A Bibliometric Analysis of Trends and Issues in Educational Artificial Intelligence (Poster 1)

• In Event: Instructional Technology SIG Poster Session 1

Abstract

This study examined the trends and issues in Artificial Intelligence (AI) in education. A bibliometric approach was used that focused on the publications disseminated in years 2013-2021. Our analysis revealed that existing research on AI in education emphasizes three key aspects: a) systems that provide adaptive and personalized learning (intelligent tutoring systems and MOOCs), b) methods that operationalize AI in education (e.g., machine learning, student modeling), and c) cognitive, affective, and metacognitive outcomes of AI-assisted learning. Within a field so dynamic and evolving as AI, having a clear picture of what has been researched will assist in guiding the way for addressing future AI research needs in a meaningful way that advances both research and practice of education.

Authors

• Brian Abramowitz, University of Florida

• Minyoung Lee, University of Florida

• Pasha Antonenko, University of Florida