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Teachers of English to Speakers of Other Languages, Inc. (TESOL) The International Corpus of Learner English: A New Resource for Foreign Language Learning and Teaching and Second Language Acquisition Research Author(s): Sylviane Granger Reviewed work(s): Source: TESOL Quarterly, Vol. 37, No. 3 (Autumn, 2003), pp. 538-546 Published by: Teachers of English to Speakers of Other Languages, Inc. (TESOL) Stable URL: http://www.jstor.org/stable/3588404 . Accessed: 13/02/2012 18:57 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Teachers of English to Speakers of Other Languages, Inc. (TESOL) is collaborating with JSTOR to digitize, preserve and extend access to TESOL Quarterly. http://www.jstor.org

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Page 1: Teachers of English to Speakers of Other Languages, Inc. (TESOL)

Teachers of English to Speakers of Other Languages, Inc. (TESOL)

The International Corpus of Learner English: A New Resource for Foreign Language Learningand Teaching and Second Language Acquisition ResearchAuthor(s): Sylviane GrangerReviewed work(s):Source: TESOL Quarterly, Vol. 37, No. 3 (Autumn, 2003), pp. 538-546Published by: Teachers of English to Speakers of Other Languages, Inc. (TESOL)Stable URL: http://www.jstor.org/stable/3588404 .Accessed: 13/02/2012 18:57

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact [email protected].

Teachers of English to Speakers of Other Languages, Inc. (TESOL) is collaborating with JSTOR to digitize,preserve and extend access to TESOL Quarterly.

http://www.jstor.org

Page 2: Teachers of English to Speakers of Other Languages, Inc. (TESOL)

The International Corpus of Learner English: A New Resource for Foreign Language Learning and Teaching and Second Language Acquisition Research

SYLVIANE GRANGER University of Louvain Louvain-la-Neuve, Belgium

* In the late 1950s, when corpus linguistics made its debut on the linguistic scene, it was a very modest enterprise in the hands of a small group of enthusiasts. Looking back on this period, Leech (1991), one of the pioneers of corpus linguistics, recalls that "for years, corpus linguis- tics was the obsession of a small group which received little or no recognition from either linguistics or computer science" (p. 25). Since that time, the group of enthusiasts has grown considerably and corpus linguistics has progressively infiltrated most-if not all-language-related disciplines. One of its major contributions has been in the field of variation studies. The diversification of corpora has given linguists a firm basis for comparing language varieties distinguished in terms of the medium (spoken vs. written), the field (general vs. specialized), and geographical status (World Englishes).

For years, foreign/second language learner varieties remained con- spicuously absent from corpus-based research. Only in the early 1990s did publishers and academics-concurrently but independently-start collecting and analyzing learner data. Two learner English corpora originated in that early period: the Longman Learners' Corpus (see Longman Corpus Network, 2003) and the International Corpus of Learner English (ICLE; see Granger, n.d.). As the latter is now being made available to the academic community (Granger, Dagneaux, & Meunier, 2002), it seems only fitting to describe the corpus in detail and, more importantly, to highlight the benefits it offers ESOL researchers and teachers.

DESIGN CRITERIA

A computer learner corpus (CLC) is an electronic collection of authentic texts produced by foreign or second language learners. Although all corpora need to be assembled according to explicit design criteria (Atkins & Clear, 1992), extra care has to be taken in collecting the data for learner corpora given the large number of variables affecting the learning/acquisition process. The ICLE is a very richly

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documented corpus: More than 20 task and learner variables have been recorded for each of the texts in the corpus through a detailed profile questionnaire completed by all learners. As shown in Figure 1, some of these variables (medium, genre, average length, learner proficiency level) were used as corpus design criteria and are therefore shared by all texts in the corpus whereas others (gender, mother tongue background, essay topic) differ from text to text. All the variables have been stored in a database and can be used by researchers as queries to compile subcorpora that match certain criteria, thus allowing for interesting comparisons (e.g., female vs. male learners, German- vs. Spanish-speaking learners).

