiful words’ (High-1). The five low achievers, by contrast, all said that text memorization had been ‘boring’ (Low-2) and ‘extremely painful’ to them (Low-1); towards the end of the experiment, however, they realized that the practice could help them ‘with further understanding of the text’ (Low-2). One of them (Low-2) said: ‘Sometimes, some of the phrases in the text “jumped” to my brain. . . . This gave me confidence I did not have before.’ The practice of text memorization (or the lack of it) may explain the differences in the command of FSs between the high and low achievers. It may also help explain the differences in the focus of their attention when they were memorizing the text materials. Since the high-achievers had already been good at text memorization, they may have paid more attention to the linguistic, textual context of FSs, resulting in progress in the accuracy of their FS use. The low achievers, by contrast, may have made more efforts to absorb the FSs they were not familiar with, resulting in progress in the frequency and variation of their FS use. At the same time, the use of newly learned FSs may have affected the accuracy; as a result, the low achievers did not make much progress in this aspect. The interview data also suggested that text memorization helped foster in the learners a habit of attending to language while engaged in reading or listening. This may help explain why the interviewees claimed that, in their post-test compositions, they had not used many of the FSs they had learned from the text materials assigned to them for memorization but instead, used many FSs they had learned elsewhere during the experimental period. They themselves, however, attributed this to the fact that the topic of the composition was not related to the content of the text materials they had memorized.

Conclusion Major findings The study produced the following findings: 1. Learners who practice text memorization make faster and greater progress in English proficiency and writing ability than those without such practice.

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2. Learners who practice text memorization make significantly greater progress in the accuracy and variation of formulaic sequences used in their compositions than those without such practice. 3. The progress resulting from text memorization is especially marked for low achieving students in the frequency and variation of the FSs they used in writing and for high achieving students in accuracy. That is to say, through text memorization, low achievers learn to use more FSs in a broader range of variety while high achievers learn to use them more accurately.

Implications The findings of the study suggest that text memorization is an effective second language learning strategy. In fact, as shown by the performance of the two groups, the strategy is actually more cost-effective than other learning practices when the total amount of time spent on learning is brought under control. There should be little doubt that teachers should encourage such practice and encourage students to attend to, imitate, memorize, and learn to use the collocations and sequences in the input, which will markedly improve the quality of their output. Text memorization is effective in language learning largely because language is exemplar-based (Skehan, 1998). Learning language involves learning rules as well as exemplars or FSs, and the learning of FSs depends on frequent exposure and memorization rather than on analysis and reasoning. The practice of text memorization, among other things, improves learner command of these unanalysed or unanalysable sequences. The current SLA literature does not answer questions as to how learners can overcome the failure to notice and to rehearse when they are under the pressure of real time communication. However, as Ding (2007) points out, because the practice of text memorization takes place outside of the settings of online meaning comprehension and expression, it enhances noticing as learners attend to formulaic sequences and other features of usage that tend to be ignored during real time communication. It also enhances rehearsal with repeated reading and recitation. The findings of this study lend support to this view.

Acknowledgements The authors would like to thank Dr. Don Snow, a colleague from Nanjing University, who helped with the editing and revision of this manuscript.

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References Biggs, J. B. (1991). Approaches to learning in secondary and tertiary students in Hong Kong: Some comparative studies. Education Research Journal, 6, 27–39. Bolinger, D. (1975). Meaning and memory. Forum Linguisticum, 1, 2–14. Cook, G. (1994). Repetition and learning by heart: An aspect of intimate discourse, and its implications. ELT Journal, 48, 133–41. Ding, Y. (2007). Text memorization and imitation: The practices of successful Chinese learners of English. System, 35, 271–80. Dong, W., & Fu, L. X. (2003). The role of recitation input in the teaching of college English (in Chinese). Foreign Languages Society, 4, 56–59. Ellis, N. (2003). Constructions, chunking, and connectionism: The emergence of second language structure. In C. J. Doughty & M. H. Long (Eds.), The handbook of second language acquisition (pp. 63–103). Malden, MA: Blackwell. Ellis, N. (2006). Language acquisition as rational contingency learning. Applied Linguistics, 27, 1–24. Howarth, P. (1998). Phraseology and second language proficiency. Applied Linguistics, 19, 24–44. Lewis, M. (1993). The lexical approach: The state of ELT and a way forward. Hove, UK: Language Teaching Publications. Nattinger, J. R., & DeCarrico, J. S. (1992). Lexical phrases and language teaching. Oxford: Oxford University Press. Nesselhauf, N. (2003). The use of collocations by advanced learners of English and some implications for teaching. Applied Linguistics, 24, 223–42. Parry, K. (Ed.). (1998). Culture, literacy, and learning English: Voices from the Chinese classroom. Portsmouth, NH: Heinemann. Pawley, A., & Syder, F. (1983). Two puzzles for linguistic theory: nativelike selection and nativelike fluency. In J. C. Richards & R. Schmidt (Eds.), Language and communication (pp. 191–226). London: Longman. Pennycook, A. (1996). Borrowing others’ words: Text, ownership, memory, and plagiarism. TESOL Quarterly, 30, 201–30. Qi, Y. (2006). A longitudinal study on the use of formulaic sequences in monologues of Chinese tertiary-level EFL learners. Unpublished doctoral dissertation, Nanjing University. Schmidt, R. (1990). The role of consciousness in second language learning. Applied Linguistics, 11, 17–46. Schmidt, R. (2001). Attention. In P. Robinson (Ed.), Cognition and second language instruction (pp. 3–32). Cambridge, UK: Cambridge University Press. Skehan, P. (1998). A cognitive approach to language learning. Oxford University Press. Ting, Y. R. (2004). Learning English text by heart in a Chinese university. Xi’an: Shanxi Normal University Press. Ting, Y. R., & Qi, Y. (2005). A study of the correlation between the use of formulaic sequences and English oral and writing proficiency (in Chinese). Journal of PLA Institute of Foreign Studies, 5, 49–53. Wong-Fillmore, L. (1976). The second time around: Cognitive and social strategies in second language acquisition. Unpublished doctoral dissertation, Stanford University. Wray, A. (2002). Formulaic language and the lexicon. Cambridge: Cambridge University Press.

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Appendix A The interviewees’ English scores (and ranks in the class) in the College Entrance Examinations (CEE) and for their intensive reading courses in three semesters Table for Appendix 1 CEE Rank Term 1 Rank Term 2 Rank Term 3 Rank Pretest Rank High achiever 1

140

1

87

1

86

1

87

1

87

1

High achiever 2

138

2

78

2

85

2

82

2

84

2

High achiever 3

135

3

73

4

82

3

80

3

83

3

High achiever 4

135

3

75

3

78

4

80

3

81

4

High achiever 5

133

5

72

5

76

5

79

5

77

5

Low achiever 1

103

22

63

22

65

22

66

22

64

22

Low achiever 2

100

23

63

22

62

23

65

23

63

23

Low achiever 3

100

23

62

24

60

25

64

24

60

24

Low achiever 4

99

25

56

25

61

24

57

25

53

25

Low achiever 5

95

26

51

26

54

26

53

26

49

26

Note: CEE = score for the English test in the national college matriculation examinations; Term 1 = score for the intensive reading course in the first semester; etc.; pretest = score for the pretest.

Appendix B Some of the FSs occurring in the texts the experimental group learned by heart: used to

be concerned with

spend time doing sth.

look through

end up in

the result of

have to do sth.

break silence

a hint of

lose control of sb’s temper

shrug one’s shoulders

one’s first impressions of

take measures to do sth.

take/tear sb. away from

a capacity for

a great surprise

in accordance with

wait for

happen to do sth.

in anger

in one’s youth

Catch sight of

bring sb. sth.

seem to do sth.

Come across

have an instinct about

in a way

in a sense

sort of

from one’s experience

ask sb. for sth.

do sth. for sb.

go (all) to pieces

Effectiveness of Text Memorization drive at

on account of

be taken aback

in good condition

so… that …

part of

in the case of

be of great importance

for example

the influences of

have influence on

live in

Correspond to

the question of

distinguish between

ideally speaking

the role of

more than

take sth. for granted

because of

the problem of

change one’s opinions

change one’s mind

of course

the possibility of

be capable of

to a large extent

the nature of

the personality of

in other words

so that

the importance of

the style of

go out

no doubt

for one thing/for another

no exception

no matter how

both … and …

afford to do sth.

As well as

the nerves of

a memory of

in one’s eyes

at the same time

a bottle of

in front of

in despair

all manner of

the essence of

mix with

the pressure of

let alone

tend to do sth.

in fact

depend on

as long as

between … and …

in need of

lead to

an example of

learn from

log on

access to

add sth. to sb.

argue over

blame sb. for sth.

break the law

bring about

challenge sb. to do sth.

direct attention to

develop one’s ability

forbid sb. from doing sth.

have a long way to go

hear of

interfere in/with

lag behind

leave behind

look before you leap

lay sth. on sb.

make a solid basis for

draw a conclusion

pass by

Prefer to do sth.

produce effect on

quit school

succeed in sth.

support sb. in doing sth.

take responsibility for sth.

take responsibility to do

take advantage of

travel through

In terms of

Note: The italicized FSs are those that the experimental group used in the post-test writing.

