What question did this study set out to answer?

This research aims to assess the effectiveness of a novel educational format combining AI, gamification, and case-based learning for medical students.

April 8, 2026Open Access

Case-based Learning and Artificial Intelligence-based Gamification to Improve Undergraduate Students’ Motivation for One Health and Climate Change: A Pilot Study

Key Points

This research aims to assess the effectiveness of a novel educational format combining AI, gamification, and case-based learning for medical students.
Utilized a large language model and gamification for teaching environmental medicine
Employed case-based learning (CBL) as a teaching method
Measured student motivation using the intrinsic motivation inventory (IMI) scale
Analyzed data through ordinal logistic regression
Higher intrinsic motivation scores observed for the CBL format on all IMI subscales
Statistical analysis revealed significant associations between the CBL format and IMI score improvements
Odds ratios ranged from 1.65 to 2.69 indicating strong positive effects

Abstract

The One Health approach (OHA) which entails the interconnectedness of human, animal, and environmental health is a critical concept for medical students. In this pilot study, we report the feasibility of a new format using a large language model, gamification elements and case-based learning (CBL) to teach medical undergraduates environmental medicine, including the OHA and climate change, and its effectiveness on students’ motivation using the intrinsic motivation inventory (IMI) scale. We found higher scores for the CBL format across all IMI subscales. Ordinal logistic regression analysis yielded that having the CBL format was significantly associated with higher IMI scores in every item (odds ratios, OR, between 1.65 and 2.69).

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