数据驱动学习在学术英语词汇教学中的应用
网络出版日期: 2020-01-25
基金资助
*本文系2019年国家社科基金项目“中国理工科大学生学术英语泛在学习模式构建研究”之阶段性成果之一(19BYY232)
The Effect of Data-driven Learning on Academic English Vocabulary Teaching
本研究是以数据驱动学习(DDL)为理论基础,进行学术英语词汇教学的一次实践探索。本研究选择上海市某高校学术英语听说课堂上的非英语专业本科生为研究对象,进行为期八周的学术英语词汇DDL教学实验,并采用问卷调查和课堂观察相结合的三角验证法研究学生对该学习模式的认可度以及在实施过程中存在的局限性。研究发现DDL确实能够激发学生学术英语词汇的学习兴趣,学生对该学习模式的认可度较高;但是学生普遍认为根据语料语境猜测词义有一定的难度。因此,语料难度的把握应当引起教师的重视。在今后的学术英语词汇教学过程中,教师可以尝试使用DDL模式来提高学术英语词汇教学的创新性和科学性。
刘芹, 可庆宝 . 数据驱动学习在学术英语词汇教学中的应用[J]. 当代外语研究, 2020 , 20(1) : 58 -67 . DOI: 10.3969/j.issn.1674-8921.2020.01.008
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
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