Leveraging Case-Based Learning Exercises in Pharmacology Courses to Promote AI Readiness Among Student Pharmacists

Area of Science:

• Pharmacy Education
• Artificial Intelligence in Healthcare
• Metacognitive Skills Development

Background:

• Pharmacy curricula increasingly require integration of new technologies.
• Pharmacy students need enhanced confidence and metacognitive skills for effective AI tool utilization.
• Generative AI presents opportunities and challenges for evidence-based practice in pharmacology.

Purpose of the Study:

• To improve pharmacy students' confidence and metacognitive awareness in using artificial intelligence (AI) tools.
• To integrate generative AI into pharmacology coursework for AI readiness.
• To guide students in triangulating AI-generated information with evidence-based drug resources.

Main Methods:

• Second-year pharmacy students completed two case-based pharmacology assignments.
• Students received training in prompt writing for AI tools.
• AI-generated information was cross-verified with evidence-based drug references.
• Pre- and post-intervention surveys assessed confidence; a metacognition survey evaluated skills.

Main Results:

• Student confidence in using AI tools significantly increased from 64.0% to 89.4% (p<.001).
• Metacognitive skills in planning, monitoring, debugging, and evaluation showed improvement (74.6% to 94.9%).
• Key barriers identified were academic integrity concerns (69.5%), reliability (52.5%), and ethical issues (50.8%).
• Students expressed interest in using AI for concept comprehension and study guide generation.
• Recommendations included more AI training and clear academic integrity guidelines.

Conclusions:

• Case-based assignments effectively foster AI competency, confidence, and metacognitive skills in pharmacy students.
• Addressing academic integrity and reliability concerns is crucial for AI adoption in pharmacy education.
• Future pharmacy curricula should incorporate structured AI training and guidelines.