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Chapter 5

Lexical Clusters in an EAP Textbook Corpus David Wood Carleton University

The present study is an investigation of the most frequently used formulaic sequences in typical textbooks most popularly used in English for academic purposes (EAP) courses in North America. The overall objective is to determine what kind of exposure EAP learners receive to these important elements of academic prose, and whether EAP textbooks and materials promote the noticing, processing, and use of formulaic sequences most relevant to reading and writing in the academy. Since EAP courses are meant to be a means of preparing non-native speakers of English to deal with the demands of post secondary academic reading and writing, it stands to reason that they should deal with the formulaic sequences most frequently used to construct academic text in English. At the least, learners should be guided to notice and understand the functions and meanings of the sequences in texts drawn from appropriate academic genres. Formulaic sequences are defined here as multi-word strings or frames which are processed mentally as if single words. The sequences are generally seen as serving a wide range of functions in discourse, and as a way of expressing concepts and textual relationships to facilitate efficient and effective communication. Formulaic sequences have been the focus of a variety of types of research over the past three or four decades, and have been given as many as 40 different labels (Wray & Perkins, 2000), but the term formulaic sequence has become the generic term for the collocations, idioms, metaphors, lexical phrases, and other labels and types of multiword units studied. Due to the nature of the language corpora to be analysed in the present study, and the process required to identify formulaic sequences, one specific type of formulaic sequence is under consideration. In previous studies of formulaic sequences in academic language, using corpora of textbooks, lectures, and articles published in journals, as well as student writing and speech, lexical bundles have been the focus of inquiry. Lexical bundles

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can be defined as frequently occurring combinations of three or more individual words which occur at a certain frequency across a range of texts in a given register. Frequency counts using corpus analysis software can locate the bundles, which can then be ranked as to frequency, and categorized by type, discourse function, or meaning. In the present study, the term lexical cluster is used, due to the fact that the focus on a small corpus comprised of topically diverse texts mitigated against the requirement of occurrence across a range of texts. Previous research of this type has mainly focused on comparing work published in academic journals to that of novice and advanced regular university student writers in the same disciplines (Biber, Conrad, & Cortes, 2004; Cortes, 2004). As for EAP-focused work, there exist very few studies. One recently published work with this intent is by Jones and Haywood (2004), studying the teaching and acquisition of particular formulaic sequences by EAP learners. In their study, they found limited success in teaching a pre-set group of formulaic sequences to EAP learners. In EAP textbooks and materials, it is often the case that certain lexical bundles are presented as types of connectors or discourse markers, although they are seldom presented in a context or arranged as to frequency (Oshima & Hogue, 2004; Williams, 2005). It is usually assumed that lexical bundles will be acquired subconsciously through input and exposure to text, or that teaching lexical bundles as connectors and discourse markers from lists and through written exercises using decontextualized sentences can suffice. Some movement is occurring in the EAP textbook field toward a more corpus-based approach to materials and textbook design (see Harwood, 2005 for an overview), but the mainstream EAP textbook market at present most likely relies on the tried and true, providing large amounts of academic reading and listening input and requiring learners to write extended texts. While providing learners with large amounts of input on various academic themes is part of a valid approach to EAP instruction, several questions arise which are related to the material used in such programmes: 1. Does the material contain rich reading input containing lexical clusters likely to be used in the actual texts the learners will encounter in regular introductory texts in their major disciplines? 2. Are learners made aware of the importance and the range of purposes to which the lexical clusters are put in the types of reading texts they are likely to encounter in regular introductory classes in their major disciplines?

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Formulaic Language and EAP For the past four decades, researchers have been interested in formulaic sequences, multi-word lexical strings or frames which are processed mentally as if single words. The sequences have a large number of discourse functions, and are often genre-specific ways to express concepts and textual relationships for efficient and effective communication. A relatively small but growing body of research explores relationships between the formulaic sequences in university written and oral discourse and materials used in the teaching of EAP. In academic writing, for example, some evidence has emerged to show that formulaic sequences are at high frequency in the writing of authors in academic disciplines, but they are comparatively rare in the production of both regular students and EAP students in those disciplines. In 1983 Pawley and Syder noted a connection between formulas and fluent language use, that we tend not to make use of the endless lexical and grammatical potential of language, and they were among the first to observe that language production may be only partly based on rule-governed formation of utterances from lexis through syntax, morphology and phonology. In spontaneous speech, such a laborious method of language production would seem improbable, particularly in light of the limitations of human memory and attention. Over time, the development of computer technology, corpus study, and phraseology have provided discourse-based evidence of how words tend to collocate and cluster. Phraseologists have pointed out that collocations cross a wide spectrum, and can include phrasal verbs, prepositional phrases, and more (Mel’cˇuk, 1998). A small number of studies have examined the role of formulaic sequences in adult L2 acquisition. Yorio (1980) found that formulaic language was used by adults as a production strategy, to save effort and attention in speaking. Schmidt (1983), in a case study of an adult L2 learner in a naturalistic context, found the learner used increasing numbers and varieties of formulaic sequences while showing little development of grammatical and other aspects of language. Bolander (1989), in a longitudinal study of adult L2 acquisition, found that learners used formulaic sequences containing particular language structures long before they could show they had actually acquired the structures themselves. The links between formulaic sequences and pragmatic competence have been researched. Coulmas (1979, p. 241) states that ‘As they provide the verbal means for certain types of conventional action, their meanings are conditioned by the behavior patterns of which they are an integrated part,’ and goes on to note that

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formulas help to facilitate unambiguous communication. Bygate (1988), in a study of adult learners, found pragmatic uses of formulas to include repetition, questioning, agreeing, confirming, clarification, and focusing attention. Formulaic sequences are ubiquitous in both written and spoken discourse (Schmitt & Carter, 2004). A study of spoken and written discourse by Erman and Warren (2000) found that word combinations comprised 58.6 per cent of the spoken corpus, and 52.6 per cent of the written corpus. The use of recurring word combinations has long been considered a marker of proficiency in many genres, including academic writing (Bamber, 1983; McCully, 1985). Over time, studies on the acquisition and use of formulaic sequences have employed a variety of research methods, including ethnography (Hakuta, 1974; Fillmore, 1979; Peters, 1983), conversation analysis (Manes & Wolfson, 1981; Tannen, 1987), and quantitative investigations of the use of multi-word units (Kjellmer, 1991; Sinclair, 1991), to name a few. Such research has tended to adopt one of two relatively distinct areas of focus. One of the foci has been sequences in which the meaning or function of the whole unit does not equal the sum of its component lexical parts, the so-called pure idioms (Chafe, 1968; Moon, 1998). The other area of focus has been fixed expressions in spoken language, particularly those which are related to particular speech events or which further the fluent production of speech (Coulmas, 1981; Wood, 2006; Yorio, 1980). The advent of corpus analysis has greatly benefitted and enriched the study of formulaic language, and the research has tended to adopt one of two approaches – the phraseological and the distributional (see Granger and Paquot, 2008 for a detailed review). The more traditionally phraseological approach involves a search for sequences which have been previously identified by researcher intuition or lexicographic or other means (e.g. Nattinger & DeCarrico, 1992). The distributional approach is more bottom-up, using corpus analysis software to identify co-occurrences of two, three, or more words, at different frequency cut-off points (Altenberg, 1998; Biber, Johansson, Leech, Conrad, & Finnegan, 1999). Phraseological methods of corpus-based research into formulaic sequences have generally been used in the study of smaller corpora, particularly those comprised of spoken language, and for identifying the meanings and discourse functions of the sequences. Distributional methods have yielded quite useful results with larger corpora and for the examination of genres such as academic prose. Another line of inquiry has focused on formulaic language in native and nonnative speaker writing in English (Bahns, 1993; Granger, 1998; Howarth,

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1998), often uncovering a connection between use of formulaic sequences and pragmatic competence. As Granger (1998, p. 145) points out, it is often the case that rules of pragmatics are realized through the use of formulaic language. Some recent research has addressed the question of whether the formulaic language needed for academic writing can be acquired by native speakers through input and experience. Although this research has not addressed issues specific to EAP students, it is possible that English language learners could also acquire formulaic language through general exposure to it in both EAP and regular university classes. Hewings and Hewings (2002) conducted a key study comparing the use of certain linguistic features in published academic writing and that of regular university students. Cortes (2004), conducted a corpus-based study of the use of formulaic sequences in published and student writing in the specific disciplines of history and biology, finding that students tended not to use the formulaic sequences which were most frequent in published writing, and that when they did, they tended to do so for different pragmatic purposes. If these regular university students rarely used the target lexical bundles in their writing, EAP learners should have even less facility with them, which suggests that EAP programmes should include some explicit treatment of formulaic language. The use of formulaic sequences has been linked to perceptions of proficiency in academic writing. Wray (2002) noted that the use of formulaic sequences has two benefits for academic writers – they are connected to the expression of identity within disciplinary communities, and they reduce reading effort. Haswell (1991) pointed out that that recurrent word combinations are a marker of mature academic writing. Cortes (2004) remarked that the use of formulaic sequences ‘seems to signal competent language use within a register to the point that learning conventions of register use may in part consist in learning how to use certain fixed phrases’ (p. 398). All of these claims about the value of formulaic language have been analysed in research into a particular type of frequently occurring word combination called lexical bundles (Biber et al., 1999; Biber & Conrad, 1999). Lexical bundles are combinations of three or more words which are identified in a corpus of natural language by means of corpus analysis software programmes. An additional characteristic of lexical bundles is that they occur across a range of texts or, in the case of academic language, a range of disciplines. Biber and Conrad (1999) noted that these word combinations ‘are so common, it might be assumed that lexical bundles are

