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认知闭合反映了学习者在认知过程中为避免模糊与不确定状态的动机,已有研究证实认知闭合状态对学习者的外显行为表现与个体动机具有显著影响,但在线学习环境下的不同认知闭合学习者积极~/消极行为影响与对应激励策略仍未明晰。因此,该研究针对在线学习中的过程数据,结合相关性分析与聚类分析将90名学习者分为低认知闭合、积极高认知闭合与消极高认知闭合三类,从时间与行为维度探究其在线学习行为模式特征与差异,并基于机器学习与大模型智能体为其中的62名消极高认知闭合学习者提供干预,形成激励策略并开展准实验研究。结果表明,所提动机激励策略能有效改善高认知闭合学习者的消极在线学习行为状态,并对其内在动机、学习绩效方面均有积极影响,为数智赋能下的认知闭合模式解析与在线学习提质增效提供理论参考与实践指导。
Abstract：Cognitive closure reflects learners' motivation to avoid ambiguity and uncertainty during cognitive processes. Existing research has confirmed that the state of cognitive closure significantly influences learners' external behavioral performance and individual motivation. However, the positive or negative behavioral impacts of learners with different cognitive closure states in online learning environments and the corresponding motivational strategies remain unclear. Therefore, this study focuses on process data in online learning. By combining correlation analysis and cluster analysis, 90 learners were classified into three groups: low cognitive closure, positive high cognitive closure, and negative high cognitive closure. The characteristics and differences in their online learning behavior patterns were explored from temporal and behavioral dimensions. Subsequently, interventions based on machine learning and large model intelligent agents were provided to 62 learners with negative high cognitive closure, leading to the formulation of motivational strategies and the implementation of a quasi-experimental study. The results indicate that the proposed motivational strategies effectively improve the negative online learning behavior states of learners with high cognitive closure and positively influence their intrinsic motivation and learning performance. This study provides theoretical references and practical guidance for analyzing cognitive closure patterns in the context of digital intelligence and enhancing the quality and efficiency of online learning.
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基本信息:
中图分类号:G434
引用信息:
[1]王希哲,黄欣欣,黄昌勤.数智赋能下在线学习者认知闭合行为模式分析与激励策略研究[J].中国电化教育,2026,No.472(05):95-103.
基金信息:
国家自然科学基金面上项目“基于大模型多智能体协同的在线学习者认知异常归因与适性引导研究”(项目编号:62577051); 浙江省哲学社会科学规划年度课题“多智能体交互支持下‘师-生-机’协同的生成式学习模式研究与实践”(课题编号:26NDJC035YB)研究成果
2026-05-10
2026-05-10