Using Affordance Analysis to Strategize the Integration of AI-Generated Instructor Avatars within MOOCs (Stage 2, 10:53 AM)

• In Event: e-Lightning Ed-Talk Session 2 - Stage 2

Abstract

Our study strategizes the use of video-based, AI-generated instructor avatars within MOOCs to enhance learning experiences and support educational goals. We adapted Bower’s affordance analysis framework to align proposed learning tasks with the technological affordances of AI-generated avatars, in support of three iteration goals of a MOOC series: inclusivity, learner motivation, and timely scaffolding. Our study highlights promising use cases and effective design strategies for the application of AI-generated instructor avatars in online contexts. By grounding our design plan and proof-of-concept videos in educational goals, technology affordances, and contextual factors, we offer a strategic, research-informed perspective to ongoing design and scholarly discourse surrounding the use of AI tools in technology-enhanced learning environments.

Authors

• Rebecca M. Quintana, University of Michigan

• Annie Zhou, University of Michigan