Structured Development of Learning and Assessment Tasks to Prevent Generative AI Misuse and Enhance AI Literacy in the Faculty in Physiotherapy Education.

OBJECTIVE

The rapid emergence of generative artificial intelligence (GAI) in higher education necessitates redesign of learning activities and assessments to uphold academic integrity and foster AI literacy. This article presents a structured approach to developing educational strategies that mitigate GAI misuse while enhancing students' understanding of GAI, with a focus on collaborative faculty engagement and curricular adaptation in physiotherapy education.

METHODS

Using the Quality Implementation Framework (QIF), we conducted a comprehensive review of all courses within a Swedish physiotherapy program employing a problem-based learning (PBL) model. Faculty-wide, time-bound development initiatives were implemented, including targeted AI literacy training. A student survey was conducted to assess GAI usage patterns and perceptions.

RESULTS

Assessment formats were adapted to emphasize clinical reasoning and critical thinking, reducing opportunities for GAI misuse. Standardized guidelines on acceptable GAI use were integrated across all courses. The survey results 2 months after implementation indicated diverse usage patterns: 13% of students reported daily use of GAI, while 24% had never used it. Additionally, 42% felt adequately informed about GAI. Faculty AI literacy and confidence improved through structured group work and feedback, supporting the integration of AI-related tasks into the curriculum.

CONCLUSIONS

The systematic approach using QIF and PBL, expert support, faculty champions, problem-solving strategies, and feedback, enabled meaningful curricular changes within 4 months. The variability in student GAI use underscores the need for equitable AI literacy education. This approach not only reduced the risk of GAI misuse but also enhanced faculty preparedness, offering a scalable model for other health sciences programs.