AI Agents in Education: Scaling Simulated Practice for the Future of Learning

In this episode of our special season, SHIFTERLABS leverages Google LM to demystify cutting-edge research, translating complex insights into actionable knowledge. Today, we explore “AI Agents and Education: Simulated Practice at Scale”, a groundbreaking study by Ethan Mollick, Lilach Mollick, Natalie Bach, LJ Ciccarelli, Ben Przystanski, and Daniel Ravipinto from the Generative AI Lab at the Wharton School, University of Pennsylvania.

 

The study introduces a powerful new approach to AI-driven educational simulations, showcasing how generative AI can create adaptive, scalable learning environments. Through AI-powered mentors, role-playing agents, and instructor-facing evaluators, simulations can now provide personalized, interactive practice opportunities—without the traditional barriers of cost and complexity.

 

A key case study in the research is PitchQuest, an AI-driven venture capital pitching simulator that allows students to hone their pitching skills with virtual investors, mentors, and evaluators. But the implications go far beyond entrepreneurship—AI agents can revolutionize skill-building across fields like healthcare, law, and management training.

 

Yet, AI-driven simulations also come with challenges: bias, hallucinations, and difficulties maintaining narrative consistency. Can AI truly replace human-guided training? How can educators integrate these tools responsibly? Join us as we break down this research and discuss how generative AI is transforming the future of education.

 

🔍 This episode is part of our mission to make AI research accessible, bridging the gap between innovation and education in an AI-integrated world.

 

🎧 Tune in now and stay ahead of the curve with SHIFTERLABS.