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Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review | ||
| Journal of Advances in Medical Education & Professionalism | ||
| دوره 13، شماره 1، فروردین 2025، صفحه 12-24 اصل مقاله (626.71 K) | ||
| نوع مقاله: Review article | ||
| شناسه دیجیتال (DOI): 10.30476/jamp.2024.103973.2034 | ||
| نویسندگان | ||
| EHSAN TOOFANINEJAD1؛ SHANE DAWSON2؛ SOMAYE SOHRABI3؛ MASOMEH KALANTARION* 3 | ||
| 1Department of eLearning in Medical Sciences, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran | ||
| 2Centre for Change and Complexity in Learning, University of South Australia, Adelaide, Australia | ||
| 3Department of Medical Education, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran | ||
| چکیده | ||
| 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. The synthesis of findings underscores LA potential to enhance learning experiences, identify at-risk learners, and improve formative assessment practices. However, ethical and privacy concerns warrant 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-centric pedagogical practices is crucial. Addressing these concerns can ensure the integration of LA into medical education, fostering its transformative potential while upholding core values. | ||
تازه های تحقیق | ||
| کلیدواژه‌ها | ||
| Medical education؛ Data mining؛ Systematic review؛ Data science | ||
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آمار تعداد مشاهده مقاله: 162 تعداد دریافت فایل اصل مقاله: 222 |
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