A Systematic Review of AI-Driven Intelligent Tutoring Systems (ITS) in K-12 Education

Saved in:
Bibliographic Details
Title: A Systematic Review of AI-Driven Intelligent Tutoring Systems (ITS) in K-12 Education
Language: English
Authors: Angélique Létourneau, Marion Deslandes Martineau (ORCID 0000-0001-6041-6604), Patrick Charland, John Alexander Karran (ORCID 0000-0002-5821-9561), Jared Boasen, Pierre Majorique Léger
Source: npj Science of Learning. 2025 10.
Availability: Nature Portfolio. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://www.nature.com/npjscilearn/
Peer Reviewed: Y
Page Count: 13
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Education Level: Elementary Secondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Intelligent Tutoring Systems, Elementary Secondary Education, Outcomes of Education, Learning Processes, Academic Achievement
DOI: 10.1038/s41539-025-00320-7
ISSN: 2056-7936
Abstract: The use of artificial intelligence in education (AIEd) has grown exponentially in the last decade, particularly intelligent tutoring systems (ITSs). Despite the increased use of ITSs and their promise to improve learning, their real educational value remains unclear. This systematic review aims to identify the effects of ITSs on K-12 students' learning and performance and which experimental designs are currently used to evaluate them. The 28 studies analyzed in this systematic review included a total of 4597 students (N = 4597) and used quasi-experimental designs with varying intervention durations. Overall, our findings suggest that the effects of ITSs on learning and performance in K-12 education are generally positive but are found to be mitigated when compared to non-intelligent tutoring systems. However, additional research with longer interventions and increased sample sizes with greater diversity is warranted. Additionally, the ethical implications of using AI for teaching should be investigated.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1471111
Database: ERIC
Be the first to leave a comment!
You must be logged in first