Treffer: AI 智能体能提升学习效果吗？——问题导向思维视角下学生深度问题解决能力发展效果研究.

Cultivating problem-solving abilities is an important way for education to adapt to the demand for social talents in the era of artificial intelligence (AI). However, at present, there are relatively few empirical studies on deep problem-solving capabilities, and existing research has not yet combined AI agents to explore the cultivation strategies of deep problem-solving capabilities in a human-machine collaborative environment. Based on the concept of design thinking, this paper designed a project-based teaching experiment on the empowerment of AI agents from the perspective of problem-oriented thinking around interdisciplinary themes. By adopting the quasi-experimental research method, it was aimed to explore the impact of problemoriented thinking design strategies and the application of AI agents on learners’ deep problem-solving abilities. It was found that (1) The teaching process supported by AI agents can significantly enhance learners’ deep problem-solving abilities, critical thinking, and learning engagement; (2) Teaching supported by AI agents from the perspective of problem-oriented thinking can effectively enhance learners’ depth of questioning and knowledge retention rate. The paper proposed a human-machine collaborative teaching design strategy emphasizing the zone of proximal development and the problem-thinking chain, promoting the trinity collaborative integration of teacher-student-machine interactions, and providing a new perspectives and practical guidance for the popularization and application of AI agent empowered teaching. [ABSTRACT FROM AUTHOR]

培养解决问题的能力是教育适应人工智能时代社会人才需求的重要方式。但目前关于深度问题解决能力的实证 研究较少, 已有研究尚未结合 AI 智能体探讨人机协同环境下深度问题解决能力的培养策略。文章以设计思维理念为 基础, 围绕跨学科主题设计了问题导向思维视角下 AI 智能体赋能的项目式教学实验, 采用准实验研究法, 旨在探讨 问题导向思维设计策略和 AI 智能体应用对学习者深度问题解决能力的影响。研究发现: AI 智能体支持的教学过程能 显著提高学习者的深度问题解决能力、批判性思维和学习投入度; 问题导向思维视角下 AI 智能体支持的教学能有效 提高学习者的提问深度和知识留存率。文章提出基于最近发展区和问题思维链条的人机协同教学设计策略, 推动 “师 -生-机” 三元协同融合, 为 AI 智能体赋能教学的推广应用提供新视角和实践指导。 [ABSTRACT FROM AUTHOR]

Copyright of Modern Educational Technology is the property of Editorial Board of Modern Educational Technology, Tsinghua University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)