Evidence map›Paper›PMID 41416455›Full record

ArticleEmerging topics in life sciences2025

Case study: creating an 'AI for Academic Writing Skills' induction session for postgraduate life science courses.

Jennifer Carter, Anne Ferrey, Hubert Lam, Kelly Webb-Davies, Damion Young, Barbara Zonta, Delia O' Rourke

Abstract read
In one paragraph

Article in Emerging topics in life sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jennifer CarterNuffield Department of Population Health, University of Oxford, U.K.ORCID 0000-0002-5298-4844
Anne FerreyNuffield Department of Primary Care Health Sciences, University of Oxford, U.K.ORCID 0000-0002-5644-2735
Hubert LamNuffield Department of Population Health, University of Oxford, U.K.
Kelly Webb-DaviesAI Competency Centre, University of Oxford, U.K.
Damion YoungMedical Sciences Division, University of Oxford, U.K.
Barbara ZontaDepartment of Pharmacology, University of Oxford, U.K.
Delia O' RourkeNuffield Department of Medicine, University of Oxford, U.K.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Student use of generative artificial intelligence (GenAI) technology in university is as ubiquitous as it is controversial, and students and staff need guidance on how to use it effectively, responsibly, ethically and critically. In this case study, we present the conception, design and evaluation of a pilot 'AI for Academic Writing Skills' induction session designed for postgraduate taught (PGT) students in Medical Sciences. The induction session was designed by an institution-wide collaboration between Master of Science (MSc) programme directors, senior learning technologists and senior business technologists in AI competency to provide approximately 100 PGT students with structured, practical training on ethical GenAI use in academic writing. To ensure equitable access for all students in the pilot, this initiative integrated ChatGPT4 via a paid application programming interface into the institution's virtual learning environment, Canvas, ensuring all the students had access to the latest version of the chatbot. Evaluation of the 'AI for Academic Writing Skills' induction session demonstrated that 100% of survey respondents rated the training positively, 86% found the academic writing lecture beneficial, and 100% found the lecture on general GenAI skills helpful. Furthermore, 82% appreciated interacting with the chatbot in group work, and 70% reported significantly reduced uncertainty about using GenAI in their academic work. This case study details our approach, which first surveyed students to assess current levels of engagement and confidence with GenAI tools. Based on these findings, we developed a scalable, evidence-based induction session on the ethical use of GenAI in academic writing. This report describes the process of creating this training, its impact on student confidence, and our reflections on how we will continue to refine the programme in future academic years.

Indexed as

Artificial IntelligenceBiological Science DisciplinesEducation, GraduateWritingCurriculumHumansPilot ProjectsStudentsacademic writingethical usegenerative AIinduction sessionpostgraduate taught

Identifiers

PMID41416455
PMCPMC12794324

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.