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simple expressions, and that they will be acquired easily.’ (p. 188) However, the acquisition and use of lexical bundles does not appear to occur naturally. Lexical bundles have been shown to be used at high frequency in published academic writing, and particular types of the bundles are characteristic of particular disciplines (Cortes, Jones, & Stoller, 2002). Academic disciplines have different ways of seeing the world, connected with different communicative conventions (Hyland & Hamps-Lyon, 2002). Biber (2006) presented a comprehensive corpus-based analysis of university language, including an examination of lexical bundles in textbooks. He found that academic disciplines differed in their use of lexical bundles, with natural and social sciences relying on them more than the humanities. Overall, the distribution of lexical bundles across functional categories in Biber’s study show that referential bundles – making direct reference to real or abstract entities or to textual content or their attributes – are the most common. Stance bundles – expressing attitudes or assessments of certainty – are the second most common type of function for lexical bundles in the textbooks, whereas discourse organizers – reflecting relationships between previous and subsequent discourse – were the least common. Within the category of referential functions, it appears that quantity and intangible framing subfunctions represent the largest categories.

Method The present study is an examination of the occurrence of lexical clusters in EAP textbooks. The corpus was compiled from six commercially available textbooks, at the intermediate-advanced level, published within the past seven years by major publishers: z z

four multi-skills, comprehensive intermediate-advanced English for academic purposes (EAP) textbooks two reading and writing skills-focused textbooks

EAP materials generally contain both reading texts and instructional material, the latter consisting of exercises, instructions for activities, and so forth. The corpus used in the present study was divided into two subcorpora, a textual subcorpus made up of the reading texts from the textbooks, and an instructional subcorpus made up of the instructional material from the textbooks.

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The corpus overall consisted of : z z z

Total corpus – 579,345 tokens (running words) Textual subcorpus – 187,959 tokens (running words) Instructional subcorpus – 391,386 tokens (running words)

Before being compiled into a corpus, the textbooks were pruned of superfluous text which did not play a direct role in either instruction or input, for example titles, headings, captions, tables of contents, prefaces and overviews, and so on. The textual subcorpus made up roughly 32 per cent of the total corpus, a rather telling piece of data in that it indicates that actual textual input made up a relatively small part of the content of the textbooks. In contrast, the instructional subcorpus made up almost 68 per cent of the total corpus, which reveals that the language related to tasks and activities took up the great majority of the textual space. Textbook writers are responsible for creating valid learning activities in the materials they produce, and it stands to reason that the sets of instructions, explanations, questions, and advice that they present in textbooks are in some ways the heart of their craft. In EAP materials, instructional material tends to be centred around texts extracted from original academic sources, and that was the case in all of the textbooks selected for this analysis. However, the fact that instructional language predominated in this EAP corpus might seem to indicate that a wide range of tasks involving analysis, synthesis, and extrapolation followed from the texts, and that a certain amount of this activity would focus on formulaic language, either directly or implicitly. This was tested by searching page by page for reference material, exercises, or activities which overtly focused on the lexical clusters and other types of formulaic language. It is important to note that lexical bundles can be viewed as a subset of formulaic language, which is often defined as multi-word lexical strings or frames processed mentally as if single words, serving a wide variety of functions in discourse, and providing generally agreed upon means of expressing concepts and textual relationships which facilitate efficient and effective communication. This last is crucially important for EAP, and it might be said that formulaic language is key to the nature of particular discourses as certain recurring word combinations are used within such communities as commonly agreed upon ways to express ideas, to link ideas, to express stance or opinion, and so forth. Lexical bundles may be defined as frequently occurring combinations of three or more individual words

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identified by means of corpus analysis, usually at a frequency of 20 per million words, across a certain number of texts or types of texts. The present study incorporated the methods used by researchers such as Biber, Cortes, and others, with certain modifications. For one, while adopting the frequency cut-off of 20/million words, no requirement of text coverage was used, because of the small size of the corpus and the fact that it was comprised of texts on a variety of topics seldom repeated. The unit of analysis in this study is four-word bundles for two reasons: they are more common than five-word bundles; they serve a wider range of function and structure than three-word bundles. WordSmith Tools 4.0 (Scott, 2004) was used to scan the corpus. The two subcorpora in this study, the instructional and the textual, were treated as separate in determining frequency of occurrence of clusters. That is, the frequency cut-off of 20/million words was used within the instructional subcorpus and within the textual subcorpus, and the overall corpus word count was not used in measuring frequencies. This yielded a remarkably high number of identified clusters in the instructional subcorpus, since the text in that subcorpus consisted to a great extent of repeated instructions, directives, and so on. This language is by necessity quite formulaic, and might be said to be an indication that the instructional language present in EAP textbooks is representative of a discourse community. In addition, publishers tend to try to ensure consistency within a textbook or series in the way instructional language is presented and phrased, which adds to the likelihood of repeated formulaic ways of expression. It may be argued that instructional language is not necessarily input for readers/learners, but rather organizational language used largely by classroom instructors. This view is an assumption which has been largely untested, however, and it is entirely possible that readers/learners read or take note of the written instructional language in textbooks. With this in mind, the two subcorpora were both treated in this study as sources of input for learners. In classifying the bundles or clusters as to discourse function and so on, we used the very workable and user friendly taxonomy elaborated by Hyland (2008), which reflects the three major metafunctions of language, ideational, textual, and interpersonal. The ideational functions are termed research-oriented by Hyland: Research-oriented – help structure experience and activity of real world. z z

Location (at the same time, at the beginning of) Procedure (the use of the, the purpose of the)

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96 z z z

Quantification (a wide range of, one of the most) Description (the structure of the, the size of the) Topic (in the United States, the currency board system)

The textual functions are labeled by Hyland as text-oriented: Text-oriented – deal with meaning of text and its organization. z z z z

Transition signals (on the other hand, in addition to the) Resultative signals (as a result of, it was found that) Structuring signals (in the present study, in the next section) Framing signals (in the case of, on the basis of)

The interpersonal functions are labeled participant-oriented: Participant-oriented – focused on the writer or the reader. z z

Stance features (may be due to, it is possible that) Engagement features (as can be seen)

After scanning the corpora for lexical clusters and classifying them according to discourse function, each of the textbooks was examined page by page for reference material, exercises, or activities which overtly focused on the lexical bundles.

Results The clusters One of the most obvious features of the lexical clusters in the corpus is the fact that of the top 40 most frequent in the entire corpus, 26 or 80 per cent are from the instructional materials, not the texts. Table 5.1 presents a list of the clusters in the instructional subcorpus, that is, the instructions and so on, not the reading texts. Not surprisingly, a remarkably high number of clusters were identified in this subcorpus, over 800, of which the top 30 most frequent are presented in Table 5.1. The clusters in the instructional subcorpus vary in structure and type, and many of them are immediately recognizable as samples of instructional language, with references to lectures, words, reading resources, class, sentences, underlined words, and so on. Table 5.2 presents a list of the lexical clusters which occurred in the textual subcorpus, that is, the reading texts. Given the nature of this subcorpus,

Lexical Clusters Table 5.1

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Lexical Clusters in the Instructional Subcorpus

At the end of

Do you think the

This part of the

Listen to the lecture

On the left with

Of the reading selection

The meaning of the

The end of the

Scan the reading to

In the case of

Rest of the class

Form of the word

The words in the

In the united states

In the box below

Of the reading resources

Of the words in

You listen to the

The rest of the

What do you think

To answer the following

With the rest of

In the following sentences

Of the underlined words

Answer the following questions

Guess the meaning of

Is the main idea

At the beginning of

Answer the questions that

And the number of

Table 5.2

Lexical Clusters in the Textual Subcorpus

On the other hand

In the form of

In the labor force

In the united states

At the beginning of

At the time of

At the same time

Is one of the

And the united states

One of the most

The size of the

The source of the

The nature of the

The beginning of the

In the level of

The end of the

According to the multistore model

A role in the

Parts of the world

Of the united states

In the northern hemisphere

Was one of the

The rest of the

Played a role in

To the multistore model At the university of

In the U.S.

