GenAI has moved from novelty to everyday infrastructure in education, whether it is endorsed or not. Rather than focusing on speculative futures such as artificial general intelligence, this webinar examines how current forms of GenAI are already reshaping learning practices, assessment and academic norms.
Drawing on the concept of postplagiarism and original survey data on postsecondary students’ perceptions of creativity, this session explores a central tension: While AI tools gain traction because of their convenience, students increasingly perceive them as creativity-enhancing at the level of learning and understanding, even when the ideas involved appear routine to experts. At the same time, perceived creativity does not always align with measurable changes in creative academic practice.
This session situates these findings within a broader conceptual discussion of trust in AI as a cognitive artifact, distinguishing between competitive and complementary forms of trust and their implications for creativity in learning. Building on ideas previously presented in the Postplagiarism Speaker Series, participants in this webinar will leave with a clearer framework for understanding creativity as a core tenet of postplagiarism and for navigating the practical implications of AI use in teaching and learning.
Key takeaways:
- AI in education is already reshaping practice. The session focuses on GenAI as it exists today, not speculative discussions of AGI or ASI, and examines how current tools challenge assessment, learning design and academic norms.
- Convenience explains adoption, but learner insight explains persistence. Students continue using AI not only because it is efficient, but because it supports moments of understanding that are new and meaningful to them, even when those ideas appear routine to experts.
- Creativity is a core tenet of postplagiarism, understood developmentally. Postplagiarism foregrounds creativity as learner-centred meaning-making rather than expert-level originality alone.
- Perceived creativity and measurable creative outcomes do not always align. Students may experience AI-supported learning as creative without clear evidence of deeper or more original academic work.