體驗區
|
| 篇名 |
从人机融合走向深度学习：范式、方法与价值意蕴
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| 並列篇名 |
From Human-machine Integration to Deeper Learning: Paradigm, Methodology and Value Implications
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| 作者 |
胡航(HU Hang)
、王家壹(WANG Jiayi)
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| 中文摘要 |
机器深度学习在与人类的碰撞和交互中不断突破自身功能界限，以人机融合的态势持续促进人类深度学习。本研究以人类深度学习为核心，基于人与机器在脑科学、认知心理学、计算教育学跨学科视域下的人机一致性，从内涵、实施、机制和测评四方面展现“学习者中心设计”的人机融合，提炼深度学习范式，由此聚焦人机融合走向深度学习的方法，用真实情境、跨学科、智能化、大概念、“个性化—合作”学习、思维与创新等关键词阐述其具体路径，构建人机融合的教育新生态，提高学习者“真问题解决”能力。
|
| 英文摘要 |
Machine deep learning constantly breaks through its own functional boundaries in repeated collisions and interactions with humans, and continues to promote human deeper learning with human-machine integration. This research takes human deeper learning as the core, and based on human-machine consistency from the interdisciplinary perspective, demonstrates the human-machine integration of "learner-centered design" from four aspects of connotation, implementation, mechanism, and assessment to extract the deeper learning paradigm. Therefore, it focuses on the method of human-machine integration to deeper learning, and expounds its specific path with key words such as real situations, interdisciplinary, intelligentization, big idea, personalized - cooperative learning, thinking and innovation, so as to build a new education ecology of human-machine integration and improve learners' real-problem-solving ability.
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| 頁次 |
069-079
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| 關鍵詞 |
深度学习
、跨学科
、真问题解决
、人机融合
、教育新生态
、deeper learning
、interdisciplinary
、real problem solving
、man-machine integration
、new ecology of education
、CSSCI
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| 卷期 |
30:2
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| 日期 |
202404
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| 刊名 |
開放教育研究
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| 出版單位 |
上海遠程教育集團、上海電視大學
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| DOI |
10.13966/j.cnki.kfjyyj.2024.02.008
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