Bridging basic physiology and clinical reasoning: student perceptions of a case-based collaborative activity with AI support.

چکیده اصلی

Teaching membrane transport in introductory physiology is challenging because students often struggle to integrate membrane transport, electrochemical gradients, and related mechanisms into clinically meaningful reasoning. To address this problem, a case-based collaborative activity was introduced in a first-year cell physiology course for undergraduate life and medical sciences students. Small groups analyzed a membrane transport disorder, explained the underlying physiological defect, and were permitted to use AI tools during the task. After the activity and short presentation, the students completed the Cell Physiology Bridge & Interaction Survey, an adapted Likert-scale questionnaire assessing perceived links between basic physiology and pathology, perceptions of AI use, and the role of peer interaction in problem-solving. Students reported that the activity strengthened their ability to connect transport mechanisms to disease, increased their confidence in explaining mechanistic failure, and enhanced the relevance of basic physiology to their future studies. AI was viewed as a useful and efficient support tool, but peer discussion remained important for conceptual clarity and deeper understanding. When groups encountered difficulty, students most often reported turning first to AI tools, followed by group discussion. These findings suggest that students perceived a brief, clinically anchored collaborative activity as helpful for connecting mechanistic understanding with clinical reasoning in introductory physiology. Incorporating AI as a supplementary tool may enhance learning efficiency without replacing the critical role of peer collaboration.NEW & NOTEWORTHY This study describes a simple, reproducible case-based collaborative activity in an introductory undergraduate physiology course in which students were permitted to use AI tools while solving clinical problems involving membrane transport disorders. The activity was associated with stronger perceived links between membrane transport and disease, greater confidence in mechanistic explanation, and continued reliance on peer discussion for deeper understanding. These findings suggest that AI can support, but should not replace, collaborative learning in physiology education.

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