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Connecting the Dots Towards Collaborative AIED: Linking Group Makeup to Process to Learning

机译:将点连接到协作AIED:将组组成链接到过程与学习

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We model collaborative problem solving outcomes using data from 37 triads who completed a challenging computer programming task. Participants individually rated their group's performance, communication, cooperation, and agreeableness after the session, which were aggregated to produce group-level measures of subjective outcomes. We scored teams on objective task outcomes and measured individual students' learning outcomes with a posttest. Groups with similar personalities performed better on the task and had higher ratings of communication, cooperation, and agreeableness. Importantly, greater deviation in teammates' perception of group performance and higher ratings of communication, cooperation, and agreeableness negatively predicted individual learning. We discuss findings from the perspective of group work norms and consider applications to intelligent systems that support collaborative problem solving.
机译:我们使用来自37个三合会的数据建模协作解决问题的结果,这些三合会完成了具有挑战性的计算机编程任务。参加者在会议结束后分别对小组的表现,沟通,合作和同意程度进行了评分,这些意见汇总在一起就形成了小组一级的主观评价指标。我们在客观任务成果方面对团队进行了评分,并通过事后测试来衡量单个学生的学习成果。具有相似性格的小组在这项任务上的表现更好,并且在沟通,合作和友善方面的评价更高。重要的是,队友对团队绩效的看法更大的偏差以及更高的沟通,合作和友善度会负面地预测个人学习。我们从小组工作规范的角度讨论发现的问题,并考虑将其应用到支持协作解决问题的智能系统中。

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