Student perspectives on AI-supported formative assessment in pharmacology

High-quality feedback is crucial for helping medical students understand and apply core concepts of pharmacology, yet personalized feedback is resource-intensive to produce. Artificial intelligence (AI) offers a potential solution, but little is known about students' perspectives on AI-generated feedback. This study investigated how medical students perceived and made use of AI feedback in a formative assessment while studying fundamental pharmacology.

We used a qualitative approach to explore how third year medical students perceived AI score and feedback after completing a formative test containing eight short-answer questions on core concepts in pharmacology. Data were collected using focus groups (n = 11). In an iterative thematic approach, the transcripts were analysed and themes identified.

Three themes representing factors that affect students' experiences with AI-generated feedback were identified in the analyses: (1) trustworthy and accessible feedback information, (2) aligning the feedback with the study programme and (3) student feedback literacy.

Our findings illustrate the complex interplay between technological, contextual and individual factors in shaping the effectiveness of AI-supported formative assessment. Students found the AI-generated feedback to be useful and mostly reliable, but raised concerns regarding AI being overly positive, the timing and mandatory nature of the assessment, and the workload required to engage with lengthy narrative feedback comments. While AI tools have the potential to provide reliable, personalized and effective feedback, its implementation needs to ensure that students are equipped with feedback literacy and that the educational programme incentivizes meaningful engagement with feedback.