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Systematic review of research on artificial intelligence in K–12 education (2017–2022)
Open accessAbstract
The use of Artificial Intelligence (AI) has increased in all education sectors including K-12 settings where students can learn about AI and have an augmented learning experience using AI. The purpose of this systematic review is to provide a more complete and nuanced understanding of the role and impact of AI in K-12 education by synthesizing publication trends, AI research themes, AI methods and technology applications, and AI use by students and teachers in K-12 educational settings. The systematic review searched Web of Science and six databases indexed in EBSCO host. A PRISMA flow chart was applied to search and screen for studies. Articles were screened at the title, abstract and full-text level and coded and analyzed. Themes in 66 AI studies include AI as a predictor and indicator of academic behavior or performance, AI curriculum design, integrating AI in various subjects, evaluation of AI in education, AI to enhance learning environments and school operations, AI ethics, and the equity and safety of AI. AI methods were grouped into Supervised Learning, Unsupervised Learning and Reinforcement Learning. AI technology applications were Machine Learning (ML) model building tools, intelligent tutors, chat bot, educational games, AI robots and virtual reality devices. AI applications were mostly used by teachers for ML model demonstration, academic performance prediction and behavior prediction. AI was used by students for scientific discovery learning, improving learning experience and data driven decisions. This review has implications for K-12 school personnel and researchers. Practitioners can use the findings to implement AI in K-12 education. Researchers can benefit from the findings of the review but also build on the gap in research on AI K-12 education.
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“A separate stream of reviews surveys GenAI's administrative, technical, and outcome-focused uses in teaching [35-38].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [35]
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Cheng, J., Gao, Y., Liu, X., Barany, A., & Chen, B. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-12229-2_2
Personal Resources in AI-Assisted Translation
Pietrzak, P. (2025) · Research in Language · doi:10.18778/1731-7533.23.01
“Indeed, the integration of generative AI (GenAI) in translator education has gained popularity (e.g. Chiu et al. 2023, Martin et al. 2023, Sun et al. 2025) and some scholars advocate its inclusion, for example by incorporating AI-assisted translation exercises into teaching (Chen 2025, Jiang 2025).”
The Role of AI and Machine Translation in Students’ Translation Training
Kałużna, A. (2025) · Research in Language · doi:10.18778/1731-7533.23.07
“The topic of the use of AI in education has gained on popularity (Martin et al. 2023).”
Students, Learning, Classrooms and Schools
Reimers, F., Azim, Z., Palomo, M.-R., & Thony, C. (2025) · Springer eBooks · doi:10.1007/978-3-032-11449-5_3
Girard, M.-A., Roy, N., & Roméro, M. (2025) · Enjeux et société Approches transdisciplinaires · doi:10.7202/1122020ar · Cited by 1
A Multi-Agent Environment With Artificial Intelligence for English Language Learning and Teaching
Slyusar, V. I. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-3561-2.ch006
Maritasari, D. B., -, D. A., & Hudri, M. (2025) · Tadris Jurnal Keguruan dan Ilmu Tarbiyah · doi:10.24042/tadris.v10i1.28626 · Cited by 1
School Violence: A Systemic Analysis of Artificial Intelligence Detection
Barrios-Cogollo, C., Gómez, J. G., & De-La-Hoz-Franco, E. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-10731-2_15
Zhao, H., Dong, J., & Song, J. (2025) · International Conference on Artificial Intelligence and Future Education (AIFE) · doi:10.1145/3785987.3786030
“Furthermore, interaction theory underscores the significance of active involvement with both educational content and peers, a dynamic that can be effectively supported by intelligent agents through adaptive learning systems and real-time feedback mechanisms [5].”
AI-Driven Personalized Teaching Models in Higher Education Painting Courses
Cui, B. (2025) · International Conference on Artificial Intelligence and Future Education (AIFE) · doi:10.1145/3785987.3786088
İngilizce Öğretmenlerinin Dil Eğitimine Yapay Zekanın Dahil Edilmesine İlişkin Görüşleri
Karaoğlu, S. Ü., & Doğan, C. (2025) · DergiPark (Istanbul University)
Aldous, K. K., Salminen, J. O., Jung, S.-G., Azem, J. Y., Medina, J., Khan, S. M., Alabed, A., & Jansen, B. J. (2025) · International Conference on Foundation and Large Language Models (FLLM) · doi:10.1109/fllm67465.2025.11390874
“Multiple attempts to develop educational chatbots have been documented [6], [11], evolving from rule-based systems limited in handling complex queries [22]–[25] to more adaptive large language model (LLM)-based systems capable of natural dialogue and personalized interactions that adjust to…”
AI-Driven Innovations in Mathematics Education
Jita, T., Jita, L. C., & Omoniyi, A. A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0101-1.ch009 · Cited by 1
Teachers' Artificial Intelligence Practices, Benefits, and Challenges
Aravantinos, S., Lavidas, K., Papadakis, S., Karalis, T., & Komis, V. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0101-1.ch012
Yassin, A., Surjono, H. D., Ghufron, A., Upahi, J. E., & Fadli, R. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0101-1.ch002 · Cited by 1
AI-Powered Virtual Teachers and Their Role in Developing Critical Thinking Skills
Aksin, A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-2637-5.ch008
Metadata
- Authors
- Martin, F., Zhuang, M., & Schaefer, D.
- Affiliations
- North Carolina State University (US)
- University of North Carolina at Charlotte (US)
- Corresponding author
- Martin, Florence
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2024-06
- Volume
- 6
- Pages
- 100195
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4390154952
- Semantic Scholar
- b3e704df385ec074a58d6468ac60746cd16a2178
- Cited by
- 132
- References
- 90
- Citations by year
- 2026: 46 · 2025: 70 · 2024: 16
- FWCI
- 5.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Education › 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
- artificial intelligence in education, K-12 education, student performance prediction, student behavior prediction, AI curriculum design, intelligent tutoring systems, chatbots, game-based learning, AI robots, virtual reality in education, AI ethics, supervised learning, unsupervised learning, reinforcement learning, machine learning in education, teacher use of AI, student use of AI
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