【作 者】：
董 艳， 陈 辉， 于 浩
【关 键 词 】：
跨学科主题学习； 数智技术； 数智赋能； 跨学科教育； 评价
【栏 目】：
课程与教学
【中文摘要】：
以生成式人工智能为代表的新一代数智技术为跨学科教育的新质发展带来广袤机遇。研究从审视跨学科主题学习的现存问题出发，发现突出问题包括学科整合拼盘化与任务设计浅散化、活动组织形式单一与空间资源受限、评价方式单一与评价标准模糊。针对这些问题，研究接着从内容增强、场景拓展和证据生成三个层面剖析了数智技术赋能跨学科主题学习的内在机理。最后，研究提出了数智赋能跨学科主题学习的设计、实施与评价的关键路径。在设计路径方面，搭建“跨学科教学设计”教育智能体，形成人机协同的跨学科教学设计模式；在实施路径方面，打造跨学科智慧教学空间，丰富教学资源供给，形成多样态的跨学科主题学习活动组织形式；在评价路径方面，坚持素养导向评价，借由数智技术赋能实现循证跨学科教学评价。研究对切实推进跨学科教育的数智化转型与新质发展提供理论与实践参考。
【英文摘要】：
The new generation of digital intelligence technologies, represented by generative artificial intelligence, has brought vast opportunities for the new quality development of interdisciplinary education. Starting from examining the existing problems in interdisciplinary thematic learning, the study identifies the prominent problems include the superficial integration of disciplines and the fragmentation of task design, the monotony of activity organization and the limitation of spatial resources, as well as the singularity of evaluation and the ambiguity of evaluation criteria. In response to these issues, the study then delves into the intrinsic mechanism of digital intelligence technologies empowering interdisciplinary thematic learning from three perspectives: content enhancement, scenario expansion and evidence generation. Finally, the study proposes key pathways for the design, implementation and evaluation of digital intelligence empowering interdisciplinary thematic learning. In terms of design pathways, it suggests the establishment of an "interdisciplinary instructional design" educational agent to form a human-machine collaborative interdisciplinary instructional design model. For implementation pathways, it advocates for the creation of smart interdisciplinary teaching spaces, so as to enrich the supply of teaching resources and develop diverse forms of interdisciplinary thematic learning activities. Regarding evaluation pathways, it emphasizes the importance of competency-oriented evaluation, leveraging digital intelligence technologies to enable evidence-based interdisciplinary teaching evaluation. The study provides both theoretical and practical references for effectively advancing the digital intelligence transformation and new quality development of interdisciplinary education.