Automatic Analysis of Constructional Diversity as a Predictor of EFL Students’ Writing Proficiency
Haerim Hwang, Hyunwoo Kim
Abstract
Abstract One of the important components in second language (L2) development is to produce clause-level units of form–meaning pairings or argument structure constructions. Based on the usage-based constructionist approach that language development entails an ability to use more diverse, more complex, and less frequent constructions, this study tested whether constructional diversity and complexity predict L2 learners’ writing proficiency. Using a natural language processing tool called the Constructional Diversity Analyzer (CDA), we analyzed 3,284 essays produced by college EFL students in terms of the proportion of individual constructions and their diversity. Results from regression analyses showed that constructional diversity reliably predicted learner proficiency: essays with higher scores contained more diverse constructions. We also found that less frequent and more complex constructions made a stronger contribution to predicting the written proficiency levels. Based on the findings, we argue for the validity of constructional diversity and the use of individual constructions as reliable predictors of L2 writing proficiency and propose the application of the CDA for L2 writing assessment and instruction.