The future of educational technology

Episode Summary

Executive Summary: The episode explores how generative AI is reshaping education, from cheating and grading to curriculum design and student motivation. Stanford’s Dan Schwartz argues AI is both a disruptive threat and a powerful tool: it can automate routine work, support project-based learning, and force educators to rethink what should actually be assessed—conceptual understanding, creativity, and decision-making rather than mere output.

Main Topics: AI as a disruptive but useful force in education (Priority: 5/5): Schwartz describes generative AI as a turning point that makes educators, students, and institutions confront what humans should do versus what machines can do, while also creating new opportunities for learning design. Cheating, assessment, and redesigning tests (Priority: 5/5): The conversation centers on whether students should use ChatGPT during tests and assignments, and how assessment must shift away from routine tasks toward conceptual, creative, and strategic thinking. Motivation and the protege effect (Priority: 4/5): Schwartz argues that well-designed computer interactions can motivate students, especially when they teach an agent or work toward an authentic goal, but gamification alone can distort learning. Edtech industry incentives and commercialization (Priority: 4/5): The discussion highlights how companies are building AI to improve efficiency and scale, sometimes optimizing for speed and automation rather than deeper learning outcomes or educational theory. Teacher agency and classroom adoption (Priority: 4/5): Teachers are not passive bystanders; many are already using GenAI, especially in K-12, and can deploy it to support project-based learning, planning, and monitoring student progress. Embodiment, physicality, and learning (Priority: 3/5): Schwartz emphasizes that learning is not only verbal or abstract; physical action, perception, and virtual/embodied experiences are crucial and present a major challenge for current AI systems.

Key Arguments: AI is forcing a redefinition of education because it can handle routine tasks, leaving humans to focus on creativity, judgment, and deeper understanding. Assessment should change: if AI can produce code or prose, educators need to test whether students understand the underlying concepts and can make good choices. Using ChatGPT in class is not automatically harmful; the key is designing assignments that reveal learning and make the tool part of the process rather than a shortcut. Students who are already motivated will likely use AI productively; disengaged students will find ways to slack off regardless of the technology. The edtech market is growing fast, but many products are built for efficiency and automation rather than evidence-based learning design. Teachers, especially in K-12, can use AI to support project-based learning, planning, and progress tracking in ways that were previously impractical. Learning is embodied: physical interaction, spatial reasoning, and virtual manipulation can produce deeper understanding than text-only interfaces.

Data Points: K-12 teachers using GenAI: about 60% - Schwartz cites survey averages from the last year, suggesting teacher adoption is already substantial in pre-K–12. K-12 students using GenAI: about 30% - Compared with teacher usage, student usage in K-12 is lower but still significant. College faculty using GenAI in teaching: about 30% - Schwartz contrasts faculty adoption at the university level with student behavior. College students using GenAI: about 80% - He notes students are using GenAI far more than faculty in higher education. Student grade difference with ChatGPT use: about 2 points out of 100 - Russ Altman describes a class where ChatGPT users scored slightly lower overall, but not dramatically so. Time saved by ChatGPT users: roughly half the time - In that same class, students using ChatGPT completed assignments much faster. Edtech unicorn valuation growth: $54 billion valuation companies last year - Schwartz notes a major rise in edtech company value compared with 20 years ago when there were essentially none. Class size in a former teaching example: 130 kids - Schwartz recalls managing many students in a high school setting, illustrating why AI support for project-based learning could matter.

Pivotal Quotes: "We want to be part of the future, not part of the past." — Russ Altman: Altman explains why he and a co-instructor allowed ChatGPT in an ethics writing class. "What's left for humans?" — Dan Schwartz: Schwartz describes the existential reaction people have when they first see how capable generative AI is. "The concern is the computer does all the work." — Dan Schwartz: He summarizes a core educational risk: tools can become crutches if they replace student thinking rather than extend it.

Implications: AI will likely become embedded in teaching and assessment, but schools must prioritize conceptual understanding, creativity, and embodied learning. The winners will be educators and tools that use AI to deepen learning rather than merely speed it up.