Learning Experiments Using AB Testing at Scale

Christopher Chudzicki, David E. Pritchard, Zhongzhou Chen
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引用次数: 8

Abstract

We report the one of the first applications of treatment/control group learning experiments in MOOCs. We have compared the efficacy of deliberate practice-practicing a key procedure repetitively-with traditional practice on "whole problems". Evaluating the learning using traditional whole problems we find that traditional practice outperforms drag and drop, which in turn outperforms multiple choice. In addition, we measured the amount of learning that occurs during a pretest administered in a MOOC environment that transfers to the same question if placed on the posttest. We place a limit on the amount of such transfer, which suggests that this type of learning effect is very weak compared to the learning observed throughout the entire course.
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大规模使用AB测试学习实验
我们报告了实验组/对照组学习实验在mooc中的第一个应用。我们比较了反复练习一个关键步骤的刻意练习与传统的“整体问题”练习的效果。用传统的整道题来评估学习,我们发现传统的拖放练习优于拖放练习,而拖放练习又优于选择题。此外,我们测量了在MOOC环境中进行的前测期间发生的学习量,如果将其转移到后测中,则会转移到相同的问题。我们对这种转移的数量进行了限制,这表明与整个课程中观察到的学习相比,这种类型的学习效果非常弱。
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