Innovation in AI-Enabled Interdisciplinary Teaching Modes and Effect Evaluation
Abstract
Artificial intelligence (AI) technology is profoundly enabling the innovation of interdisciplinary teaching modes through such dimensions as reconstructing knowledge connection paths, optimizing teaching scenario design, and innovating evaluation systems. Based on typical cases at home and abroad, and combining the characteristics of AI technology with educational theories, this study proposes a four-dimensional innovation model of “dynamic generation of knowledge graphs - integration of virtual and real scenarios - adaptation of personalized learning paths - multimodal evaluation and feedback”.
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