Learner Variables

The learners who have contributed data to the ICLE have a great deal in common. All are young adults (about 20 years old) who study English in a non-English-speaking country; that is, they are EFL rather than ESL learners. They are all university undergraduates specializing in English in their second, third, or fourth year, and their level can be roughly described as advanced, although individual learners and learner groups differ in proficiency. The corpus focuses on advanced interlanguage partly because of the wish to compensate for its relative neglect in comparison with lower proficiency levels, resulting in a dearth of pedagogical materials for the advanced learner.

FIGURE 1

ICE Task and Learner Variables

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In spite of their similarities in terms of age, L2 status, and proficiency level, the learners display some significant differences, the most impor- tant one being mother tongue. The ICLE database covers 11 different mother tongue backgrounds: Bulgarian, Czech, Dutch, Finnish, French, German, Italian, Polish, Russian, Spanish, and Swedish. These groups are further subcategorized according to the geographical provenance of the learners, thus distinguishing between Dutch-speaking learners from the Netherlands and Belgium, or Finnish-speaking learners from Fin- land and Sweden. In addition, the learners' knowledge of other foreign languages is recorded. Another variable with a potentially significant impact on learner output is the amount of time learners have spent in an English-speaking country. ICLE learners differ considerably in this respect: 40% have never stayed in an English-speaking country whereas some 30% have lived in an English-speaking environment for 3 months or more. A last relevant variable is gender: The corpus contains data from both male and female learners, although the latter clearly consti- tute the majority (80%).

Task Variables

The ICLE data share a large number of task attributes. They consist exclusively of written productions of a particular genre, namely, essay writing, and represent general English rather than English for specific purposes. They are, on average, 700 words in length, unabridged. The topics are extremely varied, although the majority of them (85%) are argumentative. (Given the difficulty in collecting a sufficient number of argumentative essays, we allowed for the inclusion of a small portion- 25% at most-of literary essays in the data.) The query system allows researchers to select essays on the same or similar topics. For instance, by entering the key word women as a search term, the researcher can retrieve a subcorpus of essays on topics such as "Feminists have done more harm to the cause of women than good," "Women's Liberation," "Single women should not be allowed to have artificial insemination," and "Have real women disappeared?"

The essays also include certain differences in task settings. Recorded variables pertaining to the task are whether there was a time limit for writing, whether the essay was part of an exam, and whether the learners were allowed to use language reference tools such as grammars or dictionaries.

Size and Representativeness

The ICLE database contains 3,640 essays, totaling 2.5 million words. Each of the 11 national (i.e., Li-differentiated) varieties comprises around 330 essays totaling approximately 200,000 words. Compared with

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current very large corpora, such as the British National Corpus (100 million words) or the Bank of English (450 million words), the ICLE is very small. However, when it comes to learner language, size cannot simply be assessed in terms of the number of words. Equally important is the number of learners, and, in this respect, the ICLE, which contains writing by well over 3,000 learners, constitutes a solid empirical basis for second language acquisition (SLA) and foreign language teaching research. (There are slightly more essays than learners, as some learners contributed more than one essay without exceeding the maximum limit of 1,000 words per learner.) However, because of its limited number of words, the ICLE cannot be used for all types of linguistic investigation. It lends itself well to the analysis of high-frequency phenomena at all linguistic levels (morphology, grammar, lexis, discourse) but is unsuited for the study of infrequent linguistic items.

ANALYSIS OF THE CORPUS

Contrastive Interlanguage Analysis

The method most frequently used so far to analyze the ICLE is contrastive interlanguage analysis, an approach that consists in carrying out either a comparison of learner data with native speaker data (L2 vs. L1) or a comparison between different types of learner data (L2 vs. L2) (see Granger, 1996).

The first type of comparison makes it possible to uncover the patterns of use distinguishing learner data from native data. These fall into two categories: qualitative differences (misuse) and quantitative differences (over- and underuse). This type of analysis is greatly facilitated by text retrieval programs such as WordSmith Tools (Scott, 1996), which uses the compare lists function to give researchers immediate access to the words or phrases that are significantly under- or overused by learners. The concord and collocate display functions are also extremely valuable as they shed light on the recurring patterns or collocates that learners use, whether correctly or incorrectly.

