Predicting Students' Performance in an Introductory Programming Course Using Data from Students' Own Programming Process
Predicting Students' Performance in an Introductory Programming Course Using Data from Students' Own Programming Process
复制标题
使用学生自己的编程过程中的数据预测学生在入门编程课程中的表现
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Arto Vihavainen
中科院分区：
文献类型：
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作者：
Arto Vihavainen
随着理解学生编程过程的数据量、设施和工具的不断完善，分析学生实际编程过程的时机已经成熟。在我们当前的工作中，我们正在调查学生在编程过程中的行为（例如，渴望开始新发布的练习、遵循最佳编程实践）如何影响课程结果。我们有目的地仅利用通过学生编程过程中的快照自动收集的数据，并且不收集任何其他背景信息。目前，我们能够以 78% 的准确率预测学生是否表现出色、通过课程还是未通过课程。
As the amount of data, facilities, and tools for understanding students' programming process are improving, the time is ripe for analyzing students' actual programming process. In our current work we are investigating how students' behavior during her programming process (e.g. eagerness to start working on freshly released exercises, following best programming practises) affects the course outcome. We purposefully utilize only data gathered automatically using snapshots from the students' programming process, and do not gather any additional background information. Currently, we are able to predict whether the student is a high-performer, passes the course, or fails the course with a 78%accuracy.