The impact of GenAI on learning outcomes: A systematic review and meta-analysis of experimental studies
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Experimental and quasi-experimental findings report moderate learning benefits from GenAI interventions, especially for behavioural engagement and self-regulation, but heterogeneity leaves expert-rated studio creativity insufficiently resolved.
“Experimental and quasi-experimental findings similarly report moderate learning benefits from GenAI interventions, especially for behavioural engagement and self-regulation, although heterogeneity across context, duration, and task type leaves expert-rated studio creativity insufficiently resolved (Han et al. 2025).”
From A Study on the Role of Midjourney, A Generative Artificial Intelligence Tool, in Enhancing Student Creativity in Illustration Design Classes (2026) · cites this paper as Han et al. 2025
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“For example, GenAI tools have been shown to enhance cognitive learning strategies more effectively than metacognitive ones, emphasizing the importance of behavioral engagement over mere literacy (Han et al., 2025).”
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“On the micro level, GenAI can be used for automating adaptive learning, e.g., through automated feedback and guidance (Han et al., 2025; Kes-tin et al., 2025; Wang & Fan, 2025).”
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“In a recent systematic review, Han et al. (2025) identified autonomous learning and motivation as the most obvious benefits of using GenAI tools based on 68 literature papers.”
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“A substantial proportion of empirical research has examined how learners interact with GenAI tools across different educational stages, subject domains, and learning tasks (Han et al., 2025).”
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“However, the application of such models to support the operational use of real measurement instruments has received limited attention, particularly with respect to systematic performance evaluation in hands-on laboratory settings [12].”
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Wu, M., & Ouyang, F. (2026) · Educational Psychology Review · doi:10.1007/s10648-026-10211-x
“Syntheses of GenAI in education generally report a single achievement outcome without separating what students produced with the tool from what they produced without it (Han et al., 2025 ).”
He, S. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70305
Xie, Y., Chen, W., & Qiu, Y. (2025) · Communications in computer and information science · doi:10.1007/978-981-95-4499-8_18
Barillas, R. B., de Leon, M., Fraundorf, S. H., Brusilovsky, P. L., de Alencar, R. S., Nixon‐Cave, K., & Wang, Y. (2026) · American Journal of Distance Education · doi:10.1080/08923647.2026.2669412
Huesca, G., Martínez-Treviño, Y., González, C. G. J., Delgado, D. A. C., Navarrete, C., Cedillo-Hernández, A., & Meza, R. R. Q. (2026) · AI · doi:10.3390/ai7070248
“Furthermore, recent prospective analyses identify the evaluation of GenAI’s impact on learning outcomes as one of the major challenges for future educational research [13].”
Davis, M., Chow, C. M., & Divekar, R. R. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30781-1_22
Pi, Z., Cao, Y., Zhang, Y., Ma, Y., Cao, W., & Li, X. (2026) · Computers & Education · doi:10.1016/j.compedu.2026.105722
Liu, J., Sun, M., Liu, C., & Yang, H. (2026) · The Electronic Library · doi:10.1108/el-12-2025-0489
Zhuang, X., Liu, B., Yiting, S., Li, S., & Liu, B. (2026) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste69562.2026.11649684
“Overall, GAI exerts positive influence across these dimensions, supporting the shift from “tool assistance” to “intelligent collaboration” and becoming an important driver for improving learning quality and transforming learning approaches [15].”
Examining student perceptions of custom GPT Chatbots to support introductory physics instruction
Young, N. T., Freeman, J., Balasubramaniam, S., & Weliweriya, N. (2026) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--59642
Long-term impact of ChatGPT-4 on music students' creative and analytical skills: A follow-up study
Zhou, W., & Kim, Y. (2026) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2026.102344
Evaluation of ChatGPT Study Mode: Results from an Expert Rating Regarding Self-Regulated Learning
Steinberg, E., Perels, F., Aubreville, M., & Dörrenbächer‐Ulrich, L. (2026) · Open Education Studies · doi:10.1515/edu-2025-0169
“Although hallucinations or incorrect content and over-reliance are frequently reported issues in the literature (e.g., Han et al. 2025), these issues did not emerge as notable concerns among the participants in this study.”
