The Efficacy of Artificial Intelligence–Enabled Adaptive Learning From 2010 to 2020 on Learner Cognitive Outcomes: A Meta-Analysis

• In Event: Games, Artificial Intelligence, and Digital Environments for Cognition and Learning

Abstract

The purpose of the study is to provide a quantitative synthesis of research literature on adaptive learning with AI integrated from 2010 to 2020 and examine its effectiveness on students’ educational outcomes. Data were extracted from 18 academic databases applying our inclusion/exclusion criteria. Data were run in random-effects models along with moderator analyses. Results show that the overall effect size using a random-effects model is g = 0.70, which is a medium to large effect size. Additional analyses, discussion, limitations, and implications are provided in the full paper.

Authors

• Xiaoman Wang, University of Florida
  Presenting Author

• Rui Tammy Huang, University of Florida
  Presenting Author

• Max Sommer, University of Florida
  Presenting Author

• Poorya Shidfar, University of Florida
  Presenting Author

• Muhammad Rehman, University of Florida
  Presenting Author

• Albert Dieter Ritzhaupt, University of Florida
  Presenting Author

• Florence Martin, North Carolina State University
  Presenting Author