A weekly podcast exploring how artificial intelligence is transforming educational research
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Same Work, Different Feedback: Melissa Warr on Hidden Bias in AI
Azadeh and Guy talk with Dr. Melissa Warr, assistant professor of educational design and learning technologies at New Mexico State University, about how AI can quietly reinforce inequity in classrooms. Melissa shares new findings comparing 2024 and 2026 models. AI scoring of identical student work has become less biased, but the written feedback has not. When the AI is told a student likes rap music instead of classical, it writes at a lower reading level, gives more direct instruction, and talks down to the student. This echoes schooling’s “hidden curriculum,” where some students are treated as less capable.
The conversation covers why teachers should disclose when they use AI for feedback, and how generative AI’s social nature pushes TPACK toward a stronger focus on context. Melissa describes classroom activities that make bias visible. In one, students generated images of the Three Little Pigs set in India and Mexico and spotted the stereotypes. In another, veterinary science students found that AI recommended oxygen for a cat with pneumonia at a city clinic but not at a low-resource one. She also explains why she protects AI-free time each morning, and why “one-to-three” (students talking to each other while using AI) may matter more than one-to-one devices. Her activities are available at equityandai.net.
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit guyonai.substack.com (https://guyonai.substack.com?utm_medium=podcast&utm_campaign=CTA_1)
28 Oct 2026
Beyond the Right Answer
Can AI help students become better thinkers, or does it make it too easy to avoid the struggle that leads to real learning? Azadeh and Guy sit down with Dr. Lawrence Chen, Professor of Electrical and Computer Engineering at McGill University, to explore how AI is reshaping engineering education. They discuss productive failure, the limitations of traditional assessments, and why focusing on the learning process matters more than ever. Dr. Chen shares how he uses an “AI second” approach in his engineering ethics course, encouraging students to think and collaborate before turning to AI to challenge their ideas. The conversation also explores AI bias, diverse perspectives, and the importance of questioning AI-generated answers. As Dr. Chen reminds us, plausibility is not validity, and learning to recognize the difference is an essential skill for future engineers.
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit guyonai.substack.com (https://guyonai.substack.com?utm_medium=podcast&utm_campaign=CTA_1)
19 Oct 2026
What Students Should See Us Doing With AI?
Nick Husbye returns for a second conversation with Azadeh and Guy. The first question is about modeling. Pre-service teachers learn as much from how we use AI in our own courses as from anything we teach about it. Nick describes narrating his AI use out loud, writing AI expectations directly onto assignment sheets, and showing students where the tool failed him. He walks through a Claude skill he built from research on multiple-choice item design to revise his quiz banks, and the flawed items that still slipped through. The one thing he never wants students to see is him handing his pedagogical thinking over to AI, or blaming a bad question on the tool.
The conversation turns to instructors whose strong reactions to AI end up teaching students to hide their use. Nick shares how his summer children’s literature course moved from a stack of AI slop to an assignment where students submit their full chat dialogue.
In the second half, Guy asks how to prepare teachers for schools with AI policies that range from open access to complete bans, often with mentor teachers who are behind on the technology. Nick starts with what teachers can control, which is their own preparation. He also talks about using AI to put expert knowledge into words for novices, protecting human connection in a world of self-checkout lanes, and building the professional confidence to know when to adopt and when to hold a line.
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit guyonai.substack.com (https://guyonai.substack.com?utm_medium=podcast&utm_campaign=CTA_1)
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