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    人机智能协同的作业辅导:动因、框架及应用研究

    Human-Machine Intelligence Collaboration for Homework Tutoring: Motivation, Framework and Application

    [浏览次数:15887]

【作      者】:

夏雪莹, 李玉斌, 王旭光, 姚巧红


【关 键 词 】:

智能作业辅导; 人机智能协同; 学习分析; 框架构建


【栏      目】:

课程与教学


【中文摘要】:

在“双减”政策背景下,研究如何开发摆脱答案供给式辅导模式,强化高阶思维发展、元认知调节与情感激励作用的新一代智能作业辅导系统框架成为当前智能学习系统需要突破的关键性技术之一。文章针对当前智能作业辅导系统关键环节存在的学习者多元隐性特征难以挖掘、高阶思维能力难以引导与培养、辅导策略属性缺乏精细设计以及辅导效果验证数据支撑不足等问题,采用人机智能协同的技术破解路线,构建了以学习者多元数据和作业题面信息智能采集为起点、专家经验与机器智能协同决策为基础、融入元认知调节策略,结合辅导策略知识图谱,以促进学习者高阶思维能力发展的新一代智能作业辅导系统框架,自动生成服务于不同学习者的以知识掌握与思维发展并重为目标的个性化辅导方案,并在原型设计基础上结合实例进行应用分析,以推动作业辅导精准化、智能化实现。


【英文摘要】:

In the context of the "double reduction" policy, the research on how to develop a new generation of intelligent homework tutoring system framework that is free from the answer-supply tutoring mode and strengthens the role of higher-order thinking development, metacognitive regulation and emotional motivation becomes one of the key technologies that need to be broken through in the current intelligent learning system. This paper addresses the problems that exist in the key aspects of the current intelligent homework tutoring system, such as the difficulty in tapping learners' multiple implicit characteristics, the difficulty in guiding and cultivating higher-order thinking ability, the lack of fine-grained design of tutoring strategy attributes and insufficient data support for tutoring effect verification, adopts the technical breakthrough route of human-machine intelligence collaboration, and builds a new generation of intelligent homework tutoring system framework based on the intelligent collection of learners' multiple data and homework question information, the collaborative decision-making between expert experience and machine intelligence, the integration of metacognitive adjustment strategies, and the knowledge graph of tutoring strategies to promote the development of learners' higher-order thinking ability. The system automatically generates personalized tutoring solutions for different learners with the goal of both knowledge mastery and thinking development, and conducts application analysis based on the prototype design with examples to promote the accurate and intelligent implementation of homework tutoring.

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