Content area

Abstract

Artificial intelligence (AI) methods have been integrated in education during the last few decades. Interest in this integration has increased in recent years due to the popularity of AI. The use of explainable AI in educational settings is becoming a research trend. Explainable AI provides insight into the decisions made by AI, increases trust in AI, and enhances the effectiveness of the AI-supported processes. In this context, there is an increasing interest in the integration of AI, and specifically explainable AI, in the education of young children. This paper reviews research regarding explainable AI approaches in primary education in the context of teaching and learning. An exhaustive search using Google Scholar and Scopus was carried out to retrieve relevant work. After the application of exclusion criteria, twenty-three papers were included in the final list of reviewed papers. A categorization scheme for explainable AI approaches in primary education is outlined here. The main trends, tools, and findings in the reviewed papers are analyzed. To the best of the authors’ knowledge, there is no other published review on this topic.

Details

1009240
Business indexing term
Title
Explainable Artificial Intelligence Approaches in Primary Education: A Review
Publication title
Volume
14
Issue
11
First page
2279
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
20799292
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-06-03
Milestone dates
2025-05-02 (Received); 2025-06-01 (Accepted)
Publication history
 
 
   First posting date
03 Jun 2025
ProQuest document ID
3217726058
Document URL
https://www.proquest.com/scholarly-journals/explainable-artificial-intelligence-approaches/docview/3217726058/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-10
Database
2 databases
  • Coronavirus Research Database
  • ProQuest One Academic