Designed for Learning!: From Fear to Fluency: Rethinking AI in Post-Secondary Education

I am writing this post as a follow-up to a recent panel discussion I participated in at the annual BEAC/BCCAT meeting. The Business Education Articulation Committee (BEAC) is part of the BC Council on Admissions and Transfer (BCCAT), bringing together educators to explore key issues in post-secondary education. The panel, titled “Getting Comfortable with AI,” was organized by BEAC Chair, Garima Kamboj and moderated by Vice-Chair, Jennifer Duffy.

I had the pleasure of sharing the virtual space with thoughtful colleagues Gwen Nguyen and Fuat Ramazanov as we discussed the evolving role of Artificial Intelligence (AI) in post-secondary teaching and learning.

Below are some of the key questions we explored and the reflections I shared during the session.

"If there was one mindset shift you would recommend to post-secondary educators about AI, what would it be?"

One Mindset Shift: From Answers to Questions

A video of Steve Jobs from 1983 recently shifted my own mindset. In it, he imagines a world where machines can hold and convey the spirit of thinkers like Aristotle allowing us to ask them questions even after they’re gone. That future is here.

So, if there’s one mindset shift I’d recommend to educators, it’s this: Let’s stop treating AI as a shortcut to answers, and start seeing it as a way to deepen our questions.

The magic of education has never been about having the right answers. It’s about learning how to ask better ones. I don’t see AI as replacing educators. I see it redefining our role from content providers to social architects helping learners make meaningful connections with themselves, others, their work, and the world. In that world, AI becomes Augmented Intelligence, not Artificial Intelligence.

"Should academic integrity policies explicitly include guidance on AI use? If so, what might that look like in a way that is fair, inclusive, and educative?"

Academic Integrity: From Policing to Partnership

Yes, academic integrity policies should explicitly address AI. But not in a way that is rigid or punitive. Instead, I advocate for policies that are transparent, contextual, inclusive, and educative.

Here’s what that can look like:

- Make expectations visible. Clearly articulate when and how AI can be used and align AI use with course learning outcomes/objectives or the context of teaching.
- Prioritize disclosure over detection. Encourage statements like: “I used AI to brainstorm ideas” or “I checked clarity using a tool and revised it myself.” These aren’t confessions, they’re reflections.
- Avoid the binary. Move beyond “allowed vs. banned” and toward a continuum of use from “no AI” to “AI as co-creator.”
- Include learners. Involve students in setting norms. Ask them what responsible AI use looks like in your course context. Let policies be co-created, not just imposed.
- Model teaching with integrity rather than teaching for integrity.

In my experience, people rise to clarity. Students grow when they understand not just what is expected, but why it matters.

"What does digital fluency around AI look like for both instructors and students?"

Digital Fluency: From Tool Use to Learning Agility

Digital fluency isn’t just about knowing how to use AI tools. It’s about knowing when, why, and to what extent to use them and when not to.

For instructors, this includes:

- Enhancing human agency in teaching and learning
- Developing judgment around the technical, ethical and pedagogical dimensions of AI
- Practicing with real-world cases of integrating AI, not just introductory demos of AI tools
- Leveraging AI for driving their own lifelong professional development

It is important that instructors and educators apply frameworks like UNESCO’s AI Competency Framework for Teachers into their teaching practice.

Educators don’t need to become AI experts. But we do need to become AI-literate facilitators and be able to guide students in a landscape filled with both promise and peril.

For students, AI literacy must include:

- Learning to co-create with AI
- Critically evaluating outputs
- Practicing prompt engineering
- Understanding bias and ethical considerations

Both instructors and students need learning agility and develop their ability to adapt to rapidly evolving tools and systems. Our expectations must shift from mastery of a fixed set of AI tools to the ability to learn, unlearn, and relearn how we work with AI.

“What is one actionable step you recommend educators take next week to deepen their comfort with AI?”

One Action to Take Next Week

I invite everyone to try a "Plus One" mindset. This is a concept I love from Universal Design for Learning.

Think of one challenge you or your students consistently face. Then ask: Can AI help reduce or remove this barrier?

For example, maybe students often struggle with understanding assignment instructions. This leads to confusion, low-quality submissions, or a flood of emails. Could you use AI to rewrite your instructions in plain language? Or perhaps your students have trouble grasping abstract concepts. Could AI help generate analogies, visuals, or real-world examples at different levels of complexity giving students multiple ways to connect with the content?

You don’t need to overhaul your teaching. Just take one meaningful step. That’s the heart of Plus One thinking.

Getting comfortable with AI isn’t a sprint, it’s a marathon. So, we have to keep building our stamina and strengthening our muscles. And like any good workout, it helps to run alongside others. Let's stay connected and keep the conversation going!

Resources:

UNESCO AI Literacy Competencies – An overview: https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers?hub=32618

UNESCO AI Literacy Competencies for Teachers: https://www.unesco.org/en/articles/ai-competency-framework-teachers

UNESCO AI Literacy Competencies for Students: https://unesdoc.unesco.org/ark:/48223/pf0000391105

GenAI in Teaching and Learning Toolkit for Educators: https://opentextbc.ca/teachingandlearningwithai/front-matter/introduction/