Effects of Data-Driven Learning on College Students of Different Grammar Proficiencies: A Preliminary Empirical Assessment in EFL Classes

Abstract

This article reports a pre–post comparative study investigating whether the data-driven learning (DDL) approach has different pedagogical effects on grammar students of English as a foreign language (EFL) with different levels of English proficiency. The study entailed a treatment group (TG) of 95 first-year undergraduates who learned grammar using DDL and a control group (CG) of 84 students who received no grammar treatment. Most of the participants were 18 or 19 years old, with only a few outliers, aged 17 or 20. The grammar performance and learning attitudes in both groups (their motivation and self-efficacy) were quantitatively examined through grammar achievement tests and a questionnaire. The data obtained from the groups were then compared at three proficiency levels: high, intermediate, and low. The results of an analysis of covariance show that in grammar performance, the proficiency levels in all the TG students rose significantly and in the posttest they outperformed their counterparts in the CG. However, neither the members of the TG nor those of the CG made any statistically significant improvement in their learning attitudes; no significant differences were found between the groups at any proficiency level. The mixed findings make an important contribution to the field, confirming that DDL is pedagogically suitable for enhancing the linguistic knowledge of university-level grammar learners, regardless of their proficiency, but warning that practitioners who treat the development of learner attitudes (e.g., motivation and self-efficacy) as important should be cautious with this approach.