Integrating Generative AI into Healthcare Management Education: Course Design, Implementation, and Outcomes
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Abstract
As artificial intelligence (AI) transforms healthcare, it is essential that healthcare management education evolves to prepare future administrators for AI-integrated environments. This study explores the design, implementation, and outcomes of a graduate-level healthcare informatics course that incorporated generative AI tools to enhance student learning. Grounded in Bloom’s Taxonomy, Kolb’s Experiential Learning Theory, and Connectivism, the course provided hands-on experience with AI applications in healthcare decision-making, operational efficiency, and ethical considerations. A mixed-methods research approach assessed shifts in students’ knowledge, confidence, and critical thinking about AI. The findings suggest that exposure to AI in a structured, theory-driven curriculum deepens understanding, fosters adaptability, and encourages ethical engagement with emerging technologies. Students reported greater confidence in utilizing AI tools and demonstrated an increased ability to evaluate their potential benefits and risks within healthcare settings. The study highlights the importance of integrating AI literacy into healthcare administration education, ensuring future leaders can critically engage with and implement AI-driven solutions. By providing a scalable model for AI integration, this research contributes to the growing conversation on preparing healthcare professionals for an increasingly AI-driven industry while maintaining a strong foundation in ethical responsibility and strategic decision-making.
