Examining the use of artificial intelligence in pre-service teacher education

Elena B. Ponomarenko; Olga V. Sergeeva; Marina R. Zheltukhina; Kseniia M. Baranova; Roza L. Budkevich; Mariya V. Melnik

doi:10.30935/cedtech/18458

Elena B. Ponomarenko ¹, Olga V. Sergeeva ², Marina R. Zheltukhina ³ ^* , Kseniia M. Baranova ⁴, Roza L. Budkevich ⁵, Mariya V. Melnik ⁶

More Detail

CONT ED TECHNOLOGY, Volume 18, Issue 2, Article No: ep650

https://doi.org/10.30935/cedtech/18458

Submitted: 08 February 2026, Published Online: 23 April 2026

OPEN ACCESS 39 Views 19 Downloads

Download Full Text (PDF)

Abstract

This systematic review investigates the current state of artificial intelligence (AI) integration in pre-service teacher (PST) education, with an emphasis on PSTs’ perspectives, attitudes, knowledge levels, and AI-related educational experiences. The review intends to uncover the characteristics that influence PSTs’ intents to employ AI technology, as well as the success of AI training programs. A thorough search of academic databases turned up 33 research published between 2021 and 2024, which were examined using a theme framework. The findings show that PSTs have both positive and negative attitudes about AI integration, with initial AI knowledge and skills being restricted but improving with targeted training and hands-on experiences. Perceived utility, ease of use, social impact, and self-efficacy have all been proven to influence PSTs’ propensity to employ AI. The review also emphasizes PSTs’ favorable experiences using AI-based instruction, such as lesson planning, collaborative learning, and feedback/evaluation. However, issues and ethical concerns regarding data privacy, academic honesty, fairness, and the possible harmful impact on student learning were highlighted. The review recommends that teacher education institutes prioritize AI literacy development, address PSTs’ concerns, and incorporate ethical considerations into AI courses. The findings add to the expanding body of literature on AI integration in education, providing useful insights for defining teacher education practice and policy in the AI era.

Keywords: artificial intelligence, pre-service teachers, AI literacy, perceptions, attitudes

