What AI is Teaching us about Teaching

Hype and fears about generative AI are everywhere now. The rapid development of AI tools that can manage text, images, and data has created a dizzying array of possibilities and a range of challenges in our teaching (and beyond). The developing programs on teaching with genAI, piloted by our colleagues at the Writing in the Disciplines program, have taught us a fair bit. Perhaps the most important thing we’ve learned is that people matter, and that creating trust is key to navigating this (or any) technology.

Writing is about much more than generating words on a page or screen. Teaching is about much more than collecting the words that students generate. What makes learning happen are relationships. We help students see the relationships or connections between the work we assign and the rest of their lives. We create relationships as we connect with students and assess their work, and we help students form identities in relation to what we teach, and to each other.

The key pedagogical issues involved in genAI are fundamental:

• How do we communicate the value of learning processes?
• How do we make the work students do as interesting and meaningful as possible?
• How do we engage with students around their writing and the tools they use?
• How do we build relationships with students as a way to help them to stay engaged?

Our approach to thinking about genAI, then, keeps coming back to trust. It takes trust to create learning relationships, and it takes trust to successfully convey the connections between our courses, the rest of a student’s program, and work and community life. It also takes trust within a teaching community to have open and honest conversations about what learning can look like as technologies change so quickly round us.