Presenting an Optimal Educational Model: A Meta-Analysis of International Research on the Application of Artificial Intelligence in Education

Articles in Press

Document Type : Research Paper

Authors

1 Assistant Professor,Department of Psychology and Counselling, Farhangian University, P.O. Box 14665-889, Tehran

2 M.SC.Education psychology, Department of Psychology and Counseling, Nasiba Campus, Farhangian University, Tehran, Iran.

3 Assistant Professor,Department of Psychology and Counselling, Farhangian University, P.O. Box 14665-889, Tehran.

10.48310/edu.2026.20168.1569

Abstract

Background and Objectives: This research was conducted with the aim of performing a meta-analysis of studies related to the application of artificial intelligence in education, in order to present an optimal educational model.
Methods:This study was based on a meta-analysis framework. Persian-language articles from 1397 to 1403 and English-language articles from 2018 to 2024 that matched the research criteria were selected as samples.
Findings: In the first part of the study, 4 studies (11.4%) had small effect sizes, 17 (48.6%) had moderate effect sizes, and 14 (40%) had large effect sizes. The overall effect size was 0.53.Evaluation and adjustment of publication bias using the Duval and Tweedie test and meta-analysis showed that the observed and adjusted value in the fixed-effect model was 0.6154, and in the random-effects model, was 0.6196.In the second part of the study, seven criteria were identified , based on 35 indicators.In addition, five criteria were identified as the barriers and challenges of applying AI in education, based on 24 indicators.
Conclusion:Therefore, it can be concluded that AI programs require a general and specific model structure based on a comprehensive, codified, and multi-layered plan in which all components are aligned with this model and its condition

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Journal of Pouyesh in Education and Consultation (JPEC)

Articles in Press, Accepted Manuscript
Available Online from 15 April 2026

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History

  • Receive Date: 19 July 2025
  • Revise Date: 28 November 2025
  • Accept Date: 08 February 2026

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