In this episode we explore the promise, and the limits, of “closed loops” in AI-enhanced classrooms.

We talk about whether AI can really give teachers and school systems a complete picture of a student’s learning journey: where they are, what they need next, and how best to support them.

Topics covered:

• What “closed loop” means in AI-supported teaching and learning
• The appeal of real-time insight into student progress
• Why AI may work well for highly motivated students but miss many others
• The danger of mistaking niche AI learning models for universal solutions
• What technology can measure — and what only teachers can understand
• Why student motivation, context, and meaning-making still matter
• What district leaders should watch for when evaluating AI-driven personalization
• Why classroom relationships remain central, even in data-rich environments