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生成式人工智能在数字教材建设中的现实问题、改进方法与实践策略

Leveraging Artificial Intelligence Generated Content for Digital Textbooks:Challenges,Methods,and Implementation Strategies
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摘要 生成式人工智能的创新发展为数字教材建设提供了新方法与新策略,但是受技术工具论影响,生成式人工智能在数字教材应用中也还存在着“惰化学生思维、误导学生认知、淡化师生关系”等问题。针对上述问题,该研究从教学论视角分析了教材的信息化、结构化和指导化三项基本功能,通过思维链提示技术、检索增强生成技术和学习智能体等方式加强数字教材的基本功能;依据学习心理学理论将智能工具融入数字教材与教学应用中,发挥生成式人工智能优势,为学生搭建学习支架、生成个性化学习内容、提供“双师”教学指导,以智能化教材建设与应用推动教育大规模因材施教的开展。 The innovative development of Artificial Intelligence Generated Content(AIGC)offers new methods and strategies for the construction of digital textbooks.However,influenced by technological determinism,AIGC still faces issues in the application of digital textbooks,such as“making students’thinking lazy,misleading students’cognition,and diminishing the teacher-student relationship.”To address these issues,this study analyzes the three basic functions of textbooks from the perspective of educational theory:informatization,structuring,and guidance.It strengthens the functions of digital textbooks through Artificial Intelligence techniques such as chain of thought prompts,retrieval-augmented generation,and learning agents.Based on learning psychology theories,integrating intelligent tools into digital textbook teaching applications leverages the advantages of AIGC,builds learning scaffolds for students,generates personalized learning content,and provides“teacher and AI”instructional guidance,thereby promoting the large-scale implementation of personalized education through intelligent textbook construction and application.
作者 李锋 叶宜涛 程亮 Li Feng;Ye Yitao;Cheng Liang(East China Normal University,Department of Education Information Technology,Shanghai 200062;The Chinese Society of Education,Primary and Secondary Education Professional Committee on Information Technology,Beijing 100083)
出处 《中国电化教育》 CSSCI 北大核心 2024年第12期23-30,共8页 China Educational Technology
基金 人民教育出版社“十四五”规划2023年度重点课题“素养导向的信息科技生成式学习手册研制及创新应用”(课题编号:2023GHB02)研究成果。
关键词 生成式人工智能 数字教材 思维链提示技术 检索增强生成技术 学习智能体 实践策略 应用案例 AIGC digital textbooks chain of thought technology retrieval-augmented generation technology learning agents implementation strategies application case
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