At our most recent AIR|GPT podcast meetup (our regular monthly “airport” gathering), Ruben Puentedura introduced us to the concept of “pedagogical debt,” inspired by comment by Ian Bogost (in a recent Atlantic article titled AI Has Broken High School and College). Similar to technical debt in software development, pedagogical debt represents the accumulated compromises and shortcuts in education that seemed reasonable at the time but have created long-term problems. These are teaching practices we know are questionable, inadequate, or uninspiring, yet continue using. You can listen to the episode by following the link below or on your favorite podcast app.

AIR | GPT: Pedagogical Debt: What We Owe Our Students in an AI World

Our conversation acknowledged two undeniable truths: students ultimately bear the cost of this debt, and generative AI is now sending the past-due notices. As Ruben explained, we’ve accrued this debt over decades (large class sizes, assignment designs without meaningful feedback, focusing on outputs rather than learning processes) and now the chickens have come home to roost. It is not possible to coast along any longer.

In this conversation, worth listening in full, I emphasized that we owe a debt to the future, to our students, to transform education in ways that honor genuine learning and engagement. This debt isn’t just about fixing past mistakes; it’s about our moral obligation to prepare students for a future where AI is just one of many planetary level disruptive forces.

During our discussion, Caroline Kurban, Liz Kolb, Ruben, Helen Crompton and I (with Errol St. Clair Smith, or intelligent designer, guiding the conversation) shared practical approaches we’re implementing in our classrooms to address these challenges head-on.

I shared my ongoing experiments (both last semester and this one). Specifically, I described my current Education by Design class as one approach to “redeeming ourselves.” It’s a unique experiment bringing together high school students, undergraduates, masters students, doctoral candidates (both PhD and EdD), and clinical faculty. We meet openly, with projects that are intentionally open-ended, where grades take a backseat to meaningful engagement. This approach prioritizes genuine learning over traditional assessment, creating a community where participants become, as one student (from my last semester) said, “more than the sum of ourselves.”

At the end of the day, much of what we are talking about is not new. Educators have known this all along, and as we reflected on our journey in education, T.S. Eliot’s words resonated deeply: “We shall not cease from exploration, and the end of all our exploring will be to arrive where we started and know the place for the first time.” Perhaps this is the essence of addressing pedagogical debt, returning to the fundamental purpose of education with new wisdom, seeing teaching at its best as a form of collaborative discovery.

Below is a list of all the episodes of AIR | GPT

1. The Creators of SAMR, TPACK, Triple E, SETI, and GenAI-U Launch New Podcast With a Review of NoteBook LM
2. Para-social Relationships: The Pros and Cons of Falling in Love With Generative AI
3. 2024 Mic Drop on the AIR GPT Podcast
4. AI Schools Are Catching On: What They Get Wrong, What They Get Right, What They Are Teaching Us About Teaching
5. Some Think More Deeply With Gen AI, Some Less: Here’s What’s Behind The Emerging Critical Thinking Divide
6. The Science and Art of Teaching Creativity in the Age of Gen AI: What Every Educator Needs to Understand
7. The Blindspots in AI Guardrails, Guidelines, and Good Intentions: What We Need, What We Don’t, and Why
8. All Gen AI Studies Are Not Created Equal: What These Two Highly Cited Studies Overlooked, Why It Matters
9. Grok This: When AI Goes Off the Rails, What Educators Need To Know About the Root Causes
10. Three Years of Gen AI: The Lessons We’ve Learned, What We Plan to Do Differently As We Head Back to School
11. Pedagogical Debt: What We Owe Our Students in an AI World