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Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review

BACKGROUND: While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies. OBJECTIVE: This systematic review aims to examine the use of e-learning analytics d...

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Detalles Bibliográficos
Autores principales: Chan, Albert KM, Botelho, Michael G, Lam, Otto LT
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391646/
https://www.ncbi.nlm.nih.gov/pubmed/30758291
http://dx.doi.org/10.2196/11241
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author Chan, Albert KM
Botelho, Michael G
Lam, Otto LT
author_facet Chan, Albert KM
Botelho, Michael G
Lam, Otto LT
author_sort Chan, Albert KM
collection PubMed
description BACKGROUND: While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies. OBJECTIVE: This systematic review aims to examine the use of e-learning analytics data in health care studies with regards to how the analytics is reported and if there is a relationship between e-learning analytics and learning outcomes. METHODS: We performed comprehensive searches of papers from 4 electronic databases (MEDLINE, EBSCOhost, Web of Science, and ERIC) to identify relevant papers. Qualitative studies were excluded from this review. Papers were screened by 2 independent reviewers. We selected qualified studies for further investigation. RESULTS: A total of 537 papers were screened, and 19 papers were identified. With regards to analytics undertaken, 11 studies reported the number of connections and time spent on e-learning. Learning outcome measures were defined by summative final assessment marks or grades. In addition, significant statistical results of the relationships between e-learning usage and learning outcomes were reported in 12 of the identified papers. In general, students who engaged more in e-learning resources would get better academic attainments. However, 2 papers reported otherwise with better performing students consuming less e-learning videos. A total of 14 papers utilized satisfaction questionnaires for students, and all were positive in their attitude toward e-learning. Furthermore, 6 of 19 papers reported descriptive statistics only, with no statistical analysis. CONCLUSIONS: The nature of e-learning activities reported in this review was varied and not detailed well. In addition, there appeared to be inadequate reporting of learning analytics data observed in over half of the selected papers with regards to definitions and lack of detailed information of what the analytic was recording. Although learning analytics data capture is popular, a lack of detail is apparent with regards to the capturing of meaningful and comparable data. In particular, most analytics record access to a management system or particular e-learning materials, which may not necessarily detail meaningful learning time or interaction. Hence, learning analytics data should be designed to record the time spent on learning and focus on key learning activities. Finally, recommendations are made for future studies.
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spelling pubmed-63916462019-03-15 Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review Chan, Albert KM Botelho, Michael G Lam, Otto LT J Med Internet Res Review BACKGROUND: While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies. OBJECTIVE: This systematic review aims to examine the use of e-learning analytics data in health care studies with regards to how the analytics is reported and if there is a relationship between e-learning analytics and learning outcomes. METHODS: We performed comprehensive searches of papers from 4 electronic databases (MEDLINE, EBSCOhost, Web of Science, and ERIC) to identify relevant papers. Qualitative studies were excluded from this review. Papers were screened by 2 independent reviewers. We selected qualified studies for further investigation. RESULTS: A total of 537 papers were screened, and 19 papers were identified. With regards to analytics undertaken, 11 studies reported the number of connections and time spent on e-learning. Learning outcome measures were defined by summative final assessment marks or grades. In addition, significant statistical results of the relationships between e-learning usage and learning outcomes were reported in 12 of the identified papers. In general, students who engaged more in e-learning resources would get better academic attainments. However, 2 papers reported otherwise with better performing students consuming less e-learning videos. A total of 14 papers utilized satisfaction questionnaires for students, and all were positive in their attitude toward e-learning. Furthermore, 6 of 19 papers reported descriptive statistics only, with no statistical analysis. CONCLUSIONS: The nature of e-learning activities reported in this review was varied and not detailed well. In addition, there appeared to be inadequate reporting of learning analytics data observed in over half of the selected papers with regards to definitions and lack of detailed information of what the analytic was recording. Although learning analytics data capture is popular, a lack of detail is apparent with regards to the capturing of meaningful and comparable data. In particular, most analytics record access to a management system or particular e-learning materials, which may not necessarily detail meaningful learning time or interaction. Hence, learning analytics data should be designed to record the time spent on learning and focus on key learning activities. Finally, recommendations are made for future studies. JMIR Publications 2019-02-13 /pmc/articles/PMC6391646/ /pubmed/30758291 http://dx.doi.org/10.2196/11241 Text en ©Albert KM Chan, Michael G Botelho, Otto LT Lam. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.02.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Review
Chan, Albert KM
Botelho, Michael G
Lam, Otto LT
Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review
title Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review
title_full Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review
title_fullStr Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review
title_full_unstemmed Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review
title_short Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review
title_sort use of learning analytics data in health care–related educational disciplines: systematic review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391646/
https://www.ncbi.nlm.nih.gov/pubmed/30758291
http://dx.doi.org/10.2196/11241
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