生成式人工智能赋能《认知心理学》课程内容优化与教学创新

Generative AI-Enabled Curriculum Content Optimization and Teaching Innovation in Cognitive Psychology

摘要: 认知心理学作为心理学专业的核心课程，长期面临抽象认知机制可视化困难、经典实验范式复现成本高昂、教学评价维度单一滞后、课程内容静态固化等现实困境。生成式人工智能技术的快速演进为破解上述难题提供了新的可能。本文基于《认知心理学》课程的教学改革实践，在活动理论及DIKW模型的理论关照下，提出“认知共构”教学理念，将生成式AI定位为学习者的“认知外骨骼”与“思维伙伴”。从构建动态认知图谱、搭建AI辅助实验工坊、创设人性化认知导师、建立人机协作教研共同体四个维度，系统探索生成式AI赋能课程内容优化与教学创新的实施方案。研究设计表明，该方案有助于实现抽象机制的可视化、实验教学的普惠化、评价反馈的精准化和课程内容的动态化，为心理学类专业课程的教学改革提供了可迁移、可复制的实践路径。

Abstract: As a core course in psychology programs, Cognitive Psychology has long faced practical challenges including the difficulty of visualizing abstract cognitive mechanisms, high costs of replicating classic experimental paradigms, one-dimensional and delayed teaching evaluation, and static curriculum content. The rapid advancement of generative artificial intelligence offers new possibilities for addressing these issues. Based on the teaching reform practice of the Cognitive Psychology course, and under the theoretical frameworks of Activity Theory and the DIKW model, this paper proposes the teaching concept of “cognitive co-construction”, positioning generative AI as learners’ cognitive exoskeleton and thinking partner. A systematic solution is developed from four dimensions: constructing dynamic cognitive maps. Building AI-assisted experimental workshops, creating personalized cognitive tumors, and establishing human-machine collaborative teaching and research communities. Preliminary findings indicate that this approach facilitates the visualization of abstract mechanisms, the democratization of experimental teaching, the precision of assessment feedback, and the dynamization of curriculum content, providing a transferable and replicable practical pathway for the teaching reform of psychology major courses.