学生在计算机化考试中选择多次打分的定量分析

Ashank Verma, Timothy Bretl, Matthew West, C. Zilles
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摘要

在本文中,我们研究了一个计算机化的考试系统,允许学生多次尝试同一个问题。该系统允许学生立即收到对他们提交的答案的反馈,或者推迟反馈并批量评分问题。对两个学期三门课程的学生行为分析发现,不同课程和学生群体的学生行为相似。我们发现只有一小部分学生使用延迟反馈选项。聚类分析既考虑了学生选择接收反馈的时间,也考虑了学生选择立即重试不正确的问题或尝试其他未完成的问题的时间,确定了四种主要的学生策略。这些策略与考试成绩的统计显著差异相关,但尚不清楚是某些策略提高了成绩,还是更强的学生倾向于选择某些策略。
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A Quantitative Analysis of When Students Choose to Grade Questions on Computerized Exams with Multiple Attempts
In this paper, we study a computerized exam system that allows students to attempt the same question multiple times. This system permits students either to receive feedback on their submitted answer immediately or to defer the feedback and grade questions in bulk. An analysis of student behavior in three courses across two semesters found similar student behaviors across courses and student groups. We found that only a small minority of students used the deferred feedback option. A clustering analysis that considered both when students chose to receive feedback and either to immediately retry incorrect problems or to attempt other unfinished problems identified four main student strategies. These strategies were correlated to statistically significant differences in exam scores, but it was not clear if some strategies improved outcomes or if stronger students tended to prefer certain strategies.
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Trust, Sustainability and [email protected] L@S'22: Ninth ACM Conference on Learning @ Scale, New York City, NY, USA, June 1 - 3, 2022 L@S'21: Eighth ACM Conference on Learning @ Scale, Virtual Event, Germany, June 22-25, 2021 Leveraging Book Indexes for Automatic Extraction of Concepts in MOOCs Evaluating Bayesian Knowledge Tracing for Estimating Learner Proficiency and Guiding Learner Behavior
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