Primary school teachers’ professional readiness for integrating artificial intelligence concepts
Abstract
Artificial intelligence is becoming an important component of contemporary education; however, in primary school, teachers often lack sufficient methodological and ethical preparation to integrate its basic concepts into teaching and learning. The absence of age-appropriate, systematic approaches leads to a persistent gap between the potential of AI technologies and teachers’ readiness to ensure their safe and pedagogically sound application.
The purpose of this study is to substantiate and develop a model of primary school teachers’ professional readiness to introduce basic concepts of artificial intelligence to young learners, as well as to assess the actual level of such readiness based on empirical data. A mixed-methods design was employed, combining an analysis of international frameworks (UNESCO, OECD, AI4K12), pedagogical modelling, and a survey of 97 teachers. Data were analyzed using descriptive statistics, correlation analysis, and thematic coding of open-ended responses. The study’s novelty lies in the operationalization of a three-dimensional readiness model (T-P-E).
The findings indicate that teachers’ self-assessed readiness to work with AI technologies remains low: mean values range from 2.33 (creating didactic materials using AI tools) to 2.81 (understanding ethical aspects). Correlation analysis revealed a moderate and statistically significant relationship between overall AI awareness and actual use of AI tools in teaching practice (r = 0.59), underscoring the need for targeted professional development. The proposed T-P-E model structures teachers’ readiness across technical, pedagogical, and ethical dimensions, identifies key gaps, and provides a foundation for further professional support.
Effective integration of AI concepts in primary education requires a comprehensive approach that combines technical, methodological, and ethical components. The results have practical value for designing teacher professional development programmes and form a conceptual basis for developing age-appropriate learning tasks and activities for students in Grades 1–4.
Downloads
References
Morze, N., Boiko, M., Strutynska, O., & Smyrnova-Trybulska, E. (2024). What should be the digital competence of teachers in the field of artificial intelligence? Open Educational E-Environment of Modern University, 16, 76-91. DOI: https://doi.org/10.28925/2414-0325.2024.166. [in Ukrainian].
Ovcharuk, O. V., Hryshchuk, O. O., & Kravchyna, O. S. (2025). Use of generative artificial intelligence by teachers to improve pedagogical practices: Global and Ukrainian experience. Imidzh suchasnoho pedahoha, 6(225), 5-10.
[in Ukrainian].
Barna, O. V., Boiko, M. A., & Morze, N. V. (2025). Model of primary school teachers’ readiness for implementing STEM education in the era of artificial intelligence. In CEUR Workshop Proceedings (pp. 153-166).
Chiu, T. K., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171.
Council of Europe. (2025). Artificial intelligence and education: Regulating the use of AI systems in education (2nd working conference, 24-25 October 2024). Council of Europe. URL: https://rm.coe.int/prems-019925
gbr-2511-artificial-intelligence-and-education-a4-web-bat/1680b6c970
Dai, Y. Integrating unplugged and plugged activities for holistic AI education: An embodied constructionist pedagogical approach. Educ Inf Technol 30, 6741-6764 (2025). DOI: https://doi.org/10.1007/s10639-02413043-w
Dangol, A., Wolfe, R., Zhao, R., Kim, J., Ramanan, T., Davis, K., & Kientz, J.