Pedagogical Adaptation and Assessment Integrity in Canadian Higher Education
The rapid adoption of generative artificial intelligence challenges traditional pedagogical models and demands a fundamental re-examination of academic integrity frameworks within Canadian post-secondary education. Rather than treating generative tools purely through a deficit lens focused on detection and disciplinary sanctions, higher education institutions must address the systemic pedagogical gaps identified in broader educational research (Popenici & Kerr, 2017). As Zawacki-Richter et al. (2019) emphasize, much of the technological integration literature historically overlooks the central role of educators in developing nuanced instructional designs, creating vulnerabilities when disruptive tools emerge. The limitations of conventional evaluation methods become glaringly evident when algorithmic text generators produce plausible submissions, prompting scholars to argue that traditional written evaluations require thorough restructuring rather than superficial surveillance (Rudolph et al., 2023). Within the Canadian context, where provincial autonomy fosters diverse institutional responses, cultivating authentic assessment strategies is critical. Institutions that focus primarily on prohibition risk alienating students and failing to foster the ethical competencies needed in digital scholarship. Consequently, meaningful preservation of academic integrity in modern curricula relies on aligning learning outcomes with transparent AI literacy, fostering collaborative inquiry, and engaging educators directly in assessment transformation.