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The Effect of Data-driven Learning on Academic English Vocabulary Teaching
This study is a practical exploration of academic English vocabulary teaching based on data-driven learning (DDL). DDL (Tribble & Jones 1990; Stevens 1991), based on a corpus index, is a form of computer-assisted instruction that encourages students to actively understand the meaning and usage patterns of vocabulary by observing real corpus. The authors of this study adopted a convenient sampling method to select non-English major undergraduates in the academic English listening and speaking class of a university in Shanghai as research participants, and conducted an eight-week academic English vocabulary teaching experiment by using DDL. The triangulation method combining questionnaire survey and classroom observation was used to study the acceptance of DDL and the limitations in the implementation process. Findings showed that DDL could really stimulate students’ interest in academic English vocabulary learning, and it was highly recognized by students. But students also believe that sometimes it is difficult to guess word meaning from corpus context. Therefore, the difficulty of corpus should attract the attention of teachers. In the future academic English vocabulary teaching, teachers can use DDL mode to improve the innovation and scientificalness of academic English vocabulary teaching.
Key words： academic English; data-driven learning; vocabulary teaching
LIU Qin, KE Qingbao . The Effect of Data-driven Learning on Academic English Vocabulary Teaching[J]. Contemporary Foreign Languages Studies, 2020 , 20(1) : 58 -67 . DOI: 10.3969/j.issn.1674-8921.2020.01.008
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