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This project explores the impact of AI text generation on 3rd-level education in Ireland, using modules delivered in the UCD School of Biology and Environmental Science (SBES) at University College Dublin. It was co-created by students and staff.
Experts anticipate that using artificial intelligence (AI)-based tools such as ChatGPT will become a new standard in our professional lives, but what are the implications of this disruptive technology for teaching and learning in higher education, especially in STEM subjects? We argue that rather than banning AI writing tools, both students and educators need to develop understanding of the possibilities and limitations associated with this technology. Further, AI usage needs to be addressed by university plagiarism and academic integrity guidelines.
This project explores the impact of AI text generation on 3rd-level education in Ireland, using modules delivered in the UCD School of Biology and Environmental Science (SBES). In this document you will our team presents the summary of progress to date and reflections on the key findings from the . We wish to thank the Strategic Alignment of Teaching and Learning Enhancement (SATLE) fund for making this project possible.
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This work is licensed under a CC BY license, allowing sharing and adaptation with proper attribution.
https://creativecommons.org/licenses/by/4.0/If you have modified or adopted this resource, share your version here. Tracking adaptations helps us measure impact and connects others with useful updates.
This OER is targeted at lecturers and describes an inclusive framework to integrate artificial intelligence (AI) learning design at third level.
This report draws on Patricia Gibson’s research around critical approaches to Artificial Intelligence (AI) in Education and the increasing automation of Educational Technologies (EdTech).
This resource was created to share the learning from teaching adults with intellectual disabilities (ID) in IADT college as part of a national suite of pilot projects.
Comparing student and educator perceptions of generative artificial intelligence for teaching, learning and assessment: results from two institutional surveys
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