Investigating students empathy and their school learning behaviors using Artificial Intelligence methods.

Introduction: Schools have a central role in cultivating students' personality by inculcating empathy. Empathy is the ability of one person to understand what another person is thinking and feeling in a given situation. The goal of this study is to explore the relationship between students’ empathy and their learning behaviors. The first task of our work is to classify students into clusters based on their empathy measures. Clustering is an area of artificial intelligence (AI). Clustering is an unsupervised classification in which, classes are not labeled at first. The second task of our work is to find a correlation between student’s empathy and their learning behavior measures. Methods: We used a questionnaire to assess empathy of students. Similar samples are classified in one cluster. Then clusters can be labeled based their attributes. In this work we present labels for students due to their empathy measures. We used a teacher-reported questionnaire to assess learning behavior of students. Results: A meaningful relation was realized between empathy scores and learning behaviors in the classroom for boy students. There is a reverse relationship between empathy and learning behaviors. Conclusion: A cultural analysis has been performed for the obtained results. Apathetic clusters usually have a cognitive component if they are not fully apathetic. Cognitive component is determinative in learning behavior. [ABSTRACT FROM AUTHOR]

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