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    智能时代个性化学习的现实困境、 意蕴重构与模型构建

    Realistic Dilemma, Implication Reconstruction and Model Construction of Personalized Learning in Intelligent Age

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【作      者】:

王一岩, 郑永和


【关 键 词 】:

个性化学习; 个性化自主学习; 智能教育产品; 人机协同学习; 智慧学习力; 智能教育伦理


【栏      目】:

理论探讨


【中文摘要】:

智能技术的快速发展和智能教育产品的逐渐成熟为个性化学习的实现提供了可靠保障。然而,“片面化”的智能诊断、“程式化”的教育干预、“投喂式”的服务供给、“机器主导”的教育决策阻碍了个性化学习目标的实现。要从本质上实现个性化学习,应该从“技术应用”“个体发展”和“人机关系”的视角对个性化学习进行重新审视:实现对学生的智能诊断和精准干预,强化智能技术对于教育的“赋能作用”;强调学生自我意识的唤醒、自我认知的强化和自主学习能力的提升,保障智能技术应用回归“育人”的本真;通过学生和机器的“博弈”,找到“机器智能干预”和“学生自主学习”的平衡点,实现人机协同学习生态的优化。在此基础上,围绕“学生自主学习—机器智能分析—机器智能干预—学生主观评判”构建了人机协同支持的个性化学习模型,以期勾勒智能时代个性化学习的未来图景。


【英文摘要】:

The rapid development of intelligent technology and the gradual maturity of intelligent educational products provide a reliable guarantee for the realization of personalized learning. However, "one-sided" intelligent diagnosis, "programmed" educational intervention, "feeding" service supply, "machine-led" educational decision-making hinder the realization of personalized learning goals. To realize personalized learning in essence, personalized learning should be reexamined from the perspectives of "technology application", "individual development" and "human-machine relationship": to realize the intelligent diagnosis and precise intervention of students and strengthen the "enabling effect" of intelligent technology on education; to emphasize the awakening of students' self-consciousness, the strengthening of their self-cognition and the enhancement of their autonomous learning ability, so as to ensure the application of intelligent technology to return to the essence of "human education";through the "game" between students and machines, the balance between "machine intelligent intervention" and "students' autonomous learning" is found to realize the optimization of man-machine collaborative learning ecology. On this basis, around "students' self-autonomous learning - machine intelligence analysis - machine intelligence intervention - students' subjective evaluation", a "personalized learning model supported by man-machine collaboration" is constructed, which is expected to outline the future picture of personalized learning in the intelligent era.

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