WSEAS Transactions on Advances in Engineering Education
Print ISSN: 1790-1979, E-ISSN: 2224-3410
Volume 21, 2024
Data Mining Methods in Educational Process Management
Authors: ,
Abstract: The paper addresses the challenge of effectively managing the educational process by leveraging intelligent data analysis of student performance during learning activities. It introduces an approach centered around data clustering, specifically applied to the study of programming disciplines and languages. By utilizing clustering techniques, the paper aims to identify the most challenging topics within a given academic subject, track students’ learning paths, evaluate and enhance teaching methodologies, and create personalized learning plans tailored to individual students’ needs. This approach enables educators to better understand and address the diverse learning requirements of students, ultimately enhancing the overall educational experience.
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Keywords: educational process, student’s educational path, programming languages teaching, knowledge testing environments, data mining, data clustering, adaptive teaching scenarios
Pages: 110-116
DOI: 10.37394/232010.2024.21.13