Examining Canadian Undergraduates’ Perspectives with Using GenAI for Learning

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.