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TOOFANINEJAD, EHSAN, DAWSON, SHANE, SOHRABI, SOMAYE, KALANTARION, MASOMEH. (1403). Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review. سامانه مدیریت نشریات علمی, 13(1), 12-24. doi: 10.30476/jamp.2024.103973.2034
EHSAN TOOFANINEJAD; SHANE DAWSON; SOMAYE SOHRABI; MASOMEH KALANTARION. "Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review". سامانه مدیریت نشریات علمی, 13, 1, 1403, 12-24. doi: 10.30476/jamp.2024.103973.2034
TOOFANINEJAD, EHSAN, DAWSON, SHANE, SOHRABI, SOMAYE, KALANTARION, MASOMEH. (1403). 'Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review', سامانه مدیریت نشریات علمی, 13(1), pp. 12-24. doi: 10.30476/jamp.2024.103973.2034
TOOFANINEJAD, EHSAN, DAWSON, SHANE, SOHRABI, SOMAYE, KALANTARION, MASOMEH. Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review. سامانه مدیریت نشریات علمی, 1403; 13(1): 12-24. doi: 10.30476/jamp.2024.103973.2034

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
سایر فایل های مرتبط با مقاله
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