This page is multipurpose, but briefly it is:
- A record of all our GenAI programming
- A hub for all non-workshop CTE resources related to GenAI
- A place to share some the research and resources that inform our human-centric approach to GenAI in teaching & learning

Interested in attending any of these workshops? Check the events page for their next offering. If you are interested in organizing an offering specifically for your unit/department/faculty, please contact cte@uwaterloo.ca.
If you're seeking individual support, our Faculty Liaisons are often the best point of first contact.
Additional CTE GenAI Resources
Informing our Work
Although not comprehensive, the following represents a selection of research and resources that shape our approach to GenAI.
Learning
- Anderson, B. R., Shah, J. H., & Kreminski, M. (2024). Homogenization effects of large language models on human creative ideation. Proceedings of the 16th Conference on Creativity & Cognition.
- Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1).
- Pratschke, B. M. (2024). Generative AI and education: Digital pedagogies, teaching innovation and learning design (1st ed.). Springer.
- Wang, J., & Fan W. The Effect of ChatGPT on Students’ Learning Performance, Learning Perception, and Higher-Order Thinking: Insights from a Meta-Analysis. Humanities and Social Sciences Communications, 12(1).
- Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: A systemic review. Smart Learning Environments, 11(1), 28.
Assessment
- Chatfield, T. (2025). AI and the future of pedagogy (White Paper). Sage.
- Corbin, T., Bearman, M., Boud, D., & Dawson, P. (2025). The wicked problem of AI and assessment. Assessment & Evaluation in Higher Education.
- Corbin, T., Dawson, P., & Liu, D. (2025). Talk is cheap: why structural assessment changes are needed for a time of GenAI. Assessment & Evaluation in Higher Education, 50(7), 1087–1097.
- Digital Education Council. (2025). The Next Era of Assessment.
- Mao, J., Chen, B., & Liu, J. C. (2024). Generative artificial intelligence in education and its implications for assessment. TechTrends, 68(1), 58–66.
- Xia, Q., Weng, X., Ouyang, F. et al. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21(40).
Critical Perspectives
- Critical Media Lab. Before you adopt GenAI.
- Bozkurt, A., et al. (2024). The manifesto for teaching and learning in a time of generative AI: A critical collective stance to better navigate the future.
- Djerbal, Y., Brothers, K. (2025, June 11). The AI and Accessibility Paradox: Are We Solving Barriers or Reinforcing Them? [Conference presentation]. Teaching with AI Conference, University of Guelph (Online).
- Ferrara, E. (2023). Should ChatGPT be biased? Challenges and risks of bias in large language models. First Monday, 28(11).
- Tassis, A. (2025, June 9). Unpacking anthropomorphism: How we humanize AI and what it means for education [Conference session]. Teaching with AI Conference, University of Guelph (Online).
Academic Integrity and (Post)plagiarism
- Eaton, S. E., & Keyhani, M. (2025). The Pedagogical Ethics: Navigating Learning in a Generative AI-Augmented Environment in a Post-Plagiarism Era. Navigating Generative AI in Higher Education, 160–178.
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Gottardello, D., & Karabag, S. F. (2020). Ideal and actual roles of university professors in academic integrity management: a comparative study. Studies in Higher Education, 47(3), 526–544.
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McCabe, D., Butterfield, K., & Trevino, L. (2012). Cheating in College: Why students do it and what educators can do about it. Johns Hopkins University Press.
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Stone, A. (2023). Student perceptions of academic integrity: A qualitative study of understanding, consequences, and impact. Journal of Academic Ethics, 21, 357-375