Scaling Evidence-Based Instructional Design with AI: Insights from Carnegie Mellon University

Ivancast Podcast

In this episode, we dive into the paper “Scaling Evidence-Based Instructional Design Expertise through Large Language Models” by Gautam Yadav from Carnegie Mellon University. This research explores how AI, particularly GPT-4, can transform instructional design by bridging the gap between educational theory and real-world application. Through two detailed case studies, we examine AI-driven content creation, active learning strategies, and the integration of LLMs into assessment and instructional workflows.

📢 This episode is part of our ongoing season, where SHIFTERLABS leverages Google LM to demystify cutting-edge research, translating complex insights into actionable knowledge. Join us as we explore the future of education in an AI-integrated world.

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