Prof. HU Guangwei, Department of English and Communication

Data-Driven Learning of Hedges in EFL: What does an Intervention Study Tell Us? Symposium on Big Language Data and International Communication. School of Foreign Languages and Literature, Shandong University, Jinan, Shandong, China, 11-12 November 2023.

Abstract
Various corpora of language samples are increasingly available today. Such corpora can greatly enrich teachers’ curricular resources and pedagogical options, offer learners a rich experience of language by providing access to authentic language data, facilitate student-centered and discovery-based learning, and consequently foster learner agency. The adoption of corpus data in the language classroom as teaching and learning resources is known as data-driven learning (DDL). In direct DDL, learners engage in computer-based activities, directly accessing corpora and concordancing software to carry out their learning activities, whereas in indirect DDL learners capitalize on corpus data indirectly through corpus-informed, paper-based activities and materials prepared in advance by their teachers. This presentation gives an overview of research on DDL and reports on a study that set out to investigate and compare the effectiveness of a direct and an indirect approach to DDL in the teaching and learning of a challenging type of lexico-grammatical resource (i.e., hedges). In light of the empirical results obtained (i.e., participants’ mastery of hedges and perceptions of the two DDL approaches), pedagogical implications are derived for EFL classrooms, and recommendations for future DDL research are also made.