Abstract
Educational Data Mining (EDM) is an emerging interdisciplinary field that utilizes data mining techniques to analyze and extract valuable insights from educational data. The aim of this research paper is to provide a comprehensive overview of the various methods used in EDM, explore their practical applications, and discuss the challenges and opportunities in this rapidly evolving field. As educational institutions increasingly leverage digital technologies, the ability to harness data from student performance, behavior, and interactions provides significant opportunities to enhance learning outcomes, personalize instruction, and improve overall educational processes. This paper examines key EDM techniques such as classification, clustering, regression, and association rule mining, and highlights their applications in predictive analytics, student modeling, curriculum design, and learner support.
Citations
IRE Journals:
Dr. Abhishek Raghuvanshi
"Educational Data Mining: Techniques, Applications, and Challenges" Iconic Research And Engineering Journals Volume 8 Issue 9 2025 Page 112-126
IEEE:
Dr. Abhishek Raghuvanshi
"Educational Data Mining: Techniques, Applications, and Challenges" Iconic Research And Engineering Journals, 8(9)
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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