AI tutors are more than just chatbots with content — they’re evolving into dynamic, personalized learning companions. In this episode of Inside the Learning Experience, we dig into what it really takes to build an AI tutor that does more than deliver answers. It’s about designing experiences that adapt to learners in real time, drawing on principles of learning science and pedagogy to support deeper understanding and mastery.
Building an effective AI tutor requires more than just loading up an LLM. It means integrating instructional strategies, adapting to different learner needs, and ensuring that content delivery aligns with clear learning objectives. From informal feedback to dynamic scenario-based learning, AI can personalize experiences on the fly, providing students with just-in-time support and challenge, based on how they’re progressing.
As these tools grow in sophistication, the question of scale looms large. Serving thousands of students while maintaining consistency and quality means rooting every interaction in clearly mapped competencies. The future of AI in education isn’t just about automation — it’s about designing systems that are smart, intentional, and deeply aligned with how people actually learn.
Hosted by Research Director Dr. Betheny Gross and featuring Lead Learning Experience Designer Christine McDonough, this episode dives deep into the architecture of AI-powered instruction and the systems that make it possible. Watch or listen using the links below to explore the future of teaching, learning, and authentic evaluation.
