Learning-State-Estimation Method Using Browsing History and Electroencephalogram During Programming Language Learning and Its Evaluation

Abstract

The failure of learners to obtain sufficient knowledge is caused by various factors, such as the difficulty level and quality of the learning materials and learner’s prior knowledge. The use of the learner’s learning log and biological information, such as the brain waves, heart rate, and eye movements during learning, makes it possible to detect the factors. If different brain waves can be measured according to the difficulty level of task execution, the difficulty level of e-learning materials can be adjusted so that the optimum learning effect can be obtained for each student. In this study, a system that obtains the learning logs during learning has been proposed. However, the learning time is insufficient to understand the learning state of the learners. For example, if the learning time is short, whether the learning materials were too easy or too difficult to abandon cannot be determined. Therefore, we propose a system and a method for estimating the learning state of the learners by comprehensively analyzing his/her learning history and brain wave. Moreover, we evaluate the learning state of high school students learning the C and Scratch programming languages using the proposed method. Also, by comparing the estimated results with those obtained from the questionnaire administered after the experiments, we evaluate the effectiveness of our proposed method.