ArticleBritish journal of clinical pharmacology2026
Student perspectives on AI-supported formative assessment in pharmacology.
Article in British journal of clinical pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Formative feedback to improve pharmacology learning: Proposed principles and guidelines for effective practice.British journal of clinical pharmacology · 2026Guideline
- AI-Based Assessment Tools in Pharmacy Education.Research square · 2026Article
- Student perspectives on AI-supported formative assessment in pharmacology.British journal of clinical pharmacology · 2026Article
- Using assessment in pharmacology to drive learning in the right direction.British journal of clinical pharmacology · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
aimsHigh-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.
methodsWe 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.
resultsThree 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.
conclusionsOur 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.