Demographic Factors and Equity in AI-Supported Learning: A Mixed-Methods Study of Chatbot Use in MOOCs

• In Event: AERA Roundtable Session Thursday 7:45 am - Gold 4
  In Roundtable Session: Designing Inclusive and Human-Centered Technology for Learning

Abstract

This study examines how demographic factors influence equitable learning experiences with an AI-driven tool in massive open online courses (MOOCs). While chatbot use in online learning is growing, little is known about how socioeconomic and geo-cultural factors shape student perceptions and use. Using statistical and qualitative analyses, we found that age and gender had no significant impact, but regional differences affected students’ learning experiences with a chatbot. Self-regulation predicted all learning domains, though behavioral intention did not translate to actual use. Students from lower-income regions generally reported positive experiences, while students from higher-income regions expected more sophisticated interactions and expertise. Guided by the Community of Inquiry framework and Expectation Confirmation Model, this study highlights the need for adaptive chatbot design.

Authors

• Songhee Han, Florida State University

• Min Liu, University of Texas at Austin