In the case of

Increase the amount of

Have the right to

which consisted of a number of short texts extracted from various sources and from a broad range of topic areas, it would be expected that relatively few clusters would meet the frequency cut-off of 20/million words. In fact, 65 clusters were identified in these texts, and the top 30 most frequent are presented in Table 5.2. It is obvious from a glance that these clusters are different in lexical content from those in the instructional subcorpus presented in Table 5.1 earlier. Here we see no consistent lexical theme, and there appear to be more standard academic discourse functions attached to these clusters. For example, the most frequent cluster is on the other hand, which links contrasting information in texts. Clusters such as in the case of and a role in the are clearly recognizable as having specific textual discourse functions even when encountered in a decontextualized environment such as a list.

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The functions The instructional subcorpus Figure 5.1 is a chart illustrating the percentages of the bundles in the instructional subcorpus which were research, text, or participant oriented. As expected, most are research oriented, but over a third are participant oriented, as befits instructions and so on, directed to learners. Clusters such as listen to the lecture, do you think the, answer the following questions, and what do you think are actually directly addressed to the reader/learner. Figure 5.2 is a chart illustrating functional subcategories of clusters in the instructional subcorpus. Looking a bit closer at the clusters in the instructional subcorpus, we find that research-oriented clusters dealing with location and description – bars two and four from the left – were most common, along with participant oriented clusters of engagement, the second last bar on the right. This latter category is exemplified by the examples listed above as being directly addressed to the reader/learner. The clusters dealing with location and description include on the left with, at the end of, at the beginning of, in the box below, to answer the following, and this part of the. An examination of the cluster list and the functional categories and subcategories from the instructional subcorpus reveals lexical content and functions consistent with classroom and instructional language – questions and commands and directives addressed to the reader/learner, along with

3.1%

NA 3.1% Research-oriented 60.9% Text-oriented 1.6%

34.4%

Participant-oriented 34.4% 60.9%

1.6%

Figure 5.1 Functional Categories of Clusters in Instructional Subcorpus

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20 18 16 14 12 10 8 6 4

N/A 2 Research-oriented: Location 13 Research-oriented: Quantification 8 Research-oriented: Description 17 Research-oriented: Topic 1 Text-oriented: Framing Signal 1 Participant-oriented: Engagement 19 Participant-oriented: Stance 3

2 0

Figure 5.2 Functional Subcategories of Clusters in Instructional Subcorpus

clusters drawing attention to texts, lists, and other phenomena relevant to the instructional foci, as well as features of these foci. In some respects these types of clusters are similar to those used in classroom talk, as reported by Biber (2006), in that they tend to be more stance-oriented and discoursefocused than those in written academic text.

The textual subcorpus Figure 5.3 is a chart illustrating the percentages of the bundles in the textual subcorpus which were research, text, or participant oriented. As expected, the vast majority are research oriented, roughly a fifth are textual, and almost none are participant oriented or directed to learners. In this subcorpus, the clusters are overwhelmingly linked to the discourse of the texts themselves and the ideas they contain. The text-oriented clusters, such as on the other hand and at the time of, are virtually completely absent from the instructional subcorpus, which generally contains brief stretches of more isolated text which does not need a great deal of cohesion marked by lexical clusters. Figure 5.4 is a chart illustrating functional subcategories of clusters in the textual subcorpus. Looking more closely at the clusters in the textual subcorpus, we find that research oriented bundles of location, quantification, description and topic

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15%

3.1%

NA 3.1% Research-oriented 75.4% Text-oriented 20.0% Participant-oriented 1.5%

20.0%

75.4%

Figure 5.3 Functional Categories of Clusters in Textual Subcorpus

NA 2 20 18 16 14 12 10

Research-oriented: Location 17 Research-oriented: Quantification 9 Research-oriented: Description 10 Research-oriented: Procedure 1 Research-oriented: Topic 12

8

Text-oriented: Transition 4

6

Text-oriented: Resultative 2

4

Research-oriented: Structuring 1

2 0

Text-oriented: Framing Signal 6 Participant-oriented: Stance 1

Figure 5.4 Functional Subcategories of Clusters in Textual Subcorpus

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are most common. Given that the texts which comprise this subcorpus are drawn by the textbook authors from a wide range of original authentic sources linked to a wide range of themes, it is likely that these subcategories of functions are roughly similar to those to be found in academic writing in general. The interesting broad conclusion to be made from examining this corpus is that an extremely high number of high frequency clusters are from instructions, not reading input, and that the nature of the clusters in the instructional subcorpus is different from that of the textual subcorpus. So if frequency alone is most important, as is the common assumption in many textbooks, and if the instructional language is a source of input for learners, we could expect learners to acquire bundles such as answer the following questions, scan the reading selection or listen to the lecture possibly ahead of or instead of more intuitively useful academic language such as in the case of, on the other hand, or one of the most. In other words, classroom procedural language dominates here, if frequency is used as the sole criterion.

Lexical clusters in the instructional material As noted earlier, the texts presented in EAP material are not necessarily selected or sequenced to function as extensive sources of input. The job of a textbook writer entails establishing learning activities which exploit certain features of the texts, at times using them as exemplars of features of academic prose. With this in mind, after the identification of the lexical clusters and their functions in the corpus, the textbooks were searched in depth and all the tasks in them completed, in order to see and feel how the material might have made up for a weak set of lexical clusters by teaching or drawing attention to their important roles in discourse and communication. Each textbook was searched page by page for reference material, exercises, or activities which overtly focused on the lexical clusters. The findings are as follows:

Textbook 1: 4 skills In the case of may be used to complete one task. Is one of the, one of the few, in the United States may be used to complete one task. The source of the may be used to complete one task.

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No tasks highlight the clusters in input. No tasks require focus or practice of clusters.

Textbook 2: 4 skills Unit on compare/contrast: instruction about in contrast; text shows that on the other hand and at the same time can indicate contrast, but not highlighted. Unit on expressing purpose: instruction about in order to, so as to, so that, for the purpose of.

Textbook 3: 4 skills The end of the helps comprehension in one task. On the other hand and on the one hand help in completing one task. In the labor force is highlighted in the input in one reading task. A role in the helps with completing a written task. One of the most is highlighted as valuable in completing one reading task. With the idea of is useful in completing one reading task, but is not highlighted.

Textbook 4: 4 skills If the suggested change occurs frequently in input for a task and is valuable – but not highlighted. No tasks highlight the clusters in input. No tasks require focus or practice of clusters.

Textbooks 5 and 6: Reading and Writing focus No tasks highlight the clusters in input. No tasks require focus or practice of clusters. The picture which emerges from this examination of the pedagogical treatment of lexical clusters in the textbooks is that the textbooks authors do not exploit this aspect of language in any systematic or meaningful way. The clusters are not taught or highlighted in the instructions. Tasks in the textbooks do not draw attention to the clusters, nor to any form of formulaic

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language. In some cases certain lexical clusters are useful for learners to complete some tasks, but these clusters are not explicitly attended to by the authors. The textbooks are quite rich in lexical clusters, and both the instructional and textual subcorpora contain plenty of them. In terms of frequency, however, the instructional subcorpus contains clusters of quite high frequency which are not clearly relevant to academic reading and writing. The clusters which appear in the textual subcorpus may be very useful in academic discourse, and we may even assume that they likely are representative. However, these clusters do not occur at a high frequency and are therefore unlikely to be acquired from reading. This problem is exacerbated by the fact that this corpus is comprised of six textbooks, and the average EAP learner is likely to deal with only several textbooks over the course of an EAP programme, and therefore encounter fewer clusters or other types of formulaic sequences than we can see in this corpus. To compound the problem, in addition to the low frequency of most clusters in the textual subcorpus here, the authors do not exploit this resource in any meaningful way in the materials. From this representative sample of recent EAP textbooks, it appears that formulaic language is definitely not a priority of EAP textbook authors. They provide neither substantial input with high frequencies of lexical clusters, nor instructional support in recognizing and utilizing formulaic language.

Conclusion In general, it can be concluded that the textbooks examined in this study are not particularly effective in dealing with lexical clusters and formulaic language. The highest frequency clusters appear in the instructional material, not the texts, meaning that the types of lexical clusters which students would be most likely to encounter in these textbooks are language classroom based and instructional, not those characteristic of academic prose. Furthermore, the lexical clusters which appear in the texts in these books are not present at high frequency, and the input the learners receive is impoverished in this regard. These weaknesses in the texts and discourse structures of the material in the textbooks might have been balanced had there been tasks and activities which drew attention to the clusters and their functions. However, virtually no exercises, reference materials, or activities in these textbooks focus overtly or even implicitly on lexical bundles.

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It is clear from this small-scale general overview of formulaic language in EAP textbooks that more work is needed which focuses on classroom materials and the role of formulaic language in them. Larger scale study of corpora of EAP materials can further investigate the nature of the gap between EAP materials and the language of the academic world, examining the use of lexical clusters and bundles in texts, the types of activities and tasks which can facilitate acquisition of this aspect of language, and so on. A conscious awareness of the role played by lexical bundles in regular academic textbooks, for example, might help EAP materials designers to craft textbooks which include a focus on the relevant bundles. More research into this is needed – see the paper by Chen in the present volume for an examination of how the lexical bundles presented in EAP textbooks geared toward electrical engineering students match those in EAP materials designed specifically for electrical engineering learners. If EAP materials are to be authentic, that is, if they are to present academic language which exemplifies that which is common in the academy, then materials developers need to attend to key features of academic language. Among these features is formulaic language, with its vital role in the creation of meaning and the structure of discourse. Materials developers should provide learners with input which is rich in formulaic sequences and activities which raise awareness of and facility with these elements of language.

