Digital Transformation of Medical Education: Integrating Intelligent Technologies into Project-Based Learning (PBL) for Students
DOI:
https://doi.org/10.63034/esr-603Keywords:
digitalization of education, project-based learning, artificial intelligence, medical education, innovative technologies.Abstract
The rapid evolution of digital technologies and artificial intelligence is transforming contemporary medical education and creating new opportunities for improving teaching and learning processes. Project-Based Learning (PBL) has proven to be an effective approach for developing students’ professional competencies; however, its successful implementation requires digital tools that support coordination, monitoring, and objective assessment. This study investigates the impact of digital technologies and AI-based tools on the effectiveness of PBL in medical education. The research was conducted at the Department of Epidemiology and Biostatistics of Astana Medical University during the 2025–2026 academic year and involved 72 students from the Schools of Medicine and Pharmacy. Cloud services, collaborative platforms, interactive boards, and analytical tools were integrated into the learning process. The results demonstrate a 37% increase in student activity and a 12% improvement in academic performance, alongside higher motivation and engagement in teamwork. The findings confirm that integrating intelligent digital technologies into PBL enhances educational effectiveness and supports the development of essential research and digital competencies in future medical professionals.
References
Barrows, H. S. (1986). A taxonomy of problem-based learning methods. Medical Education, 20(6), 481–486. https://doi.org/10.1111/j.1365-2923.1986.tb01386.x
Cook, D. A., Levinson, A. J., Garside, S., Dupras, D. M., Erwin, P. J., & Montori, V. M. (2008). Internet-based learning in the health professions: A meta-analysis. JAMA, 300(10), 1181–1196. https://doi.org/10.1001/jama.300.10.1181
Ellaway, R., & Masters, K. (2008). AMEE Guide 32: E-learning in medical education. Medical Teacher, 30(5), 455–473. https://doi.org/10.1080/01421590802108349
Kolmos, A., De Graaff, E., & Du, X. (2009). Diversity of PBL – PBL learning principles and models. Aalborg University Press.
Longhurst, G. J., Stone, D. M., Dulohery, K., Scully, D., Campbell, T., & Smith, C. F. (2020). Strength, weakness, opportunity, threat (SWOT) analysis of the adaptations to anatomical education in the United Kingdom and Republic of Ireland in response to the COVID-19 pandemic. Anatomical Sciences Education, 13(3), 301–311. https://doi.org/10.1002/ase.1967
Masters, K. (2014). Student engagement and the use of educational technologies in medical education. Medical Teacher, 36(11), 989–996. https://doi.org/10.3109/0142159X.2014.956498
McCoy, L., Lewis, J. H., & Dalton, D. (2016). Gamification and multimedia for medical education: A landscape review. Journal of the American Osteopathic Association, 116(1), 22–34. https://doi.org/10.7556/jaoa.2016.003
Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine learning in medicine. New England Journal of Medicine, 380(14), 1347–1358. https://doi.org/10.1056/NEJMra1814259
Ruiz, J. G., Mintzer, M. J., & Leipzig, R. M. (2006). The impact of e-learning in medical education. Academic Medicine, 81(3), 207–212. https://doi.org/10.1097/00001888-200603000-00002
Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.
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Copyright (c) 2025 Джаулыбаева Эльвира Бейсембаевна, Мухамеджанова Асель Узбековна, Султанова Жанылсын Джиенгельдиновна
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