References

Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligence, 4, Article 100131. https://doi.org/10.1016/j.caeai.2023.100131
Adelana, O. P., Ayanwale, M. A., & Sanusi, I. T. (2024). Exploring pre-service biology teachers’ intention to teach genetics using an AI intelligent tutoring-based system. Cogent Education, 11(1), Article 2310976. https://doi.org/10.1080/2331186X.2024.2310976
Adhikari, C., Das, P. K., & Biswas, S. D. (2025). AI in higher education: An analysis of ChatGPT’s impact on scholarly communication. Educational Point, 2(2), Article e137. https://doi.org/10.71176/edup/17641
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431-440. https://doi.org/10.1007/s43681-021-00096-7
Alier, M., García-Peñalvo, F. J., & Camba, J. D. (2024). Generative artificial intelligence in education: From deceptive to disruptive. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 5-14. https://doi.org/10.9781/ijimai.2024.02.011
AlKanaan, H. M. N. (2022). Awareness regarding the implication of artificial intelligence in science education among pre-service science teachers. International Journal of Instruction, 15(3), 895-912. https://doi.org/10.29333/iji.2022.15348a
Almufareh, M. F., Kausar, S., Humayun, M., & Tehsin, S. (2024). A conceptual model for inclusive technology: Advancing disability inclusion through artificial intelligence. Journal of Disability Research, 3(1). https://doi.org/10.57197/jdr-2023-0060
Alrishan, A. M. H. (2023). Determinants of intention to use ChatGPT for professional development among Omani EFL pre-service teachers. International Journal of Learning, Teaching and Educational Research, 22(12), 187-209. https://doi.org/10.26803/ijlter.22.12.10
Antonenko, P., & Abramowitz, B. (2023). In-service teachers’ (mis)conceptions of artificial intelligence in K-12 science education. Journal of Research on Technology in Education, 55(1), 64-78. https://doi.org/10.1080/15391523.2022.2119450
Ayanwale, M. A., Adelana, O. P., Molefi, R. R., Adeeko, O., & Ishola, A. M. (2024a). Examining artificial intelligence literacy among pre-service teachers for future classrooms. Computers and Education Open, 6, Article 100179. https://doi.org/10.1016/j.caeo.2024.100179
Ayanwale, M. A., Frimpong, E. K., Opesemowo, O. A. G., & Sanusi, I. T. (2024b). Exploring factors that support pre-service teachers’ engagement in learning artificial intelligence. Journal for STEM Education Research, 8, 199-229. https://doi.org/10.1007/s41979-024-00121-4
Betaubun, M., Eva, D., Rokhmah, L., & Budiasto, J. (2023). Personalized pathways to proficiency: Exploring the synergy of adaptive learning and artificial intelligence in English language learning. Technium: Romanian Journal of Applied Sciences and Technology, 17(1), 60-66. https://doi.org/10.47577/technium.v17i.10047
Biagini, G. (2024). Assessing the assessments: Toward a multidimensional approach to AI literacy. Media Education, 15(1), 91-101. https://doi.org/10.36253/me-15831
Boscardin, C. K., Gin, B., Golde, P. B., & Hauer, K. E. (2024). ChatGPT and generative artificial intelligence for medical education: Potential impact and opportunity. Academic Medicine, 99(1), 22-27. https://doi.org/10.1097/ACM.0000000000005439
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Çayir, A. (2023). A literature review on the effect of artificial intelligence on education. Journal of Human and Social Sciences, 6(2), 276-288. https://doi.org/10.53048/johass.1375684
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510
Chichekian, T., & Benteux, B. (2022). The potential of learning with (and not from) artificial intelligence in education. Frontiers in Artificial Intelligence, 5, Article 903051. https://doi.org/10.3389/frai.2022.903051
Ciampa, K., Wolfe, Z. M., & Bronstein, B. (2023). ChatGPT in education: Transforming digital literacy practices. Journal of Adolescent and Adult Literacy, 67(3), 186-195. https://doi.org/10.1002/jaal.1310
Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Aldraiweesh, A., Alturki, U., Almutairy, S., Shutaleva, A., & Soomro, R. B. (2024). Extended TAM based acceptance of AI-powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study. Heliyon, 10(8), Article e29317. https://doi.org/10.1016/j.heliyon.2024.e29317
Dai, Y., Lai, S., Lim, C. P., & Liu, A. (2023). ChatGPT and its impact on research supervision: Insights from Australian postgraduate research students. Australasian Journal of Educational Technology, 39(4), 74-88. https://doi.org/10.14742/ajet.8843
Eden, C. A., Chisom, O. N., & Adeniyi, I. S. (2024). Integrating AI in education: Opportunities, challenges, and ethical considerations. Magna Scientia Advanced Research and Reviews, 10(2), 6-13. https://doi.org/10.30574/msarr.2024.10.2.0039
Gatlin, M. (2023). Assessing pre-service teachers’ attitudes and perceptions of using artificial intelligence in the classroom. Texas Educator Preparation, 7(2), 1-8. https://doi.org/10.59719/txep.v7i2.35
Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), Article 692. https://doi.org/10.3390/educsci13070692
Gutiérrez, L. (2023). Artificial intelligence in language education: Navigating the potential and challenges of chatbots and NLP. Research Studies in English Language Teaching and Learning, 1(3), 180-191. https://doi.org/10.62583/rseltl.v1i3.44
Hamal, O., El Faddouli, N.-E., Alaoui Harouni, M. H., & Lu, J. (2022). Artificial intelligent in education. Sustainability, 14(5), Article 2862. https://doi.org/10.3390/su14052862
