Effects of Generative Artificial Intelligence on K-12 and Higher Education Students' Learning Outcomes: A Meta-Analysis

Autor/inn/en	Xiaohong Liu; Baoxin Guo; Wei He; Xiaoyong Hu
Titel	Effects of Generative Artificial Intelligence on K-12 and Higher Education Students' Learning Outcomes: A Meta-Analysis
Quelle	In: Journal of Educational Computing Research, 63 (2025) 5, S. 1249-1291Infoseite zur Zeitschrift PDF als Volltext Link als defekt meldenVerfügbarkeit
Zusatzinformation	ORCID (Xiaohong Liu)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0735-6331
DOI	10.1177/07356331251329185
Schlagwörter	Artificial Intelligence; Man Machine Systems; Natural Language Processing; Technology Uses in Education; Elementary School Students; Secondary School Students; College Students; Outcomes of Education; Academic Achievement; Student Motivation; Educational Research; Age Differences + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Mensch-Maschine-System; Natürliche Sprache; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Sekundarschüler; Collegestudent; Lernleistung; Schulerfolg; Schulleistung; Schulische Motivation; Bildungsforschung; Pädagogische Forschung; Age; Difference; Age difference; Altersunterschied
Abstract	Generative artificial intelligence (GenAI) has significant potential for educational innovation, although its impact on students' learning outcomes remains controversial. This study aimed to examine the impact of GenAI on the learning outcomes of K-12 and higher education students, and explore the moderating factors influencing this impact. A meta-analysis of 49 articles showed that the mean effect sizes of GenAI on students' learning achievement and learning motivation were 0.857 and 0.803, respectively, indicating a positive impact of GenAI on education. However, this effect varied according to moderators, including education level, subject classification, GenAI interface, GenAI development, interaction approaches, and experimentation time, which enhanced the impact of GenAI on education. Specifically, GenAI had a greater impact on the academic performance of higher education students, and students interacted more effectively with GenAI using text than with mixed media, such as images or audio. Although GenAI has a novel effect on students' learning motivation, the effect size decreases over time. These findings provide empirical support for the beneficial effects of GenAI on education and offer insights for optimizing its use in teaching practices. (As Provided).
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Begutachtung	Peer reviewed
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2025/3/08