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Bridging Innovations and Pedagogical Foundations in Health Professionals Education

Mila Nu,Nu Htay,Muhammad Zulfiqah Sadikan,Soumendra Sahoo

2025 · DOI: 10.71354/ijthpe.03.01.50
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TLDR

An important consideration is made for AI-SPs as a complementary tool in clinical education, suggesting their potential in interprofessional education and culturally diverse contexts, and sustainability of AI-based interventions remains another critical challenge.

Abstract

The innovative health professional education era requires technological advancement with the core foundation of pedagogical practice. In this issue of the International Journal of Transformative Health Professions Education (IJTHPE), the articles spotlight some of the key conversations shaping medical education today, from the use of artificial intelligence (AI) in clinical communication training, to approaches in postgraduate supervision, and practical guides for academic writing through review papers. Articles in this issue highlight the necessity of embracing cutting-edge technologies while preserving human-centric education and supervision roles. One of the advancements in health professionals’ education is the introduction of AI-based standardized patients (AI-SPs) for clinical communication training. As Sadikan (2025a) discussed, effective communication is essential in clinical training. However, logistic constraints may hinder this practice. AI-SPs, powered by large language models (LLMs) and natural language processing (NLP), offer a flexible and accessible alternative. The AI-SP not only simulates conversations, but also provides instant feedback and analyze behavior, making the learning experience more tailored and insightful in clinical training (Sadikan, 2025a). However, the article also wisely acknowledges the limitations of AI-SPs. This review makes an important consideration for AI-SPs as a complementary tool in clinical education, suggesting their potential in interprofessional education and culturally diverse contexts. More importantly, sustainability of AI-based interventions remains another critical challenge. AI’s role in medical education must be assessed beyond