Volume 8,Issue 9
Research on Teaching Innovation of Machine Learning Courses Synergistically Empowered by Knowledge Graphs and Intelligent Agents
Against the background of the intelligent era, fundamental changes have taken place in talent requirements and job‑post demands. Traditional teaching modes are confronted with practical problems including fragmented knowledge, insufficient adaptability to learning situations, weak personalized guidance and single‑faceted teaching evaluation, which can hardly meet the training demands for high‑order innovative talents under intelligent‑education backgrounds. On this basis, this paper focuses on exploring teaching‑innovation strategies for machine‑learning courses synergistically empowered by knowledge graphs and intelligent agents, so as to provide theoretical support for the intelligent teaching reform and the implementation of personalized education of machine‑learning courses in colleges and universities.
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