OverCode
OverCode
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DOI：
10.1145/2699751
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发表时间：
2015
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影响因子：
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通讯作者：
Robert C. Miller
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文献类型：
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作者：
Elena L. Glassman;J. Scott;Rishabh Singh;Philip J. Guo;Robert C. Miller
在mooc中，一个简单的编程练习可能会从学习者那里产生数千个解决方案。理解解决方案的变化对于大规模地向学生提供适当的反馈非常重要。这些解决方案之间的广泛差异可以成为教学上有价值的示例的来源，并且可以通过暴露极端情况来改进练习的自动分级器。我们介绍了OverCode，一个用于可视化和探索数千种编程解决方案的系统。OverCode使用静态和动态分析来聚类类似的解决方案，并允许教师根据不同的标准进一步筛选和聚类解决方案。我们在24名助教的主题研究中对OverCode进行了非聚类基线评估，发现OverCode界面使教师能够更快地对学生的理解和误解形成高层次的看法，并提供与更多学生的解决方案相关的反馈。
In MOOCs, a single programming exercise may produce thousands of solutions from learners. Understanding solution variation is important for providing appropriate feedback to students at scale. The wide variation among these solutions can be a source of pedagogically valuable examples and can be used to refine the autograder for the exercise by exposing corner cases. We present OverCode, a system for visualizing and exploring thousands of programming solutions. OverCode uses both static and dynamic analysis to cluster similar solutions, and lets teachers further filter and cluster solutions based on different criteria. We evaluated OverCode against a nonclustering baseline in a within-subjects study with 24 teaching assistants and found that the OverCode interface allows teachers to more quickly develop a high-level view of students' understanding and misconceptions, and to provide feedback that is relevant to more students' solutions.