Generative artificial intelligence and university study: a guide for students by the study advice team at the University of Reading

Authors

  • Georgia Koromila University of Reading

DOI:

https://doi.org/10.47408/jldhe.vi32.1474

Keywords:

GenAI literacy, student-facing online guidance, GenAI policy, LD advocacy

Abstract

In this showcase, we took our new student-facing generative Artificial Intelligence (AI) guide as a departure point for discussion around AI literacy support. We hoped to reflect with colleagues on resource development processes, including how we benefitted from wide-ranging and intersecting feedback, and how we navigated issues of policy. The motivation for the guide stemmed from our initial engagement with generative AI tools as they became widely available and highlighted in public and academic discourse. In addition, we quickly realised that AI was causing anxiety to colleagues and students, who expressed frustration with policy not keeping up with the need for clarity on emerging issues. Clearly, our students needed guidance on how to engage with this technology safely and ethically.

In building this resource, we aimed to strike a balance in tone and degree of complexity. Inspired by current reflections in Learning Development and higher education circles, we tried to highlight the range of emerging questions and implications that one should consider when exploring this technology in order to be in a position to harness its potential. We included examples and scenario-based exercises to encourage a critical approach.

The guide reached its published form after extensive scrutiny. Feedback from colleagues and students at the University Working Group on AI helped shape decisions around language clarity, content focus, selection of examples, and messaging on academic integrity. This was an empowering process, as it helped us feel secure in our stance whilst official institutional policy remained elusive.

So, what now and what next? The guide is being used by colleagues and students and received positive anecdotal feedback. We recognise, however, the need for regular updating in this fast-moving field. New themes for developing our guide include: AI for research, specialised AI-powered tools, and rules for acknowledging AI use.

Author Biography

Georgia Koromila, University of Reading

Georgia Koromila is a Study Adviser at the Library, University of Reading. Originally from the discipline of Archaeology, Georgia is a developing Learning Developer with interests in interdisciplinary collaboration, decolonising practice, inclusivity, global perspectives and working with international students, and, more recently, developing GenAI literacy. Georgia is a member of the ALDinHE Reflection Community of Practice.

References

University of Reading. (2024). Generative artificial intelligence and university study. https://libguides.reading.ac.uk/generative-AI-and-university-study

Downloads

Published

31-10-2024

How to Cite

Koromila, G. (2024) “Generative artificial intelligence and university study: a guide for students by the study advice team at the University of Reading”, Journal of Learning Development in Higher Education, (32). doi: 10.47408/jldhe.vi32.1474.