A Student Council for Generative AI Activity

Traditional approaches to engaging students on generative AI often rely on a small number of elected student representatives, assuming a singular “student voice.” Based on a large-scale student survey (N > 3,500), UBC found that student perspectives on AI use, support needs, and concerns are highly diverse and nuanced, mirroring the diversity of faculty views. To address the limitations of a single-representative model, UBC established a standing Student AI Council of 30 members to serve as an advisory and sounding board for institutional leadership on generative AI in teaching and learning.

An open call for expressions of interest invited students to submit a short statement outlining their motivation to join the Council. The call explicitly emphasized the importance of diversity in opinions, programs, levels of study, and attitudes toward AI, rather than recruiting only enthusiastic adopters. Council members were selected from a wide range of Faculties, disciplines, and year levels.

The Student AI Council meets four times per year, with optional work conducted between meetings. Students are compensated for their contributions beyond scheduled meetings. The Council is co-chaired by the Vice-Provost and Associate Vice-President, Teaching and Learning (Vancouver campus) and the Associate Vice-President, Students (Okanagan campus), ensuring cross-campus representation and direct connection to senior leadership.

Although the Council has only been convened for approximately six months, its impact is already evident across several institutional initiatives.

First, the Council led the development of a student-facing resource, 10 Things Students Should Know About Generative AI at UBC, drawing directly on themes identified in the 2024 student survey. This resource translates student perspectives into clear, accessible guidance for the broader student population.

https://academic.ubc.ca/teaching-learning/10-things-ubc-students-should-know/generative-ai

Second, Council members provided substantive feedback on the redesign of a repeat administration of the AI student perspectives survey planned for December 2025. Their input informed which questions should be retained for year-over-year comparison, which new items should be added to reflect changing contexts, and how survey language could be refined to better resonate with students. The Council also reviewed a companion faculty survey to enable cross-audience comparison. Following data analysis, Council members will assist in the creation of media assets to support dissemination of findings.

Finally, a subset of Council members is actively involved in refining, validating, and consulting on a student competency framework for generative AI. This work builds on earlier faculty and staff competency frameworks and ensures that student competencies reflect authentic student experiences and expectations. Participation in this work is remunerated, reinforcing the value of student expertise.

• Universal Design for Learning (UDL) framework
• Action research methodology (Stringer, 2008)
• Mixed-methods evaluation approach (Axinn & Pearce, 2006)
• Embedded professional learning for Unit Coordinators via Moodle and synchronous workshops
• Collaboration between academic staff, IT, learning designers, and institutional leadership
• Ethics-approved longitudinal data collection (UNE HR#20-083)
• Strong institutional leadership enabling scale-up to Project Uplift
• Alignment with university-wide learning and teaching strategy