Detection of Careless Mistakes during Programming Learning using a Simple Electroencephalograph

K. Umezawa, M. Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, S. Hirasawa
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Abstract

There are several difficulties encountered by learners during learning such as good or bad learning content, the difficulty level of learning content, and the degree of learning proficiency. It is possible to detect these difficulties by measuring the browsing history, editing history, and biological information such as brain waves or eye-tracking information. In this paper, we measure electroencephalograph (EEG) information during programming learning. We focus on the relationship between task response time and EEG, and try to detect careless mistakes due to the lack of attention. The results show that careless mistakes during programming learning can be detected by experiments.
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用简易脑电图检测编程学习过程中的粗心错误
学习者在学习过程中会遇到学习内容的好坏、学习内容的难易程度、学习的熟练程度等几个困难。通过测量浏览历史、编辑历史以及脑电波或眼球追踪信息等生物信息,可以检测到这些困难。在本文中,我们测量了编程学习过程中的脑电图信息。我们关注任务响应时间与EEG之间的关系,并尝试检测由于缺乏注意力而导致的粗心错误。结果表明,通过实验可以检测出编程学习过程中的粗心错误。
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