ArticleMedical science educator2025
Trust in AI Feedback: Challenges in Pharmacy Education.
Article in Medical science educator, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- AI-Based Assessment Tools in Pharmacy Education.Research square · 2026Article
- Pharmacy Practice in Somalia: Addressing Educational and Regulatory Gaps: A Commentary.Advances in medical education and practice · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This pilot study examined students' trust in artificial intelligence (AI)-generated feedback using Microsoft Copilot in a master's-level pharmacy course. Thirty-six students, divided into nine groups, participated in two peer-feedback sessions. AI feedback was optional: 67% of groups used it in the first session and 56% in the second. Survey data showed that 60% of students found AI feedback clear, but only 40% found it useful. In contrast, peer feedback was consistently rated more relevant and actionable. Many students cited trust and quality concerns. Findings support the need for improved AI prompt design, training, and integration as a complementary feedback method. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-025-02440-6.
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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.