InfluentialShi, Y., Zheng, Y., Wei, Y., Ji, X., & Ke, Z. (2026) · Creativity Research Journal · doi:10.1080/10400419.2026.2726242
GenAI in K-12 Literacy Education: Advancing the Conversation
Oakley, G. (2026) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80686-243-620261001
Wang, N. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1892204
“First, a meta-analysis (Han et al., 2025) that combined 68 experimental studies and 337 effect sizes found that, although the effect of generative AI on learning engagement was generally positive, there was significant heterogeneity, suggesting that its effectiveness highly depends on conditional…”
Learning-Science Grounded Design for Generative Artificial Intelligence in Education
Lin, J., & Hu, X. (2026) · Springer eBooks · doi:10.1007/978-3-032-24819-0_7
Kővári, A. (2026) · Computers · doi:10.3390/computers15090633 · Cited by 2 · see citing works
Fang, L., Li, Z., Xiong, B., & Lu, Z. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1832451
The Impact of AI Usage for Accounting Students Learning Experience
Rae, G., kalyana, R. S. B., Rusli, A. J., & Angelus, M. (2026) · Procedia Computer Science · doi:10.1016/j.procs.2026.08.268
Cevallos, C. A. H., Valencia, K., Vivar, J. A. M., Gallegos, L. A. C., & Alcívar, I. J. C. (2026) · Ciencia Interdisciplinaria Internacional · doi:10.70577/cieninter.v4i3.138
Su, K.-D. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2735911
Queiroz, C. C. D. S. F., Vicente, A. B., DIÓGENES, A. N., SILVA, P. L. D., Ximenes, K. C., Sousa, F. M. C., Pereira, D. D. C., & Leite, G. R. (2026) · Revista Saúde dos Vales · doi:10.66104/wkqxm368
Raju, G. M., Balart, T., & Shryock, K. J. (2026) · Education Sciences · doi:10.3390/educsci16101635
“Recent empirical work suggests that GenAI adoption in higher education is unfolding across at least three interconnected levels: student learning, institutional policy, and faculty practice (Han et al., 2025).”
Xiaotian, R., Li, X., Gao, L., Wei, Q., Liu, H., & Yu, X. (2026) · Educational Psychology Review · doi:10.1007/s10648-026-10217-5
“However, much of the evidence relies on quasi-experimental designs vulnerable to baseline differences and selection bias, limiting causal inference (Han et al., 2025 ; Nie et al., 2025; Tian & Zheng, 2025).”
Open Educational Resources and Generative AI: Towards a Framework for Responsible Integration
Rodés, V., & Atenas, J. (2026) · Open Praxis · doi:10.55982/openpraxis.18.4.1267
“In pedagogical interaction, intelligent tutoring systems, chatbots, virtual assistants, adaptive textbooks, and AI-generated pedagogical agents create new forms of feedback, dialogue, and sequencing (Han et al., 2025; Li et al., 2023; Nazaretsky et al., 2022).”
Al-Harthi, M. (2026) · Academic Journal of Research and Scientific Publishing · doi:10.52132/ajrsp.e.2026.90.3
Technology-Supported Interventions and Learners’ Metacognition: A Three-Level Meta-Analysis
Yuan, Y., & Du, Y. (2026) · Educational Psychology Review · doi:10.1007/s10648-026-10227-3
“Meta-analytic work has also examined the broader learning effects of generative AI (Han et al., 2025 ).”
Zhang, Y. (2026) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-032-42320-7_15
Guo, W., & Ren, X. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1986129
Khodjaev, B. K., Masalimova, A. R., Chistyakov, A. A., & Ay, Y. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1971476
Artificial intelligence: Reshaping medical education and the healthcare system
Meo, S. A. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-45973-3.00003-8
Kollaborative Prozesse zur Einbindung von KI in der Primarstufe
Wichers, A., Hesse, F., & Helm, G. (2026) · MedienPädagogik Zeitschrift für Theorie und Praxis der Medienbildung · doi:10.21240/mpaed/73/2026.10.24.x
“Bisweilen scheint damit sogar die Erwar-tung verknüpft, dass nur solche Tools vorgestellt werden, die bereits erwiesenermassen sinnvoll sind, ‹Werbung› statt gemeinsamer Reflexion, obwohl das Projekt gerade dafür da ist, die Funktionalität der Tools zu erproben, auch weil Forschungsergebnisse noch fehlen (siehe 1.).”
InfluentialDigital Technology Utilization at Lataban National High School: Digitization Model
Gungob, G. C. (2026) · International Journal of Global Goals and Sustainable Development · doi:10.65339/ijggsd.v1.i1.8
- Authors
- Han, X., Peng, H., & Liu, M.
- Affiliations
- East China Normal University (CN)
- Corresponding author
- Peng, Hongchao
- Liu, Mingzhuo
- Venue
- Educational Research Review
- Publisher
- Elsevier BV
- Published
- 2025-08
- Volume
- 48
- Pages
- 100714
- ISSN
- 1747-938X (ISSN-L)
- OpenAlex
- W4413003408
- Cited by
- 70
- References
- 95
- Citations by year
- 2026: 64 · 2025: 6
- FWCI
- 6.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Educational Research Review (publishedVersion)
- Funders
- Ministry of Education of the People's Republic of China
- Humanities and Social Science Fund of Ministry of Education of the People's Republic of China (24YJC880105)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, ChatGPT, learning outcomes, artificial intelligence in education, K-12 education, science education, brief intervention, effect size heterogeneity, moderator analysis
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