升级:为学生提供开放式解决方案,创造可扩展的学习机会

Xu Wang, Srinivasa Teja Talluri, C. Rosé, K. Koedinger
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引用次数: 38

摘要

在世界各地的学校和大学里,开放式的家庭作业是很常见的。然而,这样的作业需要教师付出大量的努力来评分,而且往往不支持重复练习的机会。我们提出了UpGrade,这是一种新颖的学习者资源方法,可以使用先前学生对开放式问题的解决方案来产生可扩展的学习机会。UpGrade创建交互式问题,提供自动化和实时反馈,同时允许重复练习。在一项为期两周的大学级HCI课程实验中,学生回答由upgrade设计的问题,而不是传统的开放式作业,在大约30%的时间内取得了没有区别的学习成果。此外,不需要手动分级工作。为了加强质量控制,UpGrade采用了一种心理测量方法,使用群体工作者的答案来自动剔除低质量的问题,从而形成了一个超过课堂使用可靠性标准的题库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UpGrade: Sourcing Student Open-Ended Solutions to Create Scalable Learning Opportunities
In schools and colleges around the world, open-ended home-work assignments are commonly used. However, such assignments require substantial instructor effort for grading, and tend not to support opportunities for repeated practice. We propose UpGrade, a novel learnersourcing approach that generates scalable learning opportunities using prior student solutions to open-ended problems. UpGrade creates interactive questions that offer automated and real-time feedback, while enabling repeated practice. In a two-week experiment in a college-level HCI course, students answering UpGrade-created questions instead of traditional open-ended assignments achieved indistinguishable learning outcomes in ~30% less time. Further, no manual grading effort is required. To enhance quality control, UpGrade incorporates a psychometric approach using crowd workers' answers to automatically prune out low quality questions, resulting in a question bank that exceeds reliability standards for classroom use.
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