Innovation and Optimization Approaches of College English Vocabulary Teaching Enabled by Generative Artificial Intelligence

Abstract

According to the Input-Output Hypothesis, the problems of shallow processing, homogeneity and decontextualisation in the traditional method of teaching college English vocabulary will be addressed in this paper to improve students' pragmatic competence. Based on the above, this paper will explore how to integrate the features of generative artificial intelligence (Gen AI) in the teaching of college English vocabulary. To address the problems in the current teaching of vocabulary, Generative AI will be used in this paper to create various contexts dynamically and provide personalised modifications and prompts for feedback. Then, it will introduce new teaching models to help students learn new words better, build an optimisation system for the stages of teaching, human-AI collaborative teaching and dynamic vocabulary assessment, etc., to create a new teaching-learning-assessment model. The above results can help promote the digital and intelligent transformation of college English vocabulary teaching, and some practical suggestions for further research on the application of generative AI in foreign language education are also given here.