Rethinking AI in the Classroom: Meet MSVU’s Dr. Michael Pin-Chuan Lin

Picture a learning tool designed not simply to hands over answers. Instead, it asks: What do you already understand? Where's the gap? What will you try next? That's the premise behind MetaMentorAI, a flagship project of the Artificial Intelligence in Education (AIEDU) Lab led by Mount Saint Vincent University (MSVU) Assistant Professor of Education Dr. Michael Pin-Chuan Lin, who serves as a principal investigator on the SSHRC-funded project.

Built on years of research into self-regulated learning, MetaMentorAI combines learning analytics, metacognitive prompts, knowledge visualization and conversational feedback to help students plan, monitor and reflect on their own learning rather than outsource it.

"The goal is not to create another tool that simply gives students answers," Michael says. "It's to provide guidance that helps them recognize what they understand, identify gaps, decide what to do next and take greater responsibility for their learning."

A lab-wide question

MetaMentorAI is one piece of a broader research program. The AIEDU Lab brings together educational technology, learning sciences, self-regulated learning, learning analytics and responsible AI design around a single central question: how can AI be designed and used in ways that help people become more capable, reflective, and independent learners?

Beyond MMA, the lab's research spans AI-supported writing and revision, generative AI in computer science education, emotion-aware learning support, agentic AI and a growing focus on AI ethics and student disclosure, including why students choose to disclose or conceal their AI use and how instructors can gather meaningful evidence of learning in classrooms where AI is everywhere.

Global, cross-institutional network

The AIEDU Lab connects researchers across MSVU, Simon Fraser University, Athabasca University, Dalhousie University, the British Columbia Institute of Technology, McGill University, Fairleigh Dickinson University and the Education University of Hong Kong, with a wider network reaching Taiwan, mainland China, Spain and the United States. That breadth, Michael says, is essential: "AI in education cannot be studied adequately from one discipline or one educational setting."

Research involving AIEDU Lab members has received substantial SSHRC support. Michael serves as principal investigator on an Insight Grant and an Insight Development Grant and as co-applicant on a second Insight Development Grant. Additional proposals are currently in development.

Evidence over assumption

Michael is careful to distinguish genuine learning gains from mere convenience.

"A student may complete an assignment more efficiently with AI without developing a stronger understanding of the subject," he says.

One of the lab's central goals is producing credible evidence of when AI actually improves learning, and when it simply substitutes for a learner's own thinking.

That perspective also informs Michael's advice to instructors. Rather than relying solely on final products as evidence of understanding, Michael suggests instructors build in more opportunities for students to make their thinking visible, through brief oral explanations, drafts or reflections. Instead of asking "Did you use AI?", he recommends asking students to describe which tools they used, how they used them and what intellectual contribution remained their own.

Why MSVU?

Michael's path to this research began during his doctoral studies at Simon Fraser University, years before the public release of ChatGPT, when he and his colleagues developed a chatbot to support postsecondary students' peer feedback and argumentative writing. Today, he says MSVU's Faculty of Education and its commitments to social justice, equity and inclusive teaching make it the right home for the work.

"When we introduce AI into education, we need to ask who has access, whose language and knowledge are represented and whether the technology reduces or reinforces existing inequalities," he says. "These are educational and ethical questions, not just technical ones."

For Michael and the AIEDU Lab, the future of AI in education isn't about replacing teachers - it's about making sure human judgment and student learning stay at the centre.