非认知干预对学生学习行为和结果的影响:七项大型实验发明的分析

Kirk P. Vanacore, Ashish Gurung, Andrew Mcreynolds, Allison S. Liu, S. Shaw, N. Heffernan
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引用次数: 1

摘要

随着越来越多的证据支持非认知因素在学习中的重要性,计算机辅助学习平台越来越多地纳入非学术干预来影响学生的学习和学习相关行为。非认知干预往往试图影响学生的心态、动机或元认知反思,从而影响学习行为和结果。在本文中,我们分析了五个实验的数据,这些实验涉及在以中学数学为重点的计算机辅助学习平台上进行的基于掌握的学习活动中的七种治疗条件。每个治疗条件都体现了一个特定的非认知理论视角。在7个学年里,有20,472名学生参加了实验。我们估计了每个处理条件对学生的反应时间、提示使用、掌握知识成分的可能性、学习效率和测试后表现的影响。我们的分析揭示了积极和消极的治疗对学生学习行为和表现的影响。根据后测试的评估,很少有干预措施影响学习。这些发现强调了使用非认知干预来积极影响学生学习行为和结果的困难。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of Non-Cognitive Interventions on Student Learning Behaviors and Outcomes: An analysis of seven large-scale experimental inventions
As evidence grows supporting the importance of non-cognitive factors in learning, computer-assisted learning platforms increasingly incorporate non-academic interventions to influence student learning and learning related-behaviors. Non-cognitive interventions often attempt to influence students’ mindset, motivation, or metacognitive reflection to impact learning behaviors and outcomes. In the current paper, we analyze data from five experiments, involving seven treatment conditions embedded in mastery-based learning activities hosted on a computer-assisted learning platform focused on middle school mathematics. Each treatment condition embodied a specific non-cognitive theoretical perspective. Over seven school years, 20,472 students participated in the experiments. We estimated the effects of each treatment condition on students’ response time, hint usage, likelihood of mastering knowledge components, learning efficiency, and post-tests performance. Our analyses reveal a mix of both positive and negative treatment effects on student learning behaviors and performance. Few interventions impacted learning as assessed by the post-tests. These findings highlight the difficulty in positively influencing student learning behaviors and outcomes using non-cognitive interventions.
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