The second type of comparison is essential to establish whether the differences uncovered are developmental or transfer related. With its wide range of mother-tongue backgrounds, the ICLE is an ideal resource to establish the importance of transfer in SLA. According to Odlin (1989), if the phenomenon of transfer is still incompletely understood, it is largely due to the heterogeneity of the data used:

A brief look at the studies cited will show considerable variation in the numbers of subjects, in the backgrounds of the subjects, and in the empirical data, which come from tape-recorded samples of speech, from student writing, from various types of tests, and from other sources. (p. 151)

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A highly controlled learner corpus such as the ICLE, with its strict design criteria and rich documentation, should go some way in answering Odlin's call for "improvements in data gathering" (p. 151).

Using this computer-aided contrastive approach, researchers have been able to uncover a wide range of patterns of under-, over-, and misuse in learner lexis, (lexico-) grammar, and discourse (see Centre for English Corpus Linguistics, 2002, for a comprehensive learner corpus bibliography based on the ICLE or other learner corpora). Among the many topics that have been analyzed so far on the basis of ICLE data are high-frequency words, Romance words, recurrent combinations, colloca- tions and formulae, prefabricated language, lexical profiling, lexical variation, adjective intensification, the verb make, progressives, passives, modality, noun phrase complexity, demonstratives, contractions, logical connectors, causal links, conjunctions, participle clauses, direct ques- tions, tense errors, lexical errors, part-of-speech tagging, and parsing.

Computer-Aided Error Analysis

Differences in frequency patterns are not the only differences be- tween learner and native corpora. Learner writing, even at an advanced proficiency level, is characterized by a much higher error rate than native writing (e.g., in the French subcorpus of the ICLE, the rate is 1 error in every 16 words). As current spelling and grammar-checking programs are not capable of detecting, let alone correcting, the majority of these errors (Granger & Meunier, 1994), error annotation is the only solution for the time being. This time-consuming but highly rewarding process consists in annotating all errors (or errors in a particular category, e.g., verb complementation or modals) in the text files using a standardized system of error tags and an error editor to speed up the process (see Dagneaux, Denness, & Granger, 1998, for a detailed description).

Once files have been error tagged, it is possible to search for any error category using a text retrieval program such as WordSmith Tools, sort the errors in various ways, and analyze them in the full context of the text. Although error tagging has not been used on a large scale yet, prelimi- nary work shows the tremendous potential of the approach (see Granger, 1999, for an analysis of verb tense errors).

ENGLISH LANGUAGE TEACHING APPLICATIONS

Learner corpus research opens up exciting pedagogical perspectives in a wide range of areas of English language teaching (ELT) pedagogy: materials design, syllabus design, language testing, and classroom meth- odology. Here I limit discussion to the first area (for the use of learner

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corpora in language testing, see Hasselgren, 2002; for classroom meth- odology, see Seidlhofer, 2002).

The link between corpus-based research and teaching is based on the idea that corpus evidence suggests "which language items and processes are most likely to be encountered by language users, and which therefore may deserve more investment of time in instruction" (Kennedy, 1998, p. 281). The area where corpus information is used most exten- sively, to the point of having become standard practice, is ELT lexicogra- phy: All monolingual learners' dictionaries are now corpus based. Work has also started on the production of corpus-informed textbooks, al- though progress in this area is rather slow (however, see Carter, Hughes, & McCarthy, 2000; Thurstun & Candlin, 1997). As regards grammar, although a corpus-based ELT grammar has yet to be written, the frequency information contained in Biber, Johansson, Leech, Conrad, and Finegan's (1999) corpus-based grammar of spoken and written English could be used-and, it is hoped, will soon be used-to design one.

Although the benefit of a corpus approach to teaching is evident, linguists are keen to point out that it is not a panacea (cf. Conrad, 1999, p. 17; McCarthy & Carter, 2001, p. 338). Perusal of native corpus data, however detailed, will never tell anything about the degree of difficulty of words and structures for learners. Learner corpora are the resource

par excellence to access this type of information. Evidence of learner under-, over-, and misuse can help materials designers and teachers select and rank ELT material at a particular proficiency level.