References Altenberg, B. (1998). On the phraseology of spoken English: The evidence of recurrent word-combinations. In A. P. Cowie (Ed.) Phraseology: Theory, analysis, and applications (pp. 101–22). Oxford: Clarendon. Bahns, J. (1993). Lexical collocations: A contrastive view. English Language Teaching Journal, 47 (1), 101–14. Bamber, B. (1983). What makes a text coherent? College Composition and Communication, 34, 417–29. Biber, D. (2006). University language. Amsterdam: John Benjamins. Biber, D., & Conrad, S. (1999). Lexical bundles in conversation and academic prose. In H. Hasselgard & S. Oksefjell (Eds.) Out of corpora: Studies in honour of Stig Johansson (pp. 181–89). Amsterdam: Rodopi. Biber, D., Conrad, S., & Cortes, V. (2004). If you look at . . . lexical bundles in academic lectures and textbooks. Applied Linguistics, 25, 371–405. Biber, D., Johansson, S., Leech, G, Conrad, S., & Finegan, E. (1999). Longman grammar of spoken and written English. London: Longman. Bolander, M. (1989). Prefabs, patterns and rules in interaction? Formulaic speech in adult learners’ L2 Swedish. In K. Hyltenstam & L. K. Obler (Eds.), Bilingualism

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across the lifespan: Aspects of acquisition, maturity, and loss (pp. 73–86). Cambridge: Cambridge University Press. Bygate, M. (1988). Units of oral expression and language learning in small group interaction. Applied Linguistics, 9 (1), 59–82. Chafe, W. (1968). Idiomaticity as an anomaly in the Chomskyan paradigm. Foundations of language, 4, 109–27. Cortes, V. (2004). Lexical bundles in published and student disciplinary writing: Examples from history and biology. English for Specific Purposes, 23, 397–423. Cortes, V., Jones, J., & Stoller, F. (2002, April). Lexical bundles in ESP reading and writing. Paper presented at TESOL Conference, Salt Lake City, Utah. Coulmas, F. (1979). On the sociolinguistic relevance of routine formulae. Journal of Pragmatics, 3, 239–66. Coulmas, F. (1981). Conversational routine. New York: Mouton Publishers. Erman, B., & Warren, B. (2000). The idiom principle and the open-choice principle. Text, 20, 29–62. Fillmore, L. W. (1979). Individual differences in second language. In C. Fillmore, D. Kempler, & W. Wang (Eds.), Individual differences in language ability and behavior (pp. 203–28). New York: Academic Press. Granger, S. (1998). Prefabricated patterns in advanced ESL writing: Collocations and formulae. In A. Cowie (Ed.), Phraseology: Theory, analysis, and applications (pp. 145–60). Oxford: Oxford University Press. Granger, S., & Paquot, M. (2008). Disentangling the phraseological web. In S. Granger & F. Meunier (Eds.), Phraseology: An interdisciplinary perspective (pp. 27–50). Amsterdam: John Benjamins. Hakuta, K. (1974). Prefabricated patterns and the emergence of structure in second language acquisition. Language Learning, 24 (2), 287–97. Harwood, N. (2005) What do we want EAP teaching materials for? Journal of English for Academic Purposes, 4 (2), 149–61. Haswell, R. H. (1991). Gaining Ground in College Writing: Tales of Development and Interpretation. Dallas: Southern Methodist University Press. Hewings, M., & Hewings, A. (2002). ‘It is interesting to note that . . . ’: A comparative study of anticipatory ‘it’ in student and published writing. English for Specific Purposes, 21, 367–83. Howarth, P. (1998). The phraseology of learners’ academic writing. In A. Cowie (Ed.), Phraseology: Theory, analysis, and applications (pp. 161–86). Oxford: Oxford University Press. Hyland, K. (2008). As can be seen: Lexical bundles and disciplinary variation. English for Specific Purposes, 27. 4–21. Hyland, K., & Hamp-Lyons, L. (2002). EAP: Issues and directions. Journal of English for Academic Purposes, 1, 1–12. Jones, M., & Haywood, S. (2004). Facilitating the acquisition of formulaic sequences. In N. Schmitt (Ed.), Formulaic sequences: Acquisition, processing and use (pp. 269–92). Amsterdam: John Benjamins. Kjellmer, G. (1991). A mint of phrases. In K. Aijmer & B. Altenberg (Eds.), English corpus linguistics: Studies in honour of Jan Svartvik (pp. 111–27). London: Longman. Manes, J., & Wolfson, N. (1981). The compliment formula. In F. Coulmas (Ed.), Conversational routine: Explorations in standardized communication situations and prepatterned speech (pp. 115–32). New York: Mouton Publishers.

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McCully, G. (1985). Writing quality, coherence, and cohesion. Research in the Teaching of English, 19, 269–82. Mel’cˇuk, I. (1998). Collocations and lexical functions. In A. P. Cowie (Ed.), Phraseology: Theory, analysis, and applications (pp. 23–53). Oxford: Clarendon. Moon, R. (1998). Frequencies and forms of phrasal lexemes in English. In A. P. Cowie (Ed.) Phraseology: Theory, analysis, and applications (pp. 79–100). Oxford: Clarendon. Nattinger, J. R., & DeCarrico, J. S. (1992). Lexical phrases and language teaching. Oxford: Oxford University Press. Oshima, A., & Hogue, A. (2004). Writing academic English (4th ed.). Montreal, QC: Pearson. Pawley, A., & Syder, F. H. (1983). Two puzzles for linguistic theory: Nativelike selection and nativelike fluency. In J. C. Richards & R. W. Schmidt (Eds.) Language and communication (pp. 191–226). New York: Longman. Peters, A. M. (1983). Units of language acquisition. Cambridge: Cambridge University Press. Schmidt, R. W. (1983). Interaction, acculturation, and the acquisition of communicative competence: A case study of an adult. In N. Wolfson & E. Judd (Eds.), Sociolinguistics and language acquisition (pp. 137–74). Rowley, MA: Newbury House. Schmitt, N., & Carter, R. (2004). Formulaic sequences in action: An introduction. In N. Schmitt (Ed.), Formuliac sequences: Acquisition, processing and use (pp. 1–22). Amsterdam/Philadelphia: John Benjamins. Scott, M. (2004). WordSmith Tools (Version 4). Oxford: Oxford University Press. Sinclair, J. (1991). Corpus, concordance, collocation. Oxford: Oxford University Press. Tannen, D. (1987). Repetition in conversation as spontaneous formulaicity. Text, 7 (3), 215–43. Williams, J. (2005). Learning English for academic purposes. Montreal, QC: ERPI. Wood, D. (2006). Uses and functions of formulaic sequences in second language speech: An exploration of the foundations of fluency. Canadian Modern Language Review, 63 (1), 13–33. Wray, A., & Perkins, M. R. (2000). The functions of formulaic language: An integrated model. Language and Communication, 20, 1–28. Wray, A. (2002). Formulaic language and the lexicon. Cambridge: Cambridge University Press. Yorio, C. (1980). Conventionalized language forms and the development of communicative competence. TESOL Quarterly, 14 (4), 433–42.

Chapter 6

An Investigation of Lexical Bundles in ESP Textbooks and Electrical Engineering Introductory Textbooks Lin Chen Carleton University

Formulaic language plays a prominent role in structuring spoken and written discourse as demonstrated in a range of studies (Nattinger & DeCarrico, 1992; Partington, 1998; Altenberg, 1998; Biber, Conrad, & Cortes, 2003, 2004; Hyland, 2008). Defined as multiword strings ‘[. . . ] stored and retrieved whole from memory at the time of use, rather than being subject to generation or analysis by the language grammar’ (Wray & Perkins, 2000, p. 1), formulaic language serves to relieve processing stress in time-demanding tasks (Wray, 2002). For example, sport commentators in live programmes rely heavily on formulaic language for the description of actions. In addition, formulaic language accomplishes pragmatic functions in spoken and written discourse. For example, in research into business dialogues, it has been found that we need to frames requests from an authority (the board of a company) in a polite way and softens the authoritative power of the commands made by the management (O’Keefe, McCarthy, & Carter, 2007). Medical writers frequently use it is/has been (often) . . . that X to introduce outside information as support and add authority to their own stances or positions (Oakey, 2002). For a systematic description of formulaic language, researchers have proposed a range of linguistic descriptors and types, including ‘lexical phrase’ (Nattinger & DeCarrico, 1992), ‘formulaic sequence’ (Wray, 2002), ‘lexical bundle’ (Biber, Johansson, Leech, Conrad, & Finegan, 1999), ‘collocation’ (Partington, 1998), and more. From among these, lexical bundle was chosen as the focus of the present study, since lexical bundles feature in significant proportions and have distinct pragmatic functions in spoken and written discourse. In the 40-million-word Longman Spoken and Written English (LSWE) Corpus, 28 percent of words in conversation and 20 percent of words in academic prose occur in three- and four-word

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lexical bundles (Biber et al., 1999). What is more, lexical bundles have been shown to fulfill specific functions of expressing stances, organizing discourse and specifying referential details in academic discourse (Biber et al., 2003, 2004). The present study focuses on lexical bundles and their pragmatic functions in electrical engineering (EE) introductory textbooks and English for specific purposes (ESP) textbooks. With the aim of investigating a gap in language use between the two types of textbooks, this study examines how lexical bundles with consistent pragmatic functions construct EE text, whether these lexical bundles are present in ESP textbooks, and whether pragmatic functions of the lexical bundles in EE textbooks are maintained in pedagogical materials.

