Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review
Introduction: Learning Analytics (LA) has emerged as a potent tool in medical education, offering data-driven insights and personalized support to learners. This systematic review aims to provide a comprehensive overview of the current state of LA in medical education, exploring its applications, be...
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| Language: | English |
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Shiraz University of Medical Sciences
2025-01-01
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| Series: | Journal of Advances in Medical Education and Professionalism |
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| Online Access: | https://jamp.sums.ac.ir/article_50619_1852672b326f6ff2e8569000a8cc5336.pdf |
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| author | EHSAN TOOFANINEJAD SHANE DAWSON SOMAYE SOHRABI MASOMEH KALANTARION |
| author_facet | EHSAN TOOFANINEJAD SHANE DAWSON SOMAYE SOHRABI MASOMEH KALANTARION |
| author_sort | EHSAN TOOFANINEJAD |
| collection | DOAJ |
| description | Introduction: Learning Analytics (LA) has emerged as a potent tool in medical education, offering data-driven insights and personalized support to learners. This systematic review aims to provide a comprehensive overview of the current state of LA in medical education, exploring its applications, benefits, challenges, and future directions.Methods: The study was conducted as a systematic review of learning analytics (LA) in medical education. A comprehensive search was performed in June 2023 across the following databases: ProQuest, Scopus, ERIC, Web of Science, PubMed, and ScienceDirect, with no restrictions on publication dates. The search resulted in a total of 1095 records, which were screened after removing duplicates, leaving 552 titles for review. Following the exclusion of irrelevant articles, 12 studies were selected for synthesis.Results: Four key categories of LA applications emerged: curriculum evaluation, learner performance analysis, learner feedback and support, and learning outcome assessment. Thesynthesis of findings underscores LA potential to enhance learning experiences, identify at-risk learners, and improve formative assessment practices. However, ethical and privacy concernswarrant attention to bridge the gap between research and practice.Conclusion: This review suggests a collaborative and mindful approach to leveraging LA in medical education. Balancing data-driven insights with effective, ethical, and human-centricpedagogical practices is crucial. Addressing these concerns can ensure the integration of LA into medical education, fostering its transformative potential while upholding core values. |
| format | Article |
| id | doaj-art-f3736bfb9fe547e681db2efcb4b7fd09 |
| institution | Kabale University |
| issn | 2322-2220 2322-3561 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Shiraz University of Medical Sciences |
| record_format | Article |
| series | Journal of Advances in Medical Education and Professionalism |
| spelling | doaj-art-f3736bfb9fe547e681db2efcb4b7fd092025-01-05T07:52:31ZengShiraz University of Medical SciencesJournal of Advances in Medical Education and Professionalism2322-22202322-35612025-01-01131122410.30476/jamp.2024.103973.203450619Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic ReviewEHSAN TOOFANINEJAD0SHANE DAWSON1SOMAYE SOHRABI2MASOMEH KALANTARION3Department of eLearning in Medical Sciences, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, IranCentre for Change and Complexity in Learning, University of South Australia, Adelaide, AustraliaDepartment of Medical Education, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, IranDepartment of Medical Education, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, IranIntroduction: Learning Analytics (LA) has emerged as a potent tool in medical education, offering data-driven insights and personalized support to learners. This systematic review aims to provide a comprehensive overview of the current state of LA in medical education, exploring its applications, benefits, challenges, and future directions.Methods: The study was conducted as a systematic review of learning analytics (LA) in medical education. A comprehensive search was performed in June 2023 across the following databases: ProQuest, Scopus, ERIC, Web of Science, PubMed, and ScienceDirect, with no restrictions on publication dates. The search resulted in a total of 1095 records, which were screened after removing duplicates, leaving 552 titles for review. Following the exclusion of irrelevant articles, 12 studies were selected for synthesis.Results: Four key categories of LA applications emerged: curriculum evaluation, learner performance analysis, learner feedback and support, and learning outcome assessment. Thesynthesis of findings underscores LA potential to enhance learning experiences, identify at-risk learners, and improve formative assessment practices. However, ethical and privacy concernswarrant attention to bridge the gap between research and practice.Conclusion: This review suggests a collaborative and mindful approach to leveraging LA in medical education. Balancing data-driven insights with effective, ethical, and human-centricpedagogical practices is crucial. Addressing these concerns can ensure the integration of LA into medical education, fostering its transformative potential while upholding core values.https://jamp.sums.ac.ir/article_50619_1852672b326f6ff2e8569000a8cc5336.pdfmedical educationdata miningsystematic reviewdata science |
| spellingShingle | EHSAN TOOFANINEJAD SHANE DAWSON SOMAYE SOHRABI MASOMEH KALANTARION Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review Journal of Advances in Medical Education and Professionalism medical education data mining systematic review data science |
| title | Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review |
| title_full | Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review |
| title_fullStr | Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review |
| title_full_unstemmed | Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review |
| title_short | Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review |
| title_sort | exploring the transformative potential of learning analytics in medical education a systematic review |
| topic | medical education data mining systematic review data science |
| url | https://jamp.sums.ac.ir/article_50619_1852672b326f6ff2e8569000a8cc5336.pdf |
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