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Educational Data Mining and Learning Analytics in the 21st Century

Educational Data Mining and Learning Analytics in the 21st Century

Georgios Lampropoulos
Copyright: © 2023 |Pages: 10
ISBN13: 9781799892205|ISBN10: 1799892204|EISBN13: 9781799892212
DOI: 10.4018/978-1-7998-9220-5.ch098
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MLA

Lampropoulos, Georgios. "Educational Data Mining and Learning Analytics in the 21st Century." Encyclopedia of Data Science and Machine Learning, edited by John Wang, IGI Global, 2023, pp. 1642-1651. https://doi.org/10.4018/978-1-7998-9220-5.ch098

APA

Lampropoulos, G. (2023). Educational Data Mining and Learning Analytics in the 21st Century. In J. Wang (Ed.), Encyclopedia of Data Science and Machine Learning (pp. 1642-1651). IGI Global. https://doi.org/10.4018/978-1-7998-9220-5.ch098

Chicago

Lampropoulos, Georgios. "Educational Data Mining and Learning Analytics in the 21st Century." In Encyclopedia of Data Science and Machine Learning, edited by John Wang, 1642-1651. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-7998-9220-5.ch098

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Abstract

This article aims at offering an overview of educational data mining and learning analytics and highlighting their essential role in improving 21st century education. Hence, it analyzes their concepts, goes over the recent literature, and extracts invaluable information according to the results and outcomes of related studies. Furthermore, it discusses their use in educational settings, examines their benefits, and suggests ways to address some of the current open challenges, issues, and limitations. In addition, it presents the summary of the main findings, draws conclusions, and provides directions for future research. Based on the results, educational data mining and learning analytics fields can significantly influence the current educational system and provide opportunities for new learner-centered tools and smart learning environments that provide customized experiences and meet students' specific needs to be developed. Finally, it was evident that for the complete adoption of these fields, a data-driven culture should be followed by the educational institutions.

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