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Designing Effective Laboratory Sessions of AI in Medicine: A Practical Relevance Index
Gheorghe Ioan Mihalas1, Bogdan Suceveanu1, Violeta Turcus1
1Vasile Goldiş Western University Arad, Romania.
Introduction:
Artificial Intelligence in Medicine (AIM) is increasingly included in medical curricula, yet the design of laboratory sessions remains insufficiently structured. While theoretical content can be positioned using frameworks such as the Curricular Relevance Index (CRI), fewer tools exist to evaluate practical activities.
Methods:
This paper introduces the Practical Relevance Index (PRI) for assessing the educational value of laboratory sessions, particularly hands-on activities, along five dimensions: conceptual deepening, instrumental competence, result interpretability, critical thinking, and curricular alignment. PRI is illustrated through a prompt-engineering laboratory session, with scores assigned by the instructor and compared with student feedback (n = 115).
Results And Conclusion:
Results show consistent positive evaluation and variation across dimensions and student experience levels. PRI, together with CRI, supports a more coherent alignment of theoretical instruction and practical training in AIM education.