Background of the Present Study Lexical bundles, defined as ‘sequences of word forms that commonly go together in natural discourse’ (Biber et al., 1999, p. 990), are identified mainly by the statistical feature of frequency. For example, for four-word sequences to be qualified as lexical bundles in the LSWE Corpus, Biber et al. (1999) specified that (1) the minimal cut-off frequency is five times per million words, and (2) the sequences should occur in at least five texts to avoid idiosyncrasies of individual speakers and writers. Lexical bundles are characterized by their pragmatic functions across four university registers, including classroom teaching, textbooks, conversation and academic prose (Biber et al., 2003, 2004). Biber et al. (2004) proposed a functional taxonomy, grouping four-word lexical bundles into three main categories: (1) stance bundles, (2) discourse organizers, and (3) referential bundles. Under each main category, Biber et al. (2004) identified subcategories with more specific functions. Stance bundles (e.g. are more likely to) express epistemic certainty or attitude/modality towards following propositions (see example 1). Discourse organizers (e.g. want to talk about, on the other hand) indicate the logical relationship between discourse segments, functioning as markers to introduce new topics or elaborate on current issues (see example 2). Referential bundles (e.g. those of you who, the nature of the) ‘make direct reference to the physical, temporal, and contextual context’ (Biber et al., 2003, p. 81). For example, the nature of the specifies an abstract attribute of the entity coming after (see example 3).

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1. Boys are more likely to be hyperactive, disruptive, and aggressive in class. (p. 390) 2. But, before I do that, I want to talk about Plato. (p. 392) 3. . . . students must define and constantly refine the nature of the problem. (p. 395) While the studies mentioned above investigated general language use in written and spoken registers (Biber et al., 2003, 2004), other studies have focused on language use in published research articles from a variety of disciplines (Cortes, 2004; Hyland, 2008). Disciplines in tertiary settings have their own communicative practices and norms; writers in the discipline establish appropriate reader/author relationship and precisely present propositional contents by drawing on particular lexical bundles to express their evaluation, engage readers, describe propositional facts, and organize the flow of discourse (Cortes, 2004; Hyland, 2008). For example, since biology and electrical engineering take a ‘[. . . ] linear and problemoriented approach to knowledge construction’ (Hyland, 2008, p. 19), writers of research articles in the two disciplines employ stance bundles to exert directive forces on readers by addressing them directly (e.g. we can see that, it is important that). In addition, these writers use a large amount of referential bundles for a precise description of research procedures in disciplines based on experimental research (Hyland, 2008). Writers of biology journal articles use referential bundles to specify time/location information (at the beginning of, at the University of), describe physical attributes (the depth of), or/and state quantities (a large number of) (Cortes, 2004). With the research focus on lexical bundles in general spoken/written registers or discipline-specific research articles, previous studies seem to have ignored language use in introductory textbooks of particular disciplines. Serving as an important type of texts in tertiary settings, entry-level textbooks present valid knowledge in the disciplines and offer the basis for academic lectures and evaluated tasks (exams, graded assignments, oral and written reports) (Olson, 1989; Carson, 2001). However, to date, little research has been conducted on describing how lexical bundles construct the text in introductory textbooks of different disciplines. Academic neophytes form a major reader’s group of introductory textbooks including both native and non-native English speakers. Some L2 learners simultaneously take introductory courses and preparatory ESP courses that are designed to focus on the development of discipline-specific language skills. As ESP textbooks are often the main reading materials

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for non-native speakers in English classrooms, these textbooks determine the language input that these students are immersed in and construct the basis of learning tasks in language classrooms (McDonough, 1998). The websites and prefaces of ESP textbooks explicitly state that the textbooks use authentic, discipline-specific readings as the main contents. However, it is not clear how authentic these pedagogical materials are and whether a gap exists in language use between ESP textbooks and introductory textbooks, since little empirical research has been conducted regarding this concern. Understanding how lexical bundles construct the text in introductory textbooks can help academic neophytes develop their discipline-specific literacy skills. In addition, identification of a gap in language use between ESP textbooks and discipline introductory textbooks could increase nonnative speakers’ chances of boosting discipline-specific language skills in language classrooms. Taking these factors into consideration, the present study initiates the investigation of lexical bundles in electrical engineering (EE) introductory textbooks and explores a gap in language use between ESP textbooks and EE introductory textbooks. Three main research questions are addressed: 1. What are the lexical bundles and their pragmatic functions in EE introductory textbooks? 2. Do these lexical bundles occur in ESP textbooks? 3. Do the pragmatic functions of the bundles differ in ESP textbooks?

Methodology This corpus-based study examined and compared the use of lexical bundles in EE introductory textbooks and ESP textbooks in three steps. Firstly, two corpora were set up, respectively representing EE introductory textbooks and ESP textbooks and serving as the database for textual analysis. Secondly, lexical bundles were identified in the EE textbooks. WordSmith Tools 4.0 (Scott, 2004), a computer analysis software generated frequency and distribution data of four-word sequences. Only word sequences that satisfied both frequency and distribution criteria qualified as lexical bundles (see Biber et al., 1999). Finally, WordSmith Tools 4.0 generated concordance lines or bigger stretches of text from EE textbooks and ESP textbooks, which were examined for the pragmatic functions of lexical bundles.

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The corpora For examining the gap in language use between EE textbooks and ESP textbooks, the electrical engineering introductory textbook corpus (EEITC) and the English for specific purposes textbook corpus (ESPTC) were set up. With 247 346 running words, the EEITC consists of all the 16 chapters of Basic engineering circuit analysis (Irwin, 2002), the first five chapters of Microelectronics circuits (Sedra & Smith, 2004) and a laboratory manual for an introductory course. The decision to include the two EE introductory textbooks in the EEITC was based on an online survey of the EE undergraduate programmes at three Ontario universities and an EE professor’s evaluation of representativeness of selected EE introductory textbooks. The survey of the EE undergraduate programmes indicates that the core introductory courses in the three programmes designate a total of four textbooks as course books, which offer EE novices basic concepts in circuit analysis regardless of their future specialization. A professor currently teaching an EE introductory course at one of the universities was consulted to evaluate the representativeness of the four textbooks. The professor identified two textbooks as representative, Basic engineering circuit analysis (Irwin, 2002) and Microelectronics circuits (Sedra & Smith, 2004). He considered the first textbook a good introductory course book due to its coverage of basic concepts in circuit analysis. As for the second book, he recommended the first five chapters for a one-term introductory course. The laboratory manual for Circuits and signals was included in the EEITC since the manual offered experiment instructions for students to follow in laboratory sessions. With 99 774 running words, the ESPTC draws its content from two ESP textbooks for EE students. Due to the limited supply of ESP textbooks designed for EE students on the market, only two ESP textbooks were included in the ESPTC, which are Oxford English for electronics (Glendinning & McEwan, 1993) and Oxford English for electrical and mechanical engineering (Glendinning & Glendinning, 1995). The ESP textbooks contain authentic reading materials for real communicative purposes (not created for ESP pedagogical purposes) from a wide range of sources with topics relevant to EE (e.g. electronics in the home, block diagrams and circuits).

Analytical procedures After the establishment of the two corpora, the frequency and distribution criteria for the identification of lexical bundles were set up. Since the EEITC

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is similar to the corpus used in Cortes’ (2004) study in terms of the size and specificity of language use, the same cut-off frequency was adopted, a minimum frequency of 20 occurrences per million words for four-word lexical bundles. The same distribution criterion as that of Biber et al. (1999) was followed, requiring a lexical bundle to occur in at least five texts. Concord and Wordlist, two functions of Wordsmith Tools 4.0 (Scott, 2004), were used for identification of lexical bundles and provision of concordance lines. Wordlist produced a list of four-word clusters that met the minimum cut-off frequency criterion. Concord was used to check if the clusters met the distribution criterion. Concord was also used to extract concordance lines of lexical bundles from original text, or, if necessary, longer stretches of text. The functional taxonomy by Biber et al. (2004) served as the analytic framework to determine pragmatic functions of lexical bundles in the two corpora. Only the primary function of a lexical bundle was categorized for further analysis if it had multiple functions. The final decisions about the pragmatic functions of lexical bundles were made after consultation with two university professors with expertise in applied linguistics. Lexical bundles identified in the EEITC were examined for their presence and pragmatic functions in the ESPTC. The comparison of lexical bundles and their functions in the two corpora is reported in detail below.