Hastomo, T., Mandasari, B., & Widiati, U. (2024). Scrutinizing Indonesian pre-service teachers’ technological knowledge in utilizing AI-powered tools. Journal of Education and Learning, 18(4), 1572-1581. https://doi.org/10.11591/edulearn.v18i4.21644
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504-526. https://doi.org/10.1007/s40593-021-00239-1
Hur, J. W. (2025). Fostering AI literacy: Overcoming concerns and nurturing confidence among preservice teachers. Information and Learning Science, 126(1-2), 56-74. https://doi.org/10.1108/ILS-11-2023-0170
Jenßen, L., Gierlinger, F., & Eilerts, K. (2021). Pre-service teachers’ enjoyment and ICT teaching self-efficacy in mathematics–An application of control-value theory. Journal of Digital Learning in Teacher Education, 37(3), 183-195. https://doi.org/10.1080/21532974.2021.1929585
Kaplan-Rakowski, R., Grotewold, K., Hartwick, P., & Papin, K. (2023). Generative AI and teachers’ perspectives on its implementation in education. Journal of Interactive Learning Research, 34(2), 313-338. https://doi.org/10.70725/815246mfssgp
Karahan, E. (2023). Using video-elicitation focus group interviews to explore pre-service science teachers’ views and reasoning on artificial intelligence. International Journal of Science Education, 45(15), 1283-1302. https://doi.org/10.1080/09500693.2023.2200887
Kartal, G. (2024). The influence of ChatGPT on thinking skills and creativity of EFL student teachers: A narrative inquiry. Journal of Education for Teaching, 50(4), 627-642. https://doi.org/10.1080/02607476.2024.2326502
Kim, S.-W. (2024). Development of a TPACK educational program to enhance pre-service teachers’ teaching expertise in artificial intelligence convergence education. International Journal on Advanced Science, Engineering and Information Technology, 14(1), 1-9. https://doi.org/10.18517/ijaseit.14.1.19552
Kitcharoen, P., Howimanporn, S., & Chookaew, S. (2024). Enhancing teachers’ AI competencies through artificial intelligence of things professional development training. International Journal of Interactive Mobile Technologies, 18(2), 4-15. https://doi.org/10.3991/ijim.v18i02.46613
Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M. D., Păun, D., & Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability, 13(18), Article 10424. https://doi.org/10.3390/su131810424
Kuzu, S. (2025). Artificial intelligence in pre-service teacher education: Bibliometrics analysis. Pedagogical Research, 10(4), Article em0249. https://doi.org/10.29333/pr/17402
Lee, D., & Yeo, S. (2022). Developing an AI-based chatbot for practicing responsive teaching in mathematics. Computers and Education, 191, Article 104646. https://doi.org/10.1016/j.compedu.2022.104646
Lee, G. G., & Zhai, X. (2024). Using ChatGPT for science learning: A study on pre-service teachers’ lesson planning. IEEE Transactions on Learning Technologies, 17, 1683-1700. https://doi.org/10.1109/TLT.2024.3401457
Lee, G. G., Mun, S., Shin, M. K., & Zhai, X. (2024a). Collaborative learning with artificial intelligence speakers: Pre-service elementary science teachers’ responses to the prototype. Science and Education, 34, 847-875. https://doi.org/10.1007/s11191-024-00526-y
Lee, S., Jeon, J., & Choe, H. (2024b). Enhancing pre-service teachers’ global Englishes awareness with technology: A focus on AI chatbots in 3D metaverse environments. TESOL Quarterly, 59(1), 49-74. https://doi.org/10.1002/tesq.3300
Lee, Y. J., Davis, R. O., & Ryu, J. (2024c). Korean in-service teachers’ perceptions of implementing artificial intelligence (AI) education for teaching in schools and their AI teacher training programs. International Journal of Information and Education Technology, 14(2), 214-219. https://doi.org/10.18178/ijiet.2024.14.2.2042
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Journal of Clinical Epidemiology, 62(10), e1-e34. https://doi.org/10.1016/j.jclinepi.2009.06.006
Lim, E. M. (2023). The effects of pre-service early childhood teachers’ digital literacy and self-efficacy on their perception of AI education for young children. Education and Information Technologies, 28(10), 12969-12995. https://doi.org/10.1007/s10639-023-11724-6
Lim, E. M. (2024). Metaphor analysis on pre-service early childhood teachers’ conception of AI (artificial intelligence) education for young children. Thinking Skills and Creativity, 51, Article 101455. https://doi.org/10.1016/j.tsc.2023.101455
Lozano, A., & Blanco Fontao, C. (2023). Is the education system prepared for the irruption of artificial intelligence? A study on the perceptions of students of primary education degree from a dual perspective: Current pupils and future teachers. Education Sciences, 13(7), Article 733. https://doi.org/10.3390/educsci13070733
Ma, S., & Lei, L. (2024). The factors influencing teacher education students’ willingness to adopt artificial intelligence technology for information-based teaching. Asia Pacific Journal of Education, 44(1), 94-111. https://doi.org/10.1080/02188791.2024.2305155
Markos, A., Prentzas, J., & Sidiropoulou, M. (2024). Pre-service teachers’ assessment of ChatGPT’s utility in higher education: SWOT and content analysis. Electronics, 13(10), Article 1985. https://doi.org/10.3390/electronics13101985
Martono, Arifah Drajati, N., Rochsantiningsih, D., & Agung Wijaya, S. (2023). Intertextuality in pre-service teachers’ argumentative essay in raising AI: Practices and beliefs. Register Journal, 16(2), 186-206. https://doi.org/10.18326/register.v16i2.186-205
