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    人工智能教育社会实验的理论基础与实践框架

    Theoretical Basis and Practical Framework of Social Experiment in Artificial Intelligence Education

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【作      者】:

鲍婷婷, 柯清超, 马秀芳


【关 键 词 】:

社会实验; 人工智能教育; 教育风险防控


【栏      目】:

教育信息化


【中文摘要】:

2021年我国启动了“国家智能社会治理实验基地”的建设工作,开展面向人工智能教育领域的社会实验是其重点部署内容之一,以期超前研判智能教育的发展规律与风险挑战。围绕如何正确认识与科学推进人工智能教育社会实验的现实问题,文章立足于技术社会学视角,分析了传统实验、教育准实验、教育社会实验的异同,阐释了人工智能教育社会实验的核心内涵,论述了人工智能教育社会实验的本体论、认识论、方法论与价值论等理论基础,通过剖析人工智能与教育的融合路径与理论,认为人工智能教育社会实验研究的实践进路包括:微观层面应重点研究人机复合体认知、人机协同等场景中技术对个体适应性的影响;中观层面应重点研究智能学习环境、人机协同教学模式、智能学习测评等场景对学校教育体系的影响;宏观层面应重点研究资源配置、数字治理、教育公平等场景对社会制度与政策的影响,从而推动智能时代教育的高质量发展。


【英文摘要】:

In 2021, China launched the construction of the "National Intelligent Social Governance Experimental Base", and social experiments in the field of artificial intelligence education are one of its key deployment elements, with a view to studying the development rules and risk challenges of intelligent education ahead of time. Focusing on the practical problems of how to correctly understand and scientifically promote the social experiment in artificial intelligence education, this paper, based on the perspective of technological sociology, analyzes the similarities and differences among traditional experiments, quasi-experiments and social experiments in education, explains the core connotation of the social experiment in artificial intelligence education, and discusses the theoretical basis of ontology, epistemology, methodology and axiology of it. By analyzing the integration path and theory of artificial intelligence and education, it is believed that the practical progression of social experiment research on artificial intelligence education includes: the micro-level should focus on the impact of technology on individual adaptability in scenarios such as human-computer complex cognition and human-computer collaboration; the meso-level should focus on the impact of scenarios such as intelligent learning environments, human-computer collaborative teaching models, and intelligent learning assessment on the school education system; the macro-level should focus on the impact of scenarios such as resource allocation, digital governance and educational equity on social systems and policies, so as to promote the high-quality development of education in the intelligent era.


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人工智能教育社会实验的理论基础与实践框架

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