Background/Rationale: In higher education, assessments are frequently viewed by students as isolated, high-stakes hurdles rather than engaging learning opportunities. To bridge the gap between academic theory, authentic industry practices, and generative AI resistance, we redesigned the assessment framework for a second-year physiology unit around an interconnected, semester-long narrative arc.
Methods: Framed as a simulated internship at a global pharmaceutical company (Pharmagique Industries), students rotate through four corporate departments centred on type 1 diabetes therapeutics: Medical Affairs, Clinical Trials, Marketing, and R&D. The tasks are deeply interconnected; for example, students audit raw trial data in Rotation 2 and must use those exact verified findings to critique and re-record a misleading promotional video in Rotation 3.
To ensure academic integrity and authenticity, the framework leverages custom Learning Management System (LMS) design elements:
Results & Evaluation: Student perception, engagement, and skill development are evaluated via post-rotation surveys following each task. This presentation will report quantitative evaluation data on student engagement, perceived real-world relevance, and decision-making confidence under uncertainty, alongside qualitative feedback across all rotations.
Conclusions: By combining interconnected, real-world tasks with LMS gating mechanics, assessments can become immersive, AI-resistant learning experiences that drive deep engagement in large STEM cohorts.