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Journal of Arts, Society, and Education Studies

Volume 3, 2021 - Issue 2

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Journal Article

Learning Analytics for Early Intervention: Identifying At-risk Students

by James Taylor 1,*
1
University of Malta
*
Author to whom correspondence should be addressed.
JASES  2021 3(2):60; https://doi.org/10.xxxx/xxxxxx
Received: 15 April 2021 / Accepted: 15 May 2021 / Published Online: 18 June 2021
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Abstract

Learning Analytics has emerged as a valuable tool in education, particularly in early intervention strategies for identifying at-risk students. This paper explores the significance of Learning Analytics in education, emphasizing its role in data-driven decision-making, early identification of struggling students, and personalized support. It delves into various aspects of Learning Analytics, including data collection, analysis techniques, and predictive modeling. The discussion includes the benefits of Learning Analytics, such as timely intervention, improved student outcomes, and enhanced educational efficiency. Moreover, the paper addresses the challenges and considerations in implementing Learning Analytics in educational institutions, including data privacy, ethical concerns, and the need for faculty training. Through a review of empirical studies and case examples, the study highlights the positive outcomes associated with effective Learning Analytics, including increased student retention, reduced dropout rates, and improved learning experiences. The conclusion offers recommendations for educators and institutions interested in adopting Learning Analytics, emphasizing the importance of ethical data usage, transparency, and ongoing assessment to ensure the success of early intervention strategies.

Keywords: Learning Analytics; Early Intervention; At-risk Students; Data-driven Decision-making; Predictive Modeling; Student Support; Educational Efficiency.;
Copyright: © 2021 by Taylor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Taylor, J. Learning Analytics for Early Intervention: Identifying At-risk Students. Journal of Arts, Society, and Education Studies, 2021, 3, 60. doi:10.xxxx/xxxxxx
AMA Style
Taylor J. Learning Analytics for Early Intervention: Identifying At-risk Students. Journal of Arts, Society, and Education Studies; 2021, 3(2):60. doi:10.xxxx/xxxxxx
Chicago/Turabian Style
Taylor, James 2021. "Learning Analytics for Early Intervention: Identifying At-risk Students" Journal of Arts, Society, and Education Studies 3, no.2:60. doi:10.xxxx/xxxxxx

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References

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