Improving Student Behavior within Educational Units Based on Profiling Similarity


Authors: Pantelis V. Gryparis, Klimis S. Ntalianis, Nikos E. Mastorakis

Abstract: This study looks at how the data-based approach to group formation can improve student behavior in the classroom. We built a system called the Student Profile Vector (SPV) to capture the emotional details of each student. We used cosine similarity and Genetic Algorithms to put the students into the groups that share traits. We tested the model in five institutions. We found that the model does not just reduce the classroom conflict—it increases the student engagement a lot. Our findings show that the computational tools are practical and scalable. The computational tools can make the learning environment more inclusive and adaptive. We see this as an approach.

Pages: 117-123

DOI: 10.46300/9109.2026.20.12

International Journal of Education and Information Technologies, E-ISSN: 2074-1316, Volume 20, 2026, Art. #12

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