: This study presents the redesign of a Python programming course for medical students at the University of Pavia, integrating the Generative AI (GenAI) tool Gemini within Google Colab to support learning and problem-solving. To evaluate students' experiences, attitudes, and learning strategies, a two-part post-course questionnaire was developed, combining an adapted Technology Acceptance Model (TAM) and the Learning Strategies Scale for Large Language Models (LSS/LLMs-6). A panel of domain experts assessed the questionnaire's content validity, yielding strong overall agreement (CVI = 0.98). The results highlighted the TAM's robustness and identified minor refinements needed for the LSS/LLMs-6 to better distinguish constructive (metacognitive) from dysfunctional (passive) GenAI use. This preliminary work, limited by the small expert panel and the absence of empirical data, sets the foundation for a larger study to be conducted at the end of the 2025/2026 academic year. Overall, the integration of GenAI in medical programming education offers a promising yet delicate opportunity to democratize access to computational tools while ensuring that AI acts as a means to enhance reasoning rather than replace it.
Redesigning Python Programming Course in the Generative AI Era: An Italian Case Study
Nicora G.
;Larizza C.;Parimbelli E.;Quaglini S.
2026-01-01
Abstract
: This study presents the redesign of a Python programming course for medical students at the University of Pavia, integrating the Generative AI (GenAI) tool Gemini within Google Colab to support learning and problem-solving. To evaluate students' experiences, attitudes, and learning strategies, a two-part post-course questionnaire was developed, combining an adapted Technology Acceptance Model (TAM) and the Learning Strategies Scale for Large Language Models (LSS/LLMs-6). A panel of domain experts assessed the questionnaire's content validity, yielding strong overall agreement (CVI = 0.98). The results highlighted the TAM's robustness and identified minor refinements needed for the LSS/LLMs-6 to better distinguish constructive (metacognitive) from dysfunctional (passive) GenAI use. This preliminary work, limited by the small expert panel and the absence of empirical data, sets the foundation for a larger study to be conducted at the end of the 2025/2026 academic year. Overall, the integration of GenAI in medical programming education offers a promising yet delicate opportunity to democratize access to computational tools while ensuring that AI acts as a means to enhance reasoning rather than replace it.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
