On the construction of a knowledge Graph- and AIGC-empowered multimodal interactive teaching model for college English
“知识图谱+AIGC”赋能大学英语课程多模态交互教学模式构建研究

摘要

本文结合一学年课堂试点、面向师生的问卷访谈一手数据，针对日常教学中频繁遇到的知识体系碎片化、课堂交互浅层化、分层教学难以落地、考核评价单一化等缺点，以多模态话语分析理论、建构主义学习理论为理论支撑，挖掘知识图谱结构化表征与AIGC多模态智能生成的协同互补优势，搭建覆盖课前、课中、课后全流程的闭环多模态交互教学模式。研究结合本校智慧校园硬件、智能教育专项扶持政策与跨学科教研团队资源，阐释模式内在运行逻辑、课堂实施流程与五维动态评价方案，同时从技术平台、师资培育、教学评价层面提出长效落地保障策略。本研究形成适配应用型本科大学英语课堂的智能化教学范式，以期为大学英语教学的同行提供些许参考价值。

Abstract

Drawing on a one-academic-year classroom pilot and first-hand data collected through questionnaires and interviews with teachers and students, this study addresses several persistent problems in everyday teaching, including fragmented knowledge structures, superficial classroom interaction, difficulties in implementing differentiated instruction, and overly uniform assessment methods. Grounded in multimodal discourse analysis and constructivist learning theory, the study explores the complementary strengths of knowledge graphs in structured knowledge representation and AIGC in multimodal intelligent content generation, and develops a closed-loop multimodal interactive teaching model covering the entire process of pre-class preparation, in-class instruction, and post-class consolidation. Taking into account the university’s smart-campus infrastructure, special support policies for intelligent education, and interdisciplinary teaching-research resources, the study explains the model’s internal operating mechanism, classroom implementation procedures, and five-dimensional dynamic assessment framework. It also proposes long-term implementation strategies in terms of technological platforms, teacher professional development, and teaching evaluation. The study ultimately develops an intelligent teaching paradigm tailored to College English classrooms in application-oriented undergraduate institutions, with the aim of providing useful reference for fellow College English educators.