Reexamining the Effect of Artificial Intelligence in Relation to Students’ Academic Achievement: A Meta-Analysis

• In Event: The Feasibility and Effectiveness of AI in Learning and Assessment

Abstract

The purpose of this meta-analysis study was to examine the overall effect of the Artificial Intelligence (AI) on students’ academic achievement in relation to a set of moderating variables including education level, types of AI, intervention duration, learning strategies, achievement measurement and so on. A total of 5,670 studies published between 2014 and 2024 from seven databases were screened, and finally 27 empirical studies met the inclusion criteria and were subsequently coded, calculated, and analyzed. Overall, we found a significant positive effect, with the weighted average effect size as 0.784. This study validates the efficacy of AI and provides a critical foundation for future research to identify and leverage specific conditions under which AI can most effectively enhance student learning.

Authors

• Liu Dong, Purdue University

• Xiyu Wang, Purdue University

• Xiuxiu Tang, University of Notre Dame

• Victoria Lynn Lowell, Purdue University