结合基于算例的协作反思与问题解决实践:设计大规模学习的协作编程项目

Sreecharan Sankaranarayanan, Siddharth Reddy Kandimalla, C. Bogart, R. C. Murray, Michael Hilton, M. Sakr, C. Rosé
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引用次数: 2

摘要

计算机科学教学法压倒性地倾向于解决问题的实践,而不是参与的方法,比如在高级课程中进行例题学习。这是因为人们相信,虽然这些替代方法可能会提高学生的概念学习,但由于缺乏动手实践,它们可能会使他们无法完成真正的问题解决任务。在本文中,我们在保持任务总时间不变的情况下,通过调整问题解决和协作反思之间的边界,对同步协作规划项目中的这种权衡进行了直接比较。我们发现,学生花在实例学习上的时间越多,测试前和测试后得分的提高就越多,而在随后的问题解决任务上的表现没有显著差异。因此,这些结果挑战了解决问题实践在高级课程环境中的主导地位,并为大规模协作编程项目的设计提供了信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining Collaborative Reflection based on Worked-Out Examples with Problem-Solving Practice: Designing Collaborative Programming Projects for Learning at Scale
Computer science pedagogy has overwhelmingly favored problem-solving practice over methods of engagement like worked-out example study especially in advanced classes. This is due to the belief that while these alternative methods may improve student conceptual learning, they may leave them less able to perform on authentic problem-solving tasks from a lack of hands-on practice. In this paper, we perform a direct comparison of this trade-off in a synchronous collaborative programming project by adjusting the boundary between problem-solving and collaborative reflection based on a worked-out example while keeping the total time on task constant. We find that the more time students spent on worked example study, the more was the observed improvement in the pre- to post-test scores with no significant difference in performance on a subsequent problem-solving task. These results, therefore, challenge the dominant place of problem-solving practice in the advanced curricular context and inform the design of collaborative programming projects at scale.
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