The benefits that can be derived from using learner corpora are apparent from the few CLC-informed ELT resources that exist. The Longman Essential Activator (LEA, 1997) is the first learners' dictionary to incorporate CLC data. The compilers of the dictionary used the Longman Learners' Corpus to find out how learners used the words covered in the LEA. They then turned the information into help boxes designed to warn learners against typical errors (Gillard & Gadsby, 1998). Although the LEA targets all EFL/ESL learners irrespective of their LI background, some CLC-based tools are tailor-made for particular groups of learners. Milton's WordPilot (n.d.) software is a writing kit especially designed for Hong Kong learners of English (see Milton, 1998). It contains error recognition exercises intended to sensitize learners to the most common errors attested in a Hong Kong learners' corpus. The program also includes a concordance tool and native corpora of specific genres intended to provide learners with authentic native examples of words with which they have difficulty. Allan's (2002) Web-based TeleNex network (see http://www.telenex.hku.hk) is designed to provide support to secondary-level English teachers in Hong Kong. The Web site contains both students' problems files that describe areas of learner difficulty

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extracted from a learner corpus and teaching implications files intended to help teachers deal with these problems in the classroom. The IWiLL language learning environment (Wible, Kuo, Chien, Liu, & Tsao, 2001) is a highly interactive tool that allows students and teachers to create and use an online database of Taiwanese learners' essays and teachers' error annotations. Other Web-based projects (see; Cowan, Choi, & Kim, 2003; Kindt & Wright, 2001) bear witness to the tremendous potential of the Internet for CLC-based ELT applications.

Although the ICLE has not yet resulted in concrete ELT resources, its tremendous potential in this respect is obvious. Thanks to its differen- tiation of mother tongue backgrounds, users can distinguish problem areas shared by all learners at an advanced level from those that are specific to a particular learner group and can fine-tune teaching materi- als accordingly.

CONCLUSION

In the preface to the first volume devoted to learner corpora, Leech (1998) states that "the concept of a learner corpus is an idea 'whose hour' has come" (p. xvi). At the time, however, most efforts were still expended on collecting data, establishing methodologies for learner corpus research, and trying them out in various case studies. The release of a learner corpus such as the ICLE marks the beginning of a new stage in the evolution of learner corpus research. The time has come to use the resource on a wider scale in both SLA and ELT.

On a more theoretical level, the ICLE data can be used alongside other data types of a more experimental nature to give SLA theories a more solid empirical foundation, in particular as regards the important question of LI transfer. On a practical level, the ICLE can help produce more learner-aware pedagogical material designed for advanced EFL learners in general or focused on the needs of one national learner population.

ACKNOWLEDGMENTS

I acknowledge the support in this research provided by the Belgian National Scientific Research Fund.

THE AUTHOR

Sylviane Granger is a professor of English language and linguistics and director of the Centre for English Corpus Linguistics at the University of Louvain. Her edited publications include Learner English on Computer (Longman, 1998) and Computer Learner Corpora, Second Language Acquisition and Foreign Language Teaching (with J. Hung and S. Petch-Tyson; Benjamins, 2002).

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REFERENCES

Allan, Q. G. (2002). The TELEC Secondary Learner Corpus: A resource for teacher development. In S. Granger, J. Hung, & S. Petch-Tyson (Eds.), Computer learner corpora, second language acquisition and foreign language teaching (pp. 195-211). Amsterdam: Benjamins.

Atkins, S., & Clear, J. (1992). Corpus design criteria. Literary and Linguistic Computing, 7(1), 1-16.

Biber, D., Johansson, S., Leech, G., Conrad, S., & Finegan, E. (1999). Longman grammar of spoken and written English. Harlow, England: Longman.

Carter, R., Hughes, R., & McCarthy, M. (2000). Exploring grammar in context. Cambridge: Cambridge University Press.

Centre for English Corpus Linguistics. (2002). List of publications. Retrieved May 22, 2003, from http://juppiter.fltr.ucl.ac.be/FLTR/GERM/ETAN/CECL/publications .html

Conrad, S. (1999). The importance of corpus-based research for language teachers. System: An International Journal of Educational Technology and Applied Linguistics, 27, 1-18.