Results Lexical bundles in electrical engineering introductory textbooks A total of 105 four-word lexical bundles were identified in the EEITC (see Table 6.1). These bundles were categorized as stance bundles, discourse organizers, and referential bundles. Each main function subcategory

Table 6.1

Functional Classification of Four-Word Lexical Bundles in the EEITC

Categories

Lexical bundles (sequenced in a descending order of frequency)

I. Stance bundles A. Epistemic stance A1. impersonal:

the fact that the, from the fact that, to note that the, we assume that the, can be used to, can be obtained by, can be written as, can be found from, be found from the

A2. personal:

we note that the, we see that the, we find that the

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(Continued)

Categories

Lexical bundles (sequenced in a descending order of frequency)

B. Attitudinal/modality stance B1. desire

we wish to determine, wish to determine the, we wish to find, wish to find the

B2. obligation/directive

consider the circuit shown, let us determine the, let us find the

B3. intention/prediction Personal:

we will use the

II. Discourse organizers Topic elaboration/ clarification

on the other hand, as well as the, as long as the

III. Referential expressions A. Identification/focus

is known as the, is determined by the, in the case of, referred to as the, is independent of the, is defined as the

B. Specification of attributes B1. Quantity specification is equal to the, in the range of, the sum of the, is proportional to the, is the sum of, is directly proportional to, the remainder of the B2. Tangible framing attributes

the magnitude of the, the value of the, the voltage across the, in the design of, the current in the, the gain of the, the operation of the, the ratio of the, the slope of the, the frequency response of, the voltage at the, input resistance of the, the output of the, the input resistance of, the values of the, gain of the amplifier, on the value of, the current through the, of the input signal, voltage across the capacitor, the polarity of the, the voltage gain of, equivalent circuit for the, the difference between the, energy stored in the, for the network in, the relationship between the, the direction of the, voltage gain of the, an expression for the, the energy stored in, the expression for the, the amplitude of the, a plot of the, a sketch of the, value of the current, the location of the, the resistance of the, power delivered to the, a function of the, the details of the

B3. Intangible framing attributes

in terms of the, with the result that, with respect to the, a result of the, the effect of the, the use of the, the case of the, the presence of the (Continued)

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114 Table 6.1

(Continued)

Categories

Lexical bundles (sequenced in a descending order of frequency)

C. Time/place/text reference C1. Place reference

is connected to the, in series with the, in the frequency domain, in the time domain, in parallel with the, in the circuit in, in the circuit of, in the network in, present in the network, delivered to the load, be connected to the

C2. Text deixis

is of the form, it follows that the, given by the expression, in this case the, is given by the

C3. Multi-functional reference

at the end of, the end of the

has several subcategories with more specific meanings and functions. Within each functional subcategory, the lexical bundles were sequenced in a descending order of frequency.

Stance bundles in the EEITC Stance bundles in the EEITC express assessment or attitudes toward following propositions. They fall into two categories: epistemic stance bundles evaluating the knowledge status of the proposition coming after, and attitudinal/modality stance bundles expressing the authors’ attitudes towards ongoing events. As seen in Table 6.1, the majority of epistemic stance bundles are impersonal ones (e.g. the fact that the, can be used to), demonstrating that EE introductory textbook authors prefer to assess the proposition after lexical bundles without involving their personal opinions. This usage is in line with the impersonal style of discipline-specific textbooks (Conrad, 1996; Reppen, 2004), where textbook authors avoid personal stances in arguments and claim to maintain text objectivity and an authoritative control over the data and the audience (Hyland, 2002). With the form of a modal verb + passive verb, impersonal epistemic stance bundles (e.g. can be used to, can be obtained by) express logical possibility towards the following proposition, hedging the statements without blocking the possibility of potential alternatives (see example 4): (4) Ebers and Moll, two early workers in the area, have shown that this composite model can be used to predict the operation of the BJT in all of its possible modes. (ME Chapter 05) Personal epistemic bundles (e.g. we note that the, we see that the) explicitly state knowledge claims or analysis results (see example 5). Verbs such as find, see, and note guide readers’ attention to the propositional facts. In

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addition, the use of the collective pronoun we considers readers as active participants of the analysis/argument procedure. (5) In addition, we note that the solution of sinusoidal steady-state circuits would be relatively simple if we could write the phasor equation directly from the circuit description. (CA Chapter 07) Attitudinal/modality stance bundles in the EEITC mark textbook authors’ attitude towards the events in the following proposition, including desire, obligation/directive and intention (see Table 6.1). Desire bundles (e.g. we wish to determine, we wish to find) often occur in the instructions for learning tasks where the authors clarify the ends of these tasks (see example 6). Frequently appearing in imperative clauses, obligation/directive bundles (e.g. consider the circuit shown) express the writer’s stance of directing readers to participate in particular learning tasks (see example 7). The only intention bundle, we will use the, indicates the writer’s intention (see example 8). (6) We wish to find all the currents and voltages labelled in the ladder network shown in Fig. 2.30a. (CA Chapter 02) (7) For example, consider the circuit shown in Fig.2.18a. (CA Chapter 02) (8) In general, we will use the initial condition value since it is generally the one known, but the value at any instant could be used. (CA Chapter 06) Discourse organizers in the EEITC In the EEITC, only three bundles, on the other hand, as well as the, and as long as the function as discourse organizers connecting prior and coming discourse. For example, on the other hand signals the contrast between coming and prior discourse (see example 9): (9) . . . , the power delivered to the load (from the secondary side of the transformer) is less than or at most equal to the power supplied by the signal source. On the other hand, an amplifier provides the load with power greater than that obtained from the signal source. (ME Chapter 01) Referential bundles in the EEITC Three main subcategories of referential bundles were identified in the EEITC: referential identification/focus bundles, attribute specification bundles and time/place/text reference bundles (see Table 6.1), which identify important entities, specify concrete or abstract characteristics, and make reference to time, place and text. Referential identification/focus

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bundles direct readers’ attention to the noun phrases following the bundles, and thus are widely used for the purpose of introducing concepts/definitions or identifying particular situations in the EEITC. In example 10, is known as the introduces a loop technique with the term the supermesh approach. (10) One is a special loop techniques and the other is known as the supermesh approach. (CA Chapter 03) Attribute specification bundles in the EEITC specify quantity or frame tangible/intangible attributes of the noun phrases after the bundles. For example, is equal to the, a quantity specification bundle, specifies quantities of particular items as in example 11: (11) Note that the power supplied is equal to the power absorbed. (CA Chapter 01) In addition to quantity specification bundles, most of the attribute specification bundles in the EEITC frame physical or abstract characteristics of following noun phrases, correspondingly labelled as tangible or intangible attribute framing bundles. Examples of the former subcategory include the magnitude of the, the value of the, and so on, while bundles of the latter type are like in terms of the, with the result that, and so on. The magnitude of the, a tangible attribute referential lexical bundle with the highest occurrence of 63 times in the EEITC, captures magnitude as an important specification parameter for electric current, voltage, and many other variables in circuit analysis (see example 12). Intangible attribute framing bundles frame abstract properties of noun phrases after the bundles (see example 13). (12) Therefore, it is important to specify not only the magnitude of the variable representing the current, but also its direction. (CA Chapter 01) (13) Write the equation that defines the voltage relationship between the two nonreference nodes as a result of the presence of the voltage source. (CA Chapter 03) Among the total of 18 place/text/multi-functional reference bundles (See Table 6.1), 12 are place reference bundles (e.g. in series with the, in the frequency domain), which offer location information or describe the spatial connection among electrical components in electrical circuits (see example 14). The rest are text deixis bundles and multi-functional reference bundles. Text deixis bundles (e.g. is of the form, it follows that the) make reference to text or formulas, connect written texts with diagrammatic texts (e.g. formulas, diagrams), integrate two modes of text together and create meaning out of the new combination (see example 15). Multi-functional

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reference bundles refer to time or place information, depending on the original context. In example 16, at the end of in the first concordance line refers to a particular location while the bundle in the second line locates a specific time point. (14) ...we exchange the current source and parallel impedance for a voltage source in series with the impedance, as shown in Fig. 7.19a. (CA Chapter 07) (15) Since the roots are real and unequal, the circuit is overdamped, and v (t) is of the form v (t)=K1e–2t+K2e–0.5t . (CA Chapter 06) (16) 1. numerous resistors, it is recommended that the analysis begin at the end of the network opposite the terminals. (CA Chapter 02) 2. requires that the energy stored in the inductor must be the same at the end of each switching cycle. (CA Chapter 06)

