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Predicting Java Computer Programming Task Difficulty Levels Using EEG for Educational Environments

机译:使用EEG预测教育环境中的Java计算机编程任务难度等级

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Understanding how difficult a learning task is for a person allows teaching material to be appropriately designed to suit the person, especially for programming material. A first step for this would be to predict on the task difficulty level. While this is possible through subjective questionnaire, it could lead to misleading outcome and it would be better to do this by tapping the actual thought process in the brain while the subject is performing the task, which can be done using electroencephalogram. We set out on this objective and show that it is possible to predict easy and difficult levels of mental tasks when subjects are attempting to solve Java programming problems. Using a proposed confidence threshold, we obtained a classification performance of 87.05% thereby showing that it is possible to use brain data to determine the teaching material difficulty level which will be useful in educational environments.
机译:了解学习任务对一个人的困难程度,可以适当地设计适合该人的教学材料,尤其是对编程材料而言。第一步是在任务难度级别上进行预测。尽管这可以通过主观问卷调查来实现,但它可能导致误导性结果,最好是在受试者执行任务时通过敲击大脑中的实际思维过程来完成,这可以使用脑电图来完成。我们着眼于这一目标,表明当受试者试图解决Java编程问题时,可以预测心理任务的容易程度和困难程度。使用建议的置信度阈值,我们获得了87.05%的分类效果,从而表明可以使用大脑数据来确定教材的难易程度,这将对教育环境很有用。

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