Integrating Generative AI into Challenge-Based Learning: A Case Study in Preventive Medicine and Public Health Education

Abstract

This study explores the integration of generative artificial intelligence (AI) into a challenge-based learning (CBL) course on preventive medicine and public health for first-year health students. Implemented at Tecnologico de Monterrey, the course aimed to enhance students' ability to design community based strategies for preventing non-communicable diseases (NCDs). Starting in 2024, students used AI tools to generate and refine proposals aligned with national health guidelines. Academic performance data from 2021 to 2025 showed stable overall grades, but there was a notable improvement in the quality of AI-assisted preventive proposals. Additionally, student motivation–measured using the MUSIC model–was higher in 2025, particularly in terms of empowerment and perceived success. These findings suggest that AI can enhance engagement and support the development of critical and digital skills in health education. Further research is needed to assess long-term impacts and guide the ethical and effective integration of AI in medical training.

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