Case-Based Learning with Gen AI: Level of Complexity in Case Study Creation

In recent times, generative artificial intelligence has proven to be an ally for creating contextualized and personalized teaching materials and resources that help improve the learning experience. This study aimed to determine the level of complexity of the practical cases generated by generative artificial intelligence for case-based learning. Qualitative in nature, this research analyzed 112 cases generated by this tool. The results showed that it allows for generating cases with a high level of complexity and adjusting them to the needs in the analytical, conceptual, and information presentation dimensions. However, it is important to note that human intervention is crucial in improving the tool¿s coherence, cohesion, precision, and relevance. This recognition of human input underscores the integral role of educators and professionals in education in the development and application of AI, as well as the high potential of AI as a complement to the creation of educational resources. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

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