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    智能体支持的教研共生体模型建构及实践策略研究

    Research on the Construction and Practical Strategies of An Intelligent Agent-supported Teaching-Research Symbiosis Model

    [浏览次数:2043]

【作      者】:

梁云真, 王 玥, 沈子琦, 郭 琳


【关 键 词 】:

智能体; 协同教研; 人智协同; 循证教研; 跨学科学习


【栏      目】:

学科建设与教师发展


【中文摘要】:

智能技术的发展历经计算智能、感知智能到今天的认知智能,而人类与智能体的协同范式也经历了从破箱之役、拟人超越到互塑共生的嬗变。教师教研领域呈现的技术精准化转型与循证科学化转型相互融合,为构建交互智能环境中的新型教研范式提供了可能。基于此,研究立足“人—智”二元主体视角,以共生理论为指导,提出了人智教研共生体理论模型,旨在通过知识创生的双链绞合、多元主体的协同交融、协同模式的创新以及循证流程的实施,共同推动教育智慧的涌现与教研成果的深度转化。并以“桥梁设计”跨学科的人智协同教研活动为实例,阐述人智教研共生体在人智共知、人智共论、人智共证、人智共创、人智共行这五个关键环节的实践策略,为人智协同教研的方法论创新提供理论与实践依据。


【英文摘要】:

The development of intelligent technology has evolved through stages of computational intelligence, perceptual intelligence, to today's cognitive intelligence, while the collaborative paradigm between humans and intelligent agents has undergone transformations from the battle against the "black box", anthropomorphic transcendence, to co-shaping and symbiosis. The convergence of technologically precise transformation and evidence-based scientific transformation in teacher teaching-research practices has created potential for establishing new teaching-research paradigms in interactive intelligent environments. Based on this, the study adopts a human-AI dual-subject perspective and employs symbiosis theory to propose a theoretical model of human-AI Teaching-Research Symbiosis(HATRS) . The model aims to promote the emergence of educational wisdom and deep transformation of teaching-research achievements through the dual-chain intertwining of knowledge creation, the synergistic integration of multiple agents, the innovation of collaborative models and the implementation of evidence-based processes. Taking the interdisciplinary human-AI collaborative teaching-research activity of "Bridge Design" as an example, this paper elaborates practical strategies for the HATRS model across five key phases: co-knowing, co-deliberating, co-verifying, co-creating, and co-implementing, thereby providing both theoretical and practical foundations for methodological innovation in human-AI collaborative educational teaching-research.

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