Integrating Artificial Intelligence into the PDCA Framework for Quality Assurance in Medical English Courses at UMP-HCMC

Abstract

The integration of Artificial Intelligence (AI) into quality assurance frameworks presents a transformative opportunity for enhancing medical education. This study explores the application of AI within the Plan-Do-Check-Act (PDCA) cycle to ensure continuous improvement in Medical English courses at University of Medicine and Pharmacy at Ho Chi Minh City (UMP-HCMC). By aligning with the AUN-QA (Version 4.0) programme-level standards, the AI-enhanced PDCA model provides a systematic, evidence-based approach to educational quality assurance. Through AI-driven curriculum design, adaptive learning technologies, and data-driven assessment strategies, this framework supports personalized learning experiences, real-time performance monitoring, and dynamic course refinements. Furthermore, continuous assessment and stakeholder feedback guide iterative improvements, aligning the programme with industry and healthcare demands. The findings suggest that an AI-enhanced PDCA model fosters engagement, effectiveness, and sustainability in Medical English education, ultimately contributing to the production of highly competent medical professionals. This study highlights AI’s potential in transforming educational quality assurance for future healthcare practitioners.

Key words: Artificial Intelligence (AI), Plan-Do-Check-Act (PDCA), AUN-QA (Version 4.0), continuous improvement, Medical English courses, educational quality assurance

DOI: 10.7176/JLLL/105-02

Publication date: March 30^th 2025