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Case study: creating an 'AI for Academic Writing Skills' induction session for postgraduate life science courses
Jennifer Carter1,2, Anne Ferrey3, Hubert Lam1
1Nuffield Department of Population Health, University of Oxford, U.K.
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.
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Patient outcomes reflect the patient's response to the goal rather than what the nurse aims to achieve. Terminology should be observable and measurable to avoid the reader's interpretation. The desired outcome should be realistic and achievable in the designated care timeframe. Expected outcomes should align with adjunctive therapies. The outcome should enhance care...
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