医学类高职院校心理课程群的知识图谱构建与分层教学探索

Construction of a Knowledge Graph and Exploration Differentiated Instruction for a Psychology Course Cluster in Medical Higher Vocational Colleges

摘要: 医学类高职院校学生心理健康教育公共基础课程与心理类专业基础课程长期存在彼此割裂、资源碎片化、学习路径单一等问题。知识图谱的建设与使用为心理课程群整合提供了新的条件。本文在梳理知识图谱教育应用、人工智能赋能职业教育及心理课程群建设现状的基础上，提出“公共全域–专业匹配–临床技能”三段式知识图谱课程群框架结构，并结合SPOC资源、Obsidian可视化工具和双向细目表评测模型，讨论分层教学与精准评价的实施策略。该框架有助于打通公共基础课心理健康教育与心理类专业基础课的底层逻辑，为同类院校课程改革提供了一种可操作思路。

Abstract: In medical higher vocational colleges, the public basic course in mental health education and the foundational courses for psychology-related majors have long been characterized by mutual disconnection, fragmented resources, and a single learning pathway. The construction and application of knowledge graphs provide new conditions for integrating the psychology course cluster. Based on a review of the educational applications of knowledge graphs, AI-empowered vocational education, and the current state of psychology course cluster development, this paper proposes a three-stage knowledge graph course cluster framework: “general public domain—professional matching—clinical skills” and discusses the implementation strategies of stratified teaching and precise evaluation by combining SPOC resources, Obsidian visualization tools, and bidirectional detailed table evaluation models. This framework helps to break through the underlying logic between the public basic courses on mental health education and the basic courses for psychology-related majors, providing an operational idea for the curriculum reform of similar institutions.