Artificial Intelligence-Enabled Competency Assessment in Jordanian Pharmacy Programs: A Vision for the Future
Main Article Content
Keywords
Artificial intelligence, competency-based assessment, pharmacy education, Jordan, educational technology, adaptive learning, simulation
Abstract
Background: The evolution of pharmacy education to competency-based education (CBE) demands novel assessment tools that are objective, prompt and scalable. Artificial Intelligence (AI) is considered a disruptive power in medical education worldwide, but its penetration in Jordanian pharmacy education is unassessed. Objective: To model the integration and impact of AI-enhanced competency assessment instruments in the education of pharmacy at a university and its college. Methods: Mixed-methods design was utilized. A virtual cohort of 200 students was used to simulate AI-proctored examinations at the Faculty of Pharmacy, Mutah University. Simulation results consisted of diagnostic accuracy, feedback quality, faculty burden, and student/faculty impressions. From the hypothetical focus group simulations, qualitative data was synthesized. Results: Simulated AI evaluations were more accurate than traditional evaluations diagnostically above threshold levels at 94% versus 76%, respectively, as well as provided immediate feedback and resulted in a 70% reduction in faculty time for grading. Students expressed relatively high levels of satisfaction with AI feedback clarity (4.6/5) and fairness (4.7/5). Faculty reported increased congruence with curriculum objectives and augmentation of personalized teaching. Conclusion: AI-based assessment systems had potential to enhance competency tracking, support high-quality feedback and be time efficient within Jordanian pharmacy education. A staged approach to real-world implementation is advised, along with training of stakeholders and regulatory support.
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