Results
Title

Educational Data Mining: A Foundational Overview.

Authors

Papadogiannis, Ilias; Wallace, Manolis; Karountzou, Georgia

Abstract

Definition: Educational data mining (EDM) is a novel scientific area that focuses on developing and applying methods to analyze datasets generated within educational settings. This paper outlines the evolution, significance, and applications of EDM. With the increasing popularity of e-learning in web-based educational systems, EDM has expanded to include a variety of analytical methods and data sources. Some key methodologies addressed include classification, regression analysis, clustering techniques, association rule mining, and Natural Language Processing, among others. Additionally, this paper looks at how EDM can facilitate data-driven decision-making among other areas such as curriculum development and customization of learners' experiences. It also touches on issues related to the challenges of the scientific field. Finally, some projections about EDM's future trends are made, especially concerning its integration into AI technologies and development trends like augmented reality or virtual reality, which imply greater possibilities for changes than any other series witnessed before within this sphere.

Subjects

NATURAL language processing; AUGMENTED reality; VIRTUAL reality; CURRICULUM planning; REGRESSION analysis; ASSOCIATION rule mining

Publication

Encyclopedia, 2024, Vol 4, Issue 4, p1644

ISSN

2673-8392

Publication type

Academic Journal

DOI

10.3390/encyclopedia4040108