Miles, M. B. (2014). Qualitative data analysis: A methods sourcebook. SAGE.
Mnguni, L. (2025). A qualitative analysis of South African pre-service life sciences teachers’ behavioral intentions for integrating AI in teaching. Journal for STEM Education Research, 8, 230-256. https://doi.org/10.1007/s41979-024-00128-x
Mohamed, A. M. (2023). Exploring the potential of an AI-based chatbot (ChatGPT) in enhancing English as a foreign language (EFL) teaching: Perceptions of EFL faculty members. Education and Information Technologies, 29, 3195-3217. https://doi.org/10.1007/s10639-023-11917-z
Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4, Article 1. https://doi.org/10.1186/2046-4053-4-1
Mpolomoka, D. L. (2025). Utilizing artificial intelligence for assessment in higher education. Pedagogical Research, 10(2), Article em0236. https://doi.org/10.29333/pr/16677
Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers’ trust in AI-powered educational technology and a professional development program to improve it. British Journal of Educational Technology, 53(4), 914-931. https://doi.org/10.1111/bjet.13232
Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137-161. https://doi.org/10.1007/s11423-023-10203-6
Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221-4241. https://doi.org/10.1007/s10639-022-11316-w
Nyaaba, M., Kyeremeh, P., Joseph’, S., Majialuwe, E. K., Owusu-Fordjour, C., Asebiga, E., & Vincent, S. (2024). Generative AI in academic research: A descriptive study on awareness, gender usage, and views among pre-service teachers. Research Square. https://doi.org/10.21203/rs.3.rs-3640721/v2
Ocaña-Fernández, Y., Valenzuela-Fernández, L. A., & Garro-Aburto, L. L. (2019). Artificial Intelligence and its Implications in higher education. Propósitos y Representaciones, 7(2), 536-568. https://doi.org/10.20511/pyr2019.v7n2.274
Okulu, H. Z., & Muslu, N. (2024). Designing a course for pre-service science teachers using ChatGPT: What ChatGPT brings to the table. Interactive Learning Environments, 32(10), 7450-7467. https://doi.org/10.1080/10494820.2024.2322462
Pardamean, B., Suparyanto, T., Cenggoro, T. W., Sudigyo, D., & Anugrahana, A. (2022). AI-based Learning style prediction in online learning for primary education. IEEE Access, 10, 35725-35735. https://doi.org/10.1109/ACCESS.2022.3160177
Pokrivcakova, S. (2023). Pre-service teachers’ attitudes towards artificial intelligence and its integration into EFL teaching and learning. Journal of Language and Cultural Education, 11(3), 100-114. https://doi.org/10.2478/jolace-2023-0031
Pu, S., Ahmad, N. A., Khambari, M. N. M., Yap, N. K., & Ahrari, S. (2021). Improvement of pre-service teachers’ practical knowledge and motivation about artificial intelligence through a service learning-based module in Guizhou, China: A quasi experimental study. Asian Journal of University Education, 17(3), 203-219. https://eric.ed.gov/?id=EJ1309432
Pum, M. (2025). The paradox of augmentation and erosion: Navigating utility, critical agency, and trust deficit in AI writing tools among Cambodian English major undergraduates. Interdisciplinary Educational Technology, 1(1), Article e105. https://doi.org/10.71176/interedtech/17573
Qadhi, S. M., Alduais, A., Chaaban, Y., & Khraisheh, M. (2024). Generative AI, research ethics, and higher education research: Insights from a scientometric analysis. Information, 15(6), Article 325. https://doi.org/10.3390/info15060325
Rütti-Joy, O., Winder, G., & Biedermann, H. (2023). Building AI literacy for sustainable teacher education. Zeitschrift für Hochschulentwicklung, 18(4), 175-189. https://doi.org/10.21240/zfhe/18-04/10
Sailer, M., Bauer, E., Hofmann, R., Kiesewetter, J., Glas, J., Gurevych, I., & Fischer, F. (2023). Adaptive feedback from artificial neural networks facilitates pre-service teachers’ diagnostic reasoning in simulation-based learning. Learning and Instruction, 83, Article 101620. https://doi.org/10.1016/j.learninstruc.2022.101620
Sămărescu, N., Bumbac, R., Zamfiroiu, A., & Iorgulescu, M. C. (2024). Artificial intelligence in education: Next-gen teacher perspectives. Amfiteatru Economic, 26(65), 145-161. https://doi.org/10.24818/EA/2024/65/145
Sanusi, I. T., Ayanwale, M. A., & Tolorunleke, A. E. (2024). Investigating pre-service teachers’ artificial intelligence perception from the perspective of planned behavior theory. Computers and Education: Artificial Intelligence, 6, Article 100202. https://doi.org/10.1016/j.caeai.2024.100202
Shen, Y., & Cui, W. (2024). Perceived support and AI literacy: The mediating role of psychological needs satisfaction. Frontiers in Psychology, 15, Article 1415248. https://doi.org/10.3389/fpsyg.2024.1415248
Shoaib, M., Sayed, N., Singh, J., Shafi, J., Khan, S., & Ali, F. (2024). AI student success predictor: Enhancing personalized learning in campus management systems. Computers in Human Behavior, 158, Article 108301. https://doi.org/10.1016/j.chb.2024.108301
Söğüt, S. (2024). Generative artificial intelligence in EFL writing: A pedagogical stance of pre-service teachers and teacher trainers. Focus on ELT Journal, 6(1), 58-73. https://doi.org/10.14744/felt.6.1.5
Srinivasan, V., & Murthy, H. (2021). Improving reading and comprehension in K-12: Evidence from a large-scale AI technology intervention in India. Computers and Education: Artificial Intelligence, 2, Article 100019. https://doi.org/10.1016/j.caeai.2021.100019
