Who You Are or What You Do: Comparing the Predictive Power of Demographics vs. Activity Patterns in Massive Open Online Courses (MOOCs)

Christopher A. Brooks, Craig D. S. Thompson, Stephanie D. Teasley
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引用次数: 29

Abstract

Demographics factors have been used successfully as predictors of student success in traditional higher education systems, but their relationship to achievement in MOOC environments has been largely untested. In this work we explore the predictive power of user demographics compared to learner interaction trace data generated by students in two MOOCs. We show that demographic information offers minimal predictive power compared to activity models, even when compared to models created very early on in the course before substantial interaction data has accrued.
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你是谁或你在做什么:比较大规模在线开放课程(MOOCs)中人口统计数据与活动模式的预测能力
在传统的高等教育体系中,人口因素已经被成功地用作学生成功的预测因素,但它们与MOOC环境下的成就之间的关系在很大程度上尚未经过测试。在这项工作中,我们将用户人口统计数据与两个mooc学生生成的学习者交互跟踪数据进行比较,探讨其预测能力。我们表明,与活动模型相比,人口统计信息提供的预测能力微乎其微,即使与在大量互动数据积累之前创建的模型相比也是如此。
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