Examining Canadian Undergraduates’ Perspectives with Using GenAI for Learning

Ann-Kathrin Grenz; Soroush Sabbaghan; Michele Jacobsen

doi:10.21432/cjlt29124

Authors

Ann-Kathrin Grenz Fraunhofer Institute for Applied Information Technology FIT https://orcid.org/0000-0001-9849-4923
Soroush Sabbaghan University of Calgary https://orcid.org/0000-0002-2236-7693
Michele Jacobsen University of Calgary https://orcid.org/0000-0002-0639-7606

DOI:

https://doi.org/10.21432/cjlt29124

Keywords:

generative artificial intelligence, higher education, qualitative research, self-regulated learning

Abstract

The rapid emergence of generative artificial intelligence (GenAI) tools presents new opportunities and challenges for higher education, yet little is known about how undergraduate students choose to engage with these technologies. This study examined Canadian undergraduates’ perspectives on GenAI as a learning support across three phases of the lecture cycle: before, during, and after class. Using a mixed-format survey (N = 296), we analyzed 118 student-written responses through Mayring’s qualitative content analysis and mapped themes onto Zimmerman’s model of Self-Regulated Learning (SRL). Results indicate that students see GenAI as a versatile cognitive partner—supporting preparation before lectures, engagement and clarification during, and review and assignment help afterward. Students also expressed critical concerns about overreliance, accuracy, academic integrity, and data privacy, which align with vulnerabilities in SRL processes such as self-control, self-evaluation, and help-seeking. Findings highlight a conceptual shift from institutional framings of GenAI as a production tool toward student framings of GenAI as a mechanism for intellectual capacity building. We argue that deliberate integration of GenAI into teaching practices and institutional policies—aligned with SRL subprocesses—can support responsible, student-informed adoption. The study contributes timely evidence for educators and policymakers navigating the pedagogical and ethical dimensions of GenAI in postsecondary learning.

Author Biographies

Ann-Kathrin Grenz, Fraunhofer Institute for Applied Information Technology FIT

Ann-Kathrin Grenz is Researcher at Fraunhofer FIT in Germany, specializing in learning and generative AI. With a background in psychology and computer science, she explores how humans interact with intelligent systems and how AI can enhance education. Her work bridges technical innovation with evidence-based understanding of human behaviour. Email: Ann-kathrin.grenz@fit.fraunhofer.de ORCID: https://orcid.org/0000-0001-9849-4923

Soroush Sabbaghan, University of Calgary

Soroush Sabbaghan is Associate Professor at the University of Calgary and the inaugural Generative AI Educational Leader in Residence at the Taylor Institute for Teaching and Learning in Canada. His work focuses on the intersection of educational technology, teacher development, and equity, supporting inclusive and evidence-informed teaching practices for K–12 and higher education. Email: ssabbagh@ucalgary.ca ORCID: https://orcid.org/0000-0002-2236-7693

Michele Jacobsen, University of Calgary

Michele Jacobsen is Professor of Learning Sciences at the University of Calgary in Alberta, Canada. Her research examines technology-enhanced learning, graduate supervision, and student experience in higher education. She co-leads the National Community of Practice on Supervision and publishes widely on online learning, graduate education, and the scholarship of teaching and learning. Email: dmjacobs@ucalgary.ca ORCID: https://orcid.org/0000-0002-0639-7606

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