Divide and correct: using clusters to grade short answers at scale
Divide and correct: using clusters to grade short answers at scale
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DOI：
10.1145/2556325.2566243
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发表时间：
2014-03
期刊：
影响因子：
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通讯作者：
Michael Brooks;S. Basu;Charles Jacobs;Lucy Vanderwende
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文献类型：
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作者：
Michael Brooks;S. Basu;Charles Jacobs;Lucy Vanderwende
与多项选择或其他以知识为导向的评估形式相比，简答题对学生和教师都有更大的价值;对学生来说，简答题可以提高知识的记忆力，而对教师来说，简答题可以更深入地了解学生的理解。不幸的是，同样的开放式性质，使他们如此有价值，也使他们更难以在规模上分级。为了解决这个问题，我们提出了一个基于集群的接口，允许教师阅读，评分，并提供反馈的答案大组一次。我们在一项有25名教师的学科内研究中对非聚类基线进行了评估，发现聚类界面可以让教师更快地评分，给学生更多的反馈，并对学生的理解和误解形成高层次的看法。
In comparison to multiple choice or other recognition-oriented forms of assessment, short answer questions have been shown to offer greater value for both students and teachers; for students they can improve retention of knowledge, while for teachers they provide more insight into student understanding. Unfortunately, the same open-ended nature which makes them so valuable also makes them more difficult to grade at scale. To address this, we propose a cluster-based interface that allows teachers to read, grade, and provide feedback on large groups of answers at once. We evaluated this interface against an unclustered baseline in a within-subjects study with 25 teachers, and found that the clustered interface allows teachers to grade substantially faster, to give more feedback to students, and to develop a high-level view of students' understanding and misconceptions.