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基于任务导向的人工智能基础通识课混合式教学
Task-oriented blended teaching of AI fundamental general education courses
【摘要】 针对传统人工智能基础通识课教学目前存在的问题,提出将人工智能“知识—模型—案例”贯通的创新人才培养路径,阐述如何开展AI对话式教学、案例教学、翻转课堂等多维度混合式教学,如何由低阶到高阶进行知识设计、模型案例设计和应用评价,以更好地激发学生从导知识、导应用到懂原理、懂应用,最后介绍具体实践,说明教学实践取得的成效。
【Abstract】 As for the increasing issues in traditional AI foundational general education courses such as the knowledge-acquisition-centric approach,teaching methods, and learning pathways, we propose an innovative talent cultivation path that integrates AI knowledge, models, and cases, while we design and implement a multidimensional blended teaching approach incorporating AI conversational teaching, case-based teaching, and flipped classrooms. Also, we elaborate on how to design low-to-high-order knowledge structures, model-case frameworks, and application evaluations in the context of AI, thereby better motivating students to promote from knowledge derivation, and application derivation to understanding principles and practical implementation. Finally, specific practices are introduced to demonstrate the achieved teaching outcomes.
【Key words】 large language model; artificial intelligence background; model-case design; innovative talent cultivation;
- 【文献出处】 计算机教育 ,Computer Education , 编辑部邮箱 ,2026年02期
- 【分类号】G642;TP18-4
- 【下载频次】111