Sun, F., & Ye, R. (2023). Moral considerations of artificial intelligence. Science and Education, 32(1), 1-17. https://doi.org/10.1007/s11191-021-00282-3
Sun, F., Tian, P., Sun, D., Fan, Y., & Yang, Y. (2024). Pre-service teachers’ inclination to integrate AI into STEM education: Analysis of influencing factors. British Journal of Educational Technology, 55(6), 2574-2596. https://doi.org/10.1111/bjet.13469
Tan, S. (2020). A brief analysis of AI curricula construction and development orientation from the perspective of innovation and entrepreneurship education. Creative Education, 11(10), 1866-1872. https://doi.org/10.4236/ce.2020.1110136
Tomar, P., & Verma, S. (2021). Impact and role of AI technologies in teaching, learning, and research in higher education. In S. Verma, & P. Tomar (Eds.), Impact of AI technologies on teaching, learning, and research in higher education (pp. 190-203). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-7998-4763-2.ch012
Uzumcu, O., & Acilmis, H. (2024). Do innovative teachers use AI-powered tools more interactively? A study in the context of diffusion of innovation theory. Technology, Knowledge and Learning, 29(2), 1109-1128. https://doi.org/10.1007/s10758-023-09687-1
Velander, J., Taiye, M. A., Otero, N., & Milrad, M. (2024). Artificial intelligence in K-12 education: Eliciting and reflecting on Swedish teachers’ understanding of AI and its implications for teaching & learning. Education and Information Technologies, 29(4), 4085-4105. https://doi.org/10.1007/s10639-023-11990-4
Voulgari, I., Zammit, M., Stouraitis, E., Liapis, A., & Yannakakis, G. (2021). Learn to machine learn: Designing a game based approach for teaching machine learning to primary and secondary education students. In Proceedings of the Interaction Design and Children (pp. 593-598). https://doi.org/10.1145/3459990.3465176
Wang, D., Bian, C., & Chen, G. (2024a). Using explainable AI to unravel classroom dialogue analysis: Effects of explanations on teachers’ trust, technology acceptance and cognitive load. British Journal of Educational Technology, 55(6), 2530-2556. https://doi.org/10.1111/bjet.13466
Wang, K., Ruan, Q., Zhang, X., Fu, C., & Duan, B. (2024b). Pre-service teachers’ GenAI anxiety, technology self-efficacy, and TPACK: Their structural relations with behavioral intention to design GenAI-assisted teaching. Behavioral Sciences, 14(5), Article 373. https://doi.org/10.3390/bs14050373
Wang, T., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the potential impact of artificial intelligence (AI) on international students in higher education: Generative AI, chatbots, analytics, and international student success. Applied Sciences, 13(11), Article 6716. https://doi.org/10.3390/app13116716
Xia, L., & Zheng, G. (2020). To meet the trend of AI: The ecology of developing AI talents for pre-service teachers in China. International Journal of Learning and Teaching, 6(3), 186-190. https://doi.org/10.18178/IJLT.6.3.186-190
Xing, C. (2023). Research on the application of artificial intelligence empowered education management. Journal of Artificial Intelligence Practice, 6(6), Article 060602. https://doi.org/10.23977/jaip.2023.060602
Yang, Y., & Xu, X. (2024). Research on artificial intelligence literacy level and its influencing factors of high school students. International Journal of Social Science and Research, 2(2). https://doi.org/10.58531/ijssr/2/2/1
Yau, K. W., Chai, C. S., Chiu, T. K. F., Meng, H., King, I., & Yam, Y. (2023). A phenomenographic approach on teacher conceptions of teaching artificial intelligence (AI) in K-12 schools. Education and Information Technologies, 28(1), 1041-1064. https://doi.org/10.1007/s10639-022-11161-x
Yehya, F., ElSayary, A., Al Murshidi, G., & Al Zaabi, A. (2025). Artificial intelligence integration and teachers’ self-efficacy in physics classrooms. Eurasia Journal of Mathematics, Science and Technology Education, 21(8), Article em2679. https://doi.org/10.29333/ejmste/16660
Yim, I. H. Y., & Su, J. (2024). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. Journal of Computers in Education, 12, 93-131. https://doi.org/10.1007/s40692-023-00304-9
Younis, B. (2024). Effectiveness of a professional development program based on the instructional design framework for AI literacy in developing AI literacy skills among pre-service teachers. Journal of Digital Learning in Teacher Education, 40(3), 142-158. https://doi.org/10.1080/21532974.2024.2365663
Zakaria, N. Y. K., & Hashim, H. (2024). Shaping the future of education: Conceptualising pre-service teachers’ perspectives on artificial intelligence (AI) Integration. International Journal of Academic Research in Business and Social Sciences, 14(5), 643-653. https://doi.org/10.6007/ijarbss/v14-i5/21584
Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023). Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis. International Journal of Educational Technology in Higher Education, 20, Article 49. https://doi.org/10.1186/s41239-023-00420-7
Zhang, J., & Zhang, Z. (2024). AI in teacher education: Unlocking new dimensions in teaching support, inclusive learning, and digital literacy. Journal of Computer Assisted Learning, 40(4), 1871-1885. https://doi.org/10.1111/jcal.12988
Zou, B., Guan, X., Shao, Y., & Chen, P. (2023). Supporting speaking practice by social network-based interaction in artificial intelligence (AI)-assisted language learning. Sustainability, 15(4), Article 2872. https://doi.org/10.3390/su15042872