Lexical bundles in ESP textbooks Table 6.2 includes the lexical bundles present in the ESPTC, which are classified into functional subcategories according to their pragmatic functions in the original text. Although the lexical bundles present in the ESP textbooks retain the same pragmatic functions as in EE introductory textbooks, the total number of bundles in the ESPTC is much lower than in the EEITC. Impersonal epistemic stance bundles in the ESPTC (e.g. the fact that the, can be used to) indicate assessment of the following proposition (see Table 6.2). For instance, the fact that the expresses certainty towards the coming proposition by emphasizing it as a fact (see example 17). (17) They stem from the fact that the tolerance extremes of a value reach the extremes of adjacent values, thereby covering the whole range without overlap. (English for electronics) The only discourse organizer in the ESPTC, as long as the, connects two propositions and clarifies the following proposition as the necessary condition for the prior proposition to happen (see example 18). (18) The armature continues turning as long as the direction of the current, and therefore its magnetic poles, keeps being reversed. (English for electrical and mechanical engineering) Identification/focus reference bundles in the ESPTC (e.g. is known as the, is determined by the) (see Table 6.2) guide readers’ attention to the noun phrases after the bundles (see example 19):

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118 Table 6.2

Functional Classification of Four-Word Lexical Bundles in the ESPTC

Categories

Lexical bundles (sequenced in the order of descending frequency)

I. Stance bundles Impersonal epistemic stance

the fact that the, from the fact that, can be used to

II. Discourse organizers Topic elaboration/ clarification

as long as the

III. Referential expressions A. Identification/focus

is known as the, is determined by the, in the case of, referred to as the

B. Specification of attributes B1. Quantity specification

is proportional to the

B2. Tangible framing attributes the magnitude of the, the value of the, in the design of, the current in the, the operation of the, the frequency response of, the output of the, the values of the, the current through the, of the input signal, the direction of the, the amplitude of the, value of the current, the resistance of the B3. Intangible framing attributes

with the result that, with respect to the, a result of the, the effect of the, the presence of the

C. Place/time reference C1. Place reference

is connected to the, in series with the, in parallel with the

C2. Time reference

at the end of, the end of the

(19) The overall effect of this phenomenon for the whole amplifier is known as the total harmonic distortion (THD). (English for electronics) Attribute specification bundles in the ESPTC (see Table 6.2) specify quantity, tangible or intangible features of particular entities. The majority of these bundles are tangible/intangible attribute framing bundles. Tangible attribute framing bundles (e.g. the magnitude of the, in the design of) specify physical characteristics of the following entities while intangible attribute framing bundles (e.g. with the result that, with respect to the) specify the abstract characteristics of particular entities. Place reference bundles (e.g. is connected to the) and time reference bundles (e.g. at the end of) in the ESPTC respectively specify spatial connections among electrical components and indicate exact time points in detailed description of research procedures.

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The comparison of lexical bundles in the ESPTC and the EEITC The comparison of lexical bundles and their pragmatic functions in the EEITC with those in the ESPTC indicates a gap in language use between the two corpora. Table 6.3 lists the percentages of functional subcategories of lexical bundles in both corpora. Figure 6.1 compares subcategory distributions of lexical bundles in the two corpora by stacking subcategory percentages of lexical bundles in the EEITC with those in the ESPTC. The data from Figure 6.1 and Table 6.3 are used to interpret how lexical bundles with pragmatic functions have different distributions in the two corpora and how in different ways these bundles structure the text in EE introductory textbooks and ESP textbooks.

Table 6.3 Percentages of Functional Subcategories of Lexical Bundles in the EEITC and ESPTC Main functional Functional subcategories of types of lexical lexical bundles bundles Stance bundles Epistemic stance Bundles: personal

Referential bundles

2.86

0

Epistemic stance bundles: impersonal

8.57

9.09

Attitudinal/modality stance bundles: desire

3.81

0

Attitudinal/modality stance bundles: directive/obligation

2.86

0

Attitudinal/modality stance bundles: intention

0.95

0

Total Discourse organizers

Percentages Percentages in the EEITC in the ESPTC

Topic clarification

19.05

9.09

2.86

3.03

Identification/focus

5.71

12.12

Attribute specification: quantity

6.67

3.03

Tangible attribute specification

40.95

42.42

7.62

15.15

10.48

9.09

Intangible attribute specification Place reference bundles Text deixis bundles

4.76

0

Time reference bundles

0

6.06

Multi-functional reference bundles Total

1.90 78.19

0 87.87

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corpora the EEITC the ESPTC

100.0%

Per cent

80.0%

60.0% 40.0%

20.0% 0.0% 1

2

3

4

5

6

7

8

9 10 11 12 13 14

Figure 6.1 Proportional Distribution of Functional Subcategories of Lexical Bundles in the EEITC and the ESPTC

The comparison of stance bundles in the EEITC and the ESPTC Stance bundles in the EEITC indicate how textbook writers construct their role as discipline experts and engage readers as participants in tasks or as observers of particular lines of argument. Textbook writers’ preference for impersonal epistemic stance bundles (can be obtained by, from the fact that) introduces shared evaluation towards particular propositions, keeps authors’ personal opinions out of the text, and thus helps to maintain objectivity and authority of the texts (Conrad, 1996; Reppen, 2004). The common use of the collective first person pronouns we and us in four other subcategories of stance bundles (we note that the, let us determine the) signposts writers’ invitations to readers as participants in the text and leads readers to become aware of the intellectual tasks or lines of arguments deemed essential by writers. Through the use of stance bundles, EE introductory textbook authors position readers as learners and present them with an integrated and

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coherent picture of well-established knowledge in the discipline. To initiate novices into the discipline norms, textbook authors apply stance bundles to exert directive forces (Hyland, 2002) on readers in three ways, mainly at the cognitive level, (1) by directing readers’ attention towards the findings or facts that writers believe are important (to note that the, we see that the), (2) by guiding readers to new lines of argument (we assume that the, from the fact that the), or (3) by directly instructing readers on the next step of an analysis procedure (we will use the, we wish to determine). Compared with the broad coverage of five subcategories of stance bundles in the EEITC, the ESPTC has only one subcategory of stance bundles (impersonal epistemic stance bundles) (see Figure 6.1). The missing four subcategories of stance bundles in the ESP textbooks mean that ESP texts do not offer novices chances to observe and explore the interpersonal relationship between readers and writers constructed by stance bundles in EE textbooks. For example, the lack of personal epistemic stance bundles and attitudinal/modality stance bundles in the ESPTC means that ESP learners are not allowed the chance to observe how these bundles (we see that the, we find that the) direct the readers’ attention to important points of knowledge or to explore how these bundles (e.g. we will use the, we wish to determine) explicitly signal novices about writers’ intentions for the next stage of the analysis procedure.

The comparison of discourse organizers in the EEITC and the ESPTC Only a few four-word lexical bundles in both the EEITC and the ESPTC serve as discourse organizers by linking prior and coming discourse in original text. The scarcity of discourse organizers in the EE introductory textbooks is in line with the research finding by Biber et al. (2004) that discourse organizing bundles are extremely rare in textbooks. Unlike the situation of real-time production (e.g. classroom teaching), authors of EE introductory textbooks tend to have more diverse lexical choices and more time to organize the text in a cohesive and coherent way without depending on recurrent lexical patterns.

The comparison of referential bundles in the EEITC and the ESPTC Accounting for 78 percent of the lexical bundles in the EEITC (see Table 6.3), referential bundles help present norms of the field and construct a body of knowledge by describing referential characteristics relevant to propositional content or context of the research process. Referential

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bundles identify important entities (is known as the, is determined by the), specify concrete/abstract attributes of variables or electrical components (the magnitude of the, with the result that), or make reference to time, location or text (at the end of, is connected to the, is of the form). Compared with the EEITC, the ESPTC lacks text deixis bundles and multi-functional reference bundles (see Figure 6.1). Text deixis bundles in the EEITC (is of the form, it follows that the) indicate interaction with readers and engage readers in textual acts (Hyland, 2002) by referring to certain texts or formulae. Furthermore, these bundles in the EEITC contribute to the construction of knowledge and the creation of a context in readers’ minds. Text deixis bundles link prior text with following text/formulas so that the new content is understood and ‘a context is created in the mind and signaled in the text in the process of its production’ (Widdowson, 2007, p. 43). In addition to text deixis bundles, multi-functional reference bundles are also absent in the ESPTC, which make both time and place references in the EEITC (e.g. at the end of). Not only does the ESPTC lack the two functional subcategories of referential bundles mentioned above, the rest of the subcategories show proportional distributions different from those in the EEITC, indicating that the two types of textbooks do not share the same focus on the presentation of referential information. In EE introductory textbooks, the relatively high percentages of quantity specification bundles (6.67 percent), text deixis bundles (4.76 percent) and place reference bundles (10.48 percent) (see Table 6.3) suggest textbook writers’ preference for describing quantity characteristics, making textual reference and depicting the physical connections among electrical components in circuit analysis. However the three subcategories of lexical bundles are either underrepresented or totally ignored in ESP textbooks. Instead the ESP textbooks seem to have an explicit interest in introducing new concepts/definitions and providing time information, evide