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[1L2-03] Automatic Classification of Description Problem Answers in Business Education
Keywords:Business education, Text classification, Adaptive Learning
Recently, automatic text scoring research using machine learning is progressing in an education field. Most of the short description problems have specific model answers. However, about business education, most of them don't have specific model answers. Therefore, we investigated the possibility of classifying short description problem answers in a business education field, to develop a personalized learning system. If automatic classification is possible, it is possible to provide an appropriate retrospective service in response to learner 's answers, such as changing feedback according to the pattern of answers. As a result, we confirmed that we could classify them with high accuracy if the number of answer characters is about 50 and answers can be clearly classified into less than three patterns. Then we could detect the words that contribute to the classification. Moreover, we found that the way of creating problems is one of the important factors to classify answers.