Investigating the Promise of Learner Corpora
Methodological Issues
DOI:
https://doi.org/10.1558/cj.v25i2.189-206Keywords:
Learner Corpora, Automatic Classification, Lexical Analysis of Learner LanguageAbstract
Researchers working with learner corpora promise quantitative results that would be of greater practical value in areas such as CALL than those from small-scale and qualitative studies. However, learner corpus research has not yet had an impact on practices in teaching and assessment. Significant methodological issues need to be examined if results from learner corpus research are going to provide convincing results about language development. This study explored the use of the International Corpus of Learner English (ICLE) focusing on methodological issues such as identification of variation in learners' levels and statistical analysis of large numbers of predictors consisting of lexical and quantitative text features. Results show promise for the lexical and quantitative variables and machine learning statistical procedures investigated in the study. They also suggest the need for a larger corpus with more systematically sampled subcorpora from across language groups and a clear classification of the texts in terms of levels of L2 development based on objective criteria.
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