基于动态词汇语义网络模型的数据驱动教学行动研究

An Action Research of Data-Driven Teaching Based on Dynamic Lexical-Semantic Network Model

摘要: 学习者的词汇语义网络在课堂教学与自主学习中的协同构建是高等教育阶段英语教学的经典研究议题之一。本文通过两轮教学行动研究，探讨了动态词汇语义网络模型在数据驱动教学中的实施方案及有效性。基于自建语料库，形成不同主题的动态词汇语义网络模型。设计课前、课中、课后、自主学习等环节的输入及产出任务，对应英语学科能力培养要求，引导学习者主动构建并拓展词汇语义网络，结合问卷调查对教学成效进行评价。结果表明，教师在数据驱动教学中需关注课上与课下词汇习得途径的有效衔接，加强任务产出频率及评价，以促进学习者词汇能力的长期发展。

Abstract: Building learners’ lexical-semantic network (LSN) through classroom teaching and self-learning has been one of the major topics of research in college English teaching. This study proposes a teaching plan of using dynamic LSN in data-driven teaching and discusses its validity through 2 rounds of action research. Specifically, dynamic LSNs for different topics were constructed based on a self-constructed corpus. The present study designed input and output tasks for enhancing learners’ English disciplinary competency during pre-class, in-class, after-class and self-learning periods, where learners were supposed to develop and expand their own LSNs. Questionnaires were then distributed to evaluate the outcome of this teaching plan. Results reveal that instructors need to focus on the consistency of strategies for vocabulary acquisition in and after class, increase learners’ productive frequency and corresponding evaluation so as to boost long-term development of learners’ lexical competence.