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How crucial is research philosophy in designing an AI study in medical education?
Samy A Azer1,2, Jiyoun Song3, Anthony P Guerrero4
1Faculty of Medicine, Universiti Kebangsaan Malaysia (UKM), Jalan Raja Muda Abdul Aziz, Kuala Lumpur, 50300, Malaysia. azer2000@optusnet.com.au.
Abstract:
Research papers are often rejected due to methodological problems, inappropriate tools, and poor alignment between aims, methods, and conclusions. This editorial argues that these problems often stem from neglecting research philosophy when pursuing an idea. Based on the literature and our peer-reviewed experience in medical education and biochemical sciences, we emphasize that clarifying ontological, epistemological, methodological, and axiological assumptions helps select the appropriate paradigm-positivism, post-positivism, interpretivism, critical theory, or pragmatism. To avoid such methodological problems, researchers should clarify their philosophical assumptions, explicitly state the selected paradigm, and ensure that this process is outlined in the methods section or the appendix. This approach increases the rationality, transparency, reproducibility, and defensibility of research, especially in fields like artificial intelligence in healthcare education.
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