Citation

Ponomarenko, E. B., Sergeeva, O. V., Zheltukhina, M. R., Baranova, K. M., Budkevich, R. L., & Melnik, M. V. (2026). Examining the use of artificial intelligence in pre-service teacher education. Contemporary Educational Technology, 18(2), Article ep650. https://doi.org/10.30935/cedtech/18458

Ponomarenko, E. B., Sergeeva, O. V., Zheltukhina, M. R., Baranova, K. M., Budkevich, R. L., and Melnik, M. V. (2026). Examining the use of artificial intelligence in pre-service teacher education. Contemporary Educational Technology, 18(2), ep650. https://doi.org/10.30935/cedtech/18458

Ponomarenko EB, Sergeeva OV, Zheltukhina MR, Baranova KM, Budkevich RL, Melnik MV. Examining the use of artificial intelligence in pre-service teacher education. CONT ED TECHNOLOGY. 2026;18(2), ep650. https://doi.org/10.30935/cedtech/18458

Ponomarenko, Elena B., Olga V. Sergeeva, Marina R. Zheltukhina, Kseniia M. Baranova, Roza L. Budkevich, and Mariya V. Melnik. "Examining the use of artificial intelligence in pre-service teacher education". Contemporary Educational Technology 2026 18 no. 2 (2026): ep650. https://doi.org/10.30935/cedtech/18458

Ponomarenko, Elena B. et al. "Examining the use of artificial intelligence in pre-service teacher education". Contemporary Educational Technology, vol. 18, no. 2, 2026, ep650. https://doi.org/10.30935/cedtech/18458

Ponomarenko EB, Sergeeva OV, Zheltukhina MR, Baranova KM, Budkevich RL, Melnik MV. Examining the use of artificial intelligence in pre-service teacher education. CONT ED TECHNOLOGY. 2026;18(2):ep650. https://doi.org/10.30935/cedtech/18458