Artificial Intelligence Applications in K-12 Teaching and Learning: An Umbrella Review (Poster 34)

• In Event: AERA Poster Session Sunday 1:30 p.m.
  In Poster Session: Artificial Intelligence in Education and Learning Technologies

Abstract

This umbrella review synthesizes 76 systematic reviews to examine the current state of artificial intelligence (AI) applications in K-12 learning and teaching. The study aims to describe the characteristics, summarize existing frameworks, categorize AI applications, and assess the quality of these reviews. The major contributions of this study are as follows: (a) We developed a framework to categorize AI applications reviewed in the literature; (b) We created a quality assessment rubric for umbrella reviews that is applicable across various fields; (c) We identified the need for improved clarity and thoroughness in data management, extraction processes, and analysis methods. Overall, this review provides insights for researchers, practitioners, and policymakers, highlighting trends and identifying areas for future research and development in AI-enhanced education.

Authors

• Ruiping Huang, University of Illinois at Chicago

• Yue Yin, University of illinois at Chicago

• Na Zhou, University of Illinois at Chicago

• Fei Lang, University of Illinois at Chicago

• Ying Chen, University of Illinois System

• Jeremy Riel, University of Illinois at Chicago