Role of the learning developer in teaching responsible use of AI: examples and challenges from embedded social sciences
DOI:
https://doi.org/10.47408/jldhe.vi37.1695Keywords:
artificial intelligence, learning developer role, collaborative teaching, social sciences, challengesAbstract
This academic year has seen a significant increase in requests for embedded teaching on the university’s generative artificial intelligence (AI) guidelines, which our learning development team had a significant role in developing. The session highlighted the challenges faced when creating sessions within the ever-changing AI landscape (Bobula, 2024), and the importance of meaningful dialogue with academic staff to develop a shared understanding about how students can use AI responsibly.
Collaborating with colleagues has highlighted various positions academics have taken in engaging students with AI. Our role has involved championing the university’s guidelines in discussions with academics, sometimes influencing a change in how AI is viewed or used. Developing sessions collaboratively with academics has been imperative in ensuring a consistent message for students about the responsible use of AI. While these collaborations have been successful, the ever-evolving AI landscape and increased expectations from academics raises questions about learning developers’ role in teaching this content, which we explored with delegates in this session.
We also outlined the bespoke activities developed for students, including mapping studies using ResearchRabbit, which have garnered positive feedback from staff and students. Whilst we have adapted our approach for each discipline, the key aims of these sessions have remained the same: to encourage students to critically engage with AI tools to determine their value and effectiveness. However, rapidly progressing technology is challenging us as learning developers to think creatively about how to engage students with meaningful activity to empower responsible use of AI.
References
Bobula, M. (2024) ‘Generative artificial intelligence (AI) in higher education: a comprehensive review of challenges, opportunities and implications’, Journal of Learning Development in Higher Education, (30). Available at: https://doi.org/10.47408/jldhe.vi30.1137
Perkins, M., Roe, J. and Furze, L. (2024) The AI assessment scale revisited: a framework for educational assessment. Available at: https://doi.org/10.48550/arXiv.2412.09029
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Journal of Learning Development in Higher Education

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).