Student perspectives on AI-supported formative assessment in pharmacology

Area of Science:

• Medical Education
• Artificial Intelligence in Education
• Pharmacology Education

Background:

• High-quality feedback is essential for medical students' pharmacology learning.
• Personalized feedback is resource-intensive, prompting exploration of AI solutions.
• Student perspectives on AI-generated feedback remain largely unknown.

Purpose of the Study:

• To investigate medical students' perceptions and utilization of AI-generated feedback in a formative pharmacology assessment.
• To understand the factors influencing student experiences with AI feedback.

Main Methods:

• Qualitative study involving third-year medical students.
• Formative assessment with eight short-answer pharmacology questions.
• Focus groups (n=11) analyzed using iterative thematic analysis.

Main Results:

• Three key themes emerged: trustworthiness/accessibility of feedback, alignment with the study program, and student feedback literacy.
• Students perceived AI feedback as useful and mostly reliable.
• Concerns included AI positivity, assessment timing/mandate, and workload from lengthy feedback.

Conclusions:

• AI-supported formative assessment effectiveness depends on technological, contextual, and individual factors.
• Successful AI feedback implementation requires equipping students with feedback literacy.
• Educational programs must incentivize meaningful engagement with AI-generated feedback.