智慧教育背景下基于5E教学模式的大学英语词汇教学研究

A Study on College English Vocabulary Teaching Based on the 5E Teaching Model in the Context of Smart Education

摘要: 在智慧教育迅猛发展的时代背景下，大学英语词汇教学面临从知识灌输向能力培养转型的迫切需求。为克服传统词汇教学机械记忆、脱离语境、学用脱节等困境，本研究构建了“智慧教育背景下基于5E教学模式的大学英语词汇教学”框架(5E-CVT模型)。该模型以建构主义和情境认知理论为基础，深度融合智慧教育技术(AI工具、VR/AR、大数据平台)与5E教学模式(吸引、探究、解释、迁移、评价)，通过结构化认知路径和技术赋能语境，推动词汇深度学习。研究采用文献分析、理论推演、专家咨询和案例模拟等方法，验证了模式在促进语义网络构建、语境化迁移及多维评价方面的可行性与有效性。结果表明，5E-CVT模型不仅为词汇教学提供理论新视角，更为一线教师设计智慧教学活动提供了可操作的实践路径，对提升学生词汇应用能力和跨文化交际素养具有重要价值。未来研究将聚焦智能导学系统开发与学科特异性变体探索。

Abstract: Against the backdrop of the rapid development of smart education, college English vocabulary teaching is confronted with an urgent need to transform from knowledge indoctrination to ability cultivation. To overcome the predicaments in traditional vocabulary teaching such as mechanical memorization, detachment from context, and disconnection between learning and application, this study constructs a framework of “College English Vocabulary Teaching Based on the 5E Teaching Model in the Context of Smart Education” (the 5E-CVT model). Based on constructivism and situational cognitive theory, this model deeply integrates smart educational technologies (AI tools, VR/AR, big data platforms) with the 5E teaching model (Engage, Explore, Explain, Elaborate, Evaluate). It promotes in-depth vocabulary learning through structured cognitive paths and technology-empowered contexts. The study adopts methods such as literature analysis, theoretical deduction, expert consultation, and case simulation to verify the feasibility and effectiveness of the model in facilitating the construction of semantic networks, contextualized transfer, and multi-dimensional evaluation. The results show that the 5E-CVT model not only provides a new theoretical perspective for vocabulary teaching but also offers operable practical paths for front-line teachers to design smart teaching activities, which is of great value in improving students’ vocabulary application ability and intercultural communication literacy. Future research will focus on the development of intelligent tutoring systems and the exploration of discipline-specific variants.