AI is not a single fixed tool, but a rapidly evolving set of technologies that are transforming university teaching and learning. While the different models open up new possibilities, they also raise important pedagogical, ethical and practical questions about the nature of learning and assessment. Faculty and students use AI differently depending on their discipline, course, and learning context. Even within the same course, different AI tools are used depending on the task and learning objectives.
The “buffet” approach recognizes this and gives staff and students multiple avenues for responsible and meaningful engagement. Rather than relying on rigid one-size-fits-all policies, this model provides flexible, context-based support that fosters responsible and effective use of AI. We provide teachers and students with AI-powered guidance, resources, and advanced choices in learning, allowing them to choose the opportunities that best fit their role, discipline, confidence, and experience.
In our experience, faculty and students gain confidence and competency in using AI over time through repeated engagement, hands-on work, and interaction with colleagues. Therefore, teacher development should be seen as an agile, continuous process rather than a one-time event, allowing educators to update their instruction, assessment, and curriculum in line with changes in AI technology and educational practices.
Buffet model for AI skill development
A number of AI development programs for faculty and students are offered through the Center for Teaching, Learning and Technology (CTLT). Support includes university-wide workshops on responsible AI, as well as on-demand workshops and consultations tailored to the needs of departments, individuals, departments, and disciplines. CTLT also fosters an open community of practice where faculty share their experiences working with AI tools, challenges, and opportunities. Individual mentoring programs are also available upon request to support course redesign, assessment, research, and AI integration.
Within the “buffet” model, instructors can organize guest lectures on AI literacy, responsible use of AI, and discipline-specific applications through the center. The university has guidelines for undergraduate students on the appropriate use of AI in learning, and graduate students receive guidance on the responsible use of AI in research and dissertation writing. The guidelines are clearly explained through workshops and one-on-one consultation and coaching. I believe that the AI Support Buffet model will help faculty and students increase their confidence and ability to use AI responsibly over time.
This model continues to evolve in response to faculty and student feedback, institutional priorities, advances in AI technology, changing teaching and research needs, and developments in academic integrity.
Build your organization’s capacity and promote responsible and ethical use of AI with clear guidance, flexible learning opportunities, and practical support.
Flexible governance to adapt to AI evolution
As technology and educational practices change, strict policies quickly become outdated. Instead, universities should adopt flexible governance, provide clear guidance, and invest in continuous professional learning that reflects broader experience with AI. Again, the buffet approach provides a way forward. Regularly reviewing AI tools, use cases, and support helps institutions respond responsibly to change while fostering innovation, academic integrity, and quality teaching and learning.
The priority for teaching and learning centers is to empower faculty and students to use AI responsibly, rather than police its use. Their role is to build faculty and student confidence and competency in AI through workshops, mentoring, communities of practice, and discipline-specific examples. Capabilities develop over time, so teaching and learning centers must work closely with the provost’s office, deans, faculty, graduate studies, IT, libraries, and student or academic success centers to ensure that AI guidance remains relevant, consistent, and responsive.
Departments responsible for providing support and oversight around AI can develop policies, resources, and professional learning that support the responsible use of AI in teaching, learning, research, and assessment. The IT department evaluates and supports approved AI tools, the library provides guidance on AI literacy, information literacy, copyright and citation, and the Student Success Center helps students develop responsible AI practices and effective learning strategies. Graduate Studies supports the responsible use of AI in research and supervision. Regular collaboration and feedback from faculty and students allows universities to continually review and update AI guidance as technology, policy, and educational needs evolve.
Introducing a buffet support approach to AI teacher training
- Design your AI literacy and competency programs to be flexible rather than one-size-fits-all.
- Use clear principles rather than hard and fast rules.
- Move from a single enforcement policy to coordinated support.
- Enable context-specific access to the use of AI across disciplines.
- Provide mentoring on AI course and assessment redesign as needed.
- Share practical and domain-relevant examples in the responsible use of AI.
- Create a space for faculty and students to reflect and provide feedback on the challenges and opportunities of using AI for teaching and learning.
- Continually adapt faculty and student support programs to the evolving use of AI.
Ben Kay Daniel is Professor of Artificial Intelligence in Education, Research Methodology, and Educational Technology and Director of the Center for Teaching and Learning at the University of Northern British Columbia, Canada.
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