Cowan, R, Choi, H. E., & Kim, D. H. (2003). Four questions for error diagnosis and correction in CALL. CALICO Journal, 20, 451-463.

Dagneaux, E., Denness, S., & Granger, S. (1998). Computer-aided error analysis. System: An International Journal of Educational Technology and Applied Linguistics, 26, 163-174.

Gillard, P., & Gadsby, A. (1998). Using a learners' corpus in compiling ELT dictionaries. In S. Granger (Ed.), Learner English on computer (pp. 159-171). London: Addison Wesley Longman.

Granger, S. (1996). From CA to CIA and back: An integrated approach to computerized bilingual and learner corpora. In K. Aijmer, B. Altenberg, & M. Johansson (Eds.), Languages in contrast (Lund Studies in English 88, pp. 37- 51). Lund, Sweden: Lund University Press.

Granger, S. (Ed.). (1998). Learner English on computer. London: Addison Wesley Longman.

Granger, S. (1999). Use of tenses by advanced EFL learners: Evidence from an error- tagged computer corpus. In H. Hasselgard & S. Oksefjell (Eds.), Out of corpora: Studies in honour of StigJohansson (pp. 191-202). Amsterdam: Rodopi.

Granger, S. (n.d.). International Corpus of Learner English. Retrieved May 22, 2003, from http://www.fltr.ucl.ac.be/fltr/germ/etan/cecl/Cecl-Projects/Icle/icle.htm

Granger, S., Dagneaux, E., & Meunier, F. (Eds.). (2002). The international corpus of learner English: Handbook and CD-ROM. Louvain-la-Neuve, Belgium: Presses Universitaires de Louvain. (Available from http://www.i6doc.com)

Granger, S., Hung,J., & Petch-Tyson, S. (Eds.). (2002). Computer learner corpora, second language acquisition and foreign language teaching. Amsterdam: Benjamins.

Granger, S., & Meunier, F. (1994). Towards a grammar checker for learners of English. In U. Fries & G. Tottie (Eds.), Creating and using English language corpora (pp. 79-91). Amsterdam: Rodopi.

Hasselgren, A. (2002). Learner corpora and language testing: Smallwords as markers of learner fluency. In S. Granger, J. Hung, & S. Petch-Tyson (Eds.), Computer learner corpora, second language acquisition and foreign language teaching (pp. 143- 173). Amsterdam: Benjamins.

Kennedy, G. (1998). An introduction to corpus linguistics. London: Longman. Kindt, D., & Wright, M. (2001). Integrating language learning and teaching with the

construction of computer learner corpora. Retrieved May 22, 2003, from http://www .nufs.ac.jp/~dukindt/pages/SOCCpapers.html

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Leech, G. (1991). The state of the art in corpus linguistics. In B. Altenberg & K. Aijmer (Eds.), English corpus linguistics (pp. 8-29). London: Longman.

Leech, G. (1998). Learner corpora: What they are and what can be done with them. In S. Granger (Ed.), Learner English on computer (pp. xiv-xx). London: Addison Wesley Longman.

Longman Corpus Network. (2003). The Longman learners' corpus. Retrieved May 22, 2003, from http://www.longman-elt.com/dictionaries/corpus/lcleam.html

Longman essential activator. (1997). Harlow, England: Addison Wesley Longman. McCarthy, M., & Carter, R. (2001). Size isn't everything: Spoken English, corpus, and

the classroom. TESOL Quarterly, 35, 337-340. Milton, J. (1998). Exploiting LI and interlanguage corpora in the design of an

electronic language learning and production environment. In S. Granger (Ed.), Learner English on computer (pp. 186-198). London: Longman.

Milton, J. (n.d.). WordPilot [Computer software]. (Available from http://home .ust.hk/~autolang/download_WP.htm)

Odlin, T. (1989). Language transfer: Cross-linguistic influence in language learning. Cambridge: Cambridge University Press.

Scott, M. (1996). WordSmith Tools [Computer software]. Oxford: Oxford University Press.

Seidlhofer, B. (2002). Pedagogy and local learner corpora: Working with learning- driven data. In S. Granger, J. Hung, & S. Petch-Tyson (Eds.), Computer learner corpora, second language acquisition and foreign language teaching (pp. 213-234). Amsterdam: Benjamins.

Thurstun, J., & Candlin, C. (1997). Exploring academic English: A workbook for student essay writing. Sydney, Australia: National Centre for English Language Teaching and Research.

Wible, D., Kuo C.-H., Chien, F.-Y., Liu, A., & Tsao, N.-L. (2001). A Web-based EFL writing environment: Integrating information for learners, teachers, and re- searchers. Computers and Education, 37, 297-315.

The Multimedia Adult ESL Learner Corpus

STEPHEN REDER, KATHRYN HARRIS, and KRISTEN SETZLER Portland State University Portland, Oregon, United States

* This report describes an innovative corpus project that will add several

important dimensions to the emerging connections between corpus linguistics and TESOL. A multimedia learner corpus, the Multimedia Adult ESL Learner Corpus (MAELC), is being collected within an adult ESL instructional environment. This Lab School environment (see

http://www.labschool.pdx.edu) is jointly operated by the Applied Lin-

guistics Department at Portland State University and Portland Commu- nity College, an adult ESL provider. Low-level adult ESL classrooms within a regular program are continuously recorded with multiple video cameras and microphones. By the end of the 5-year project period

Leech, G. (1991). The state of the art in corpus linguistics. In B. Altenberg & K. Aijmer (Eds.), English corpus linguistics (pp. 8-29). London: Longman.

Leech, G. (1998). Learner corpora: What they are and what can be done with them. In S. Granger (Ed.), Learner English on computer (pp. xiv-xx). London: Addison Wesley Longman.

Longman Corpus Network. (2003). The Longman learners' corpus. Retrieved May 22, 2003, from http://www.longman-elt.com/dictionaries/corpus/lcleam.html

Longman essential activator. (1997). Harlow, England: Addison Wesley Longman. McCarthy, M., & Carter, R. (2001). Size isn't everything: Spoken English, corpus, and

the classroom. TESOL Quarterly, 35, 337-340. Milton, J. (1998). Exploiting LI and interlanguage corpora in the design of an

electronic language learning and production environment. In S. Granger (Ed.), Learner English on computer (pp. 186-198). London: Longman.

Milton, J. (n.d.). WordPilot [Computer software]. (Available from http://home .ust.hk/~autolang/download_WP.htm)

Odlin, T. (1989). Language transfer: Cross-linguistic influence in language learning. Cambridge: Cambridge University Press.

Scott, M. (1996). WordSmith Tools [Computer software]. Oxford: Oxford University Press.

Seidlhofer, B. (2002). Pedagogy and local learner corpora: Working with learning- driven data. In S. Granger, J. Hung, & S. Petch-Tyson (Eds.), Computer learner corpora, second language acquisition and foreign language teaching (pp. 213-234). Amsterdam: Benjamins.

Thurstun, J., & Candlin, C. (1997). Exploring academic English: A workbook for student essay writing. Sydney, Australia: National Centre for English Language Teaching and Research.

Wible, D., Kuo C.-H., Chien, F.-Y., Liu, A., & Tsao, N.-L. (2001). A Web-based EFL writing environment: Integrating information for learners, teachers, and re- searchers. Computers and Education, 37, 297-315.

The Multimedia Adult ESL Learner Corpus

STEPHEN REDER, KATHRYN HARRIS, and KRISTEN SETZLER Portland State University Portland, Oregon, United States

* This report describes an innovative corpus project that will add several

important dimensions to the emerging connections between corpus linguistics and TESOL. A multimedia learner corpus, the Multimedia Adult ESL Learner Corpus (MAELC), is being collected within an adult ESL instructional environment. This Lab School environment (see

http://www.labschool.pdx.edu) is jointly operated by the Applied Lin-

guistics Department at Portland State University and Portland Commu- nity College, an adult ESL provider. Low-level adult ESL classrooms within a regular program are continuously recorded with multiple video cameras and microphones. By the end of the 5-year project period

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