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    基于启发式挖掘算法探究混合式协作学习过程

    Exploring Process of Blended Collaborative Learning Based on Heuristic Mining Algorithm

    [浏览次数:7326]

【作      者】:

许 玮, 沈致仪


【关 键 词 】:

混合式协作学习; 过程挖掘; 启发式挖掘算法


【栏      目】:

课程与教学


【中文摘要】:

混合式协作学习下,学生可以通过社交媒体分享和建构知识,研究大学生如何在此过程中发展基于认知与情感的互动调节是建成混合式“金课”的关键。研究以30名本科生的2256条协作学习对话数据为样本,采用启发式挖掘算法和时间序列分析总结互动过程的发展规律与高低分组的行为模式。研究结果表明,高分组在协作过程中注重规划与反思,且情感参与的认知互动多于低分组,协作学习互动过程遵循IDB型的变化规律,高低分组的行为模式与自我调节阶段的变化趋势存在差异。本研究试图进一步理解学习者在协作学习中的认知与情感的调节互动模式,可为高校教师建设混合式课程资源、设计混合式协作学习的课程方案提供参考和借鉴。


【英文摘要】:

Under blended collaborative learning, students can share and construct knowledge through social media, and studying how undergraduates develop their interaction adjustment based on cognition and emotion in this process is the key to building a blended "golden class". The sample of this study is 2256 collaborative learning dialogues from 30 undergraduates. Heuristic mining algorithm and time series analysis are used to summarize the development rules of the interaction process and behavior patterns of high and low score subgroups. The results show that the high score subgroups pay attention to planning and reflection in the collaborative process, and the cognitive interaction with emotional involvement is more than that of the low score subgroups. The collaborative learning interaction process follows the IDB-type change pattern. There are differences between the behavioral patterns and self-regulation phases of high and low score subgroups. This study tries to further understand the cognitive and affective regulation interaction patterns of learners in collaborative learning, which can provide reference for college teachers to construct blended course resources and design course programs of blended collaborative learning.

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