University of Tasmania
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Retention factors in STEM education identified using learning analytics: a systematic review

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Student persistence and retention in STEM disciplines is an important yet complex and multi-dimensional issue confronting universities. Considering the rapid evolution of online pedagogy and virtual learning environments, we must rethink the factors that impact students’ decisions to stay or leave the current course. Learning analytics has demonstrated positive outcomes in higher education contexts and shows promise in enhancing academic success and retention. However, the retention factors in learning analytics practice for STEM education have not been fully reviewed and revealed. The purpose of this systematic review is to contribute to this research gap by reviewing the empirical evidence on factors affecting student persistence and retention in STEM disciplines in higher education and how these factors are measured and quantified in learning analytics practice. By analysing 59 key publications, seven factors and associated features contributing to STEM retention using learning analytics were comprehensively categorised and discussed. This study will guide future research to critically evaluate the influence of each factor and evaluate relationships among factors and the feature selection process to enrich STEM retention studies using learning analytics.

History

Publication title

Education Sciences

Volume

12

Issue

11

Article number

781

Number

781

Pagination

1-18

ISSN

2227-7102

Department/School

School of Information and Communication Technology

Publisher

MDPI AG

Place of publication

Switzerland

Rights statement

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. his is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License, (https://creativecommons.org/licenses/by/4.0/)

Repository Status

  • Open

Socio-economic Objectives

Higher education

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