AI policy in higher education
Relational-affective considerations for governance in a Canadian university case study
DOI:
https://doi.org/10.32674/ndvc6674Keywords:
Generative Artificial Intelligence, Higher Education Policy, mixed-methods case study, STEM higher education, relational-affective dimensionAbstract
Generative artificial intelligence is reshaping higher education and raising new questions for policy, pedagogy, and governance, especially in STEM-related contexts. This mixed-methods case study examined faculty perceptions of the pedagogical, governance, and operational implications of AI at a Canadian university. Survey and focus group findings revealed limited current use, stronger anticipated future use, and widespread concerns about academic integrity, trust, workload, authenticity, and professional support. The analysis suggests that relational and affective conditions shape how AI policy is interpreted and enacted in academic practice. It further proposes that a relational-affective dimension may extend existing policy frameworks, particularly in STEM-oriented governance where technical judgement, accountability, and human oversight remain central.
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