摘要
将混沌学习理论与深度学习理论系统融入生成式人工智能支持的PBL全过程,构建兼具理论支撑、智能辅助与工程导向的“人机共创”实践教学模式。通过任务拆解、实时人工智能支持及多维评价机制优化PBL教学过程。以混沌学习理论为基础应对学习过程中的不确定性,以深度学习理论指导知识迁移与能力建构。教学实施中,生成式人工智能提供案例生成、任务优化、逻辑验证与反馈迭代等智能支持。通过设立实验班与对照班开展对比分析,结果显示实验班在学习参与度、协作能力、主动性、专业归属感等方面显著优于对照班,学生的适应性与创造力得到提升,课程目标达成度明显提高。该教学模式为工科教学智能化改革提供了可行路径与实践依据。
Based on chaotic learning theory and deep learning theory,a“human-AI co-creation”teaching model was developed to optimize the PBL process through task decomposition,real-time AIGC support,and a multidimensional evaluation mechanism.Chaotic learning theory provides a foundation for managing uncertainty in the learning process,while deep learning theory guides knowledge transfer and competency development.During implementation,AIGC offers intelligent support such as case generation,task refinement,logic validation,and iterative feedback,significantly enhancing students’adaptability and creativity.A comparative study involving experimental and control groups reveals that the experimental group outperforms the control group in learning engagement,collaboration skills,initiative,and professional identity,with a notable improvement in the achievement of course objectives.By systematically integrating both learning theories into the AIGC-supported PBL framework,this approach establishes a theoretically grounded,AI-assisted,and engineering-oriented instructional model,offering a viable path and practical reference for the intelligent reform of engineering education.
作者
周瑜
张其亮
王丽敏
ZHOU Yu;ZHANG Qiliang;WANG Limin(College of Electrical and Information Engineering,Jiangsu University of Science and Technology,Zhenjiang 212000,Jiangsu,China)
出处
《实验室研究与探索》
北大核心
2025年第8期166-172,共7页
Research and Exploration In Laboratory
基金
江苏省教育科学“十四五”规划重点课题(B/2021/01/79)
江苏科技大学高等教育课题(1792032403)
苏州市高等教育教学改革研究课题(202412012)。
关键词
生成式人工智能
项目式学习
人机协同
电气工程
创新教学模式
generative artificial intelligence
project-based learning(PBL)
human-AI collaboration
electrical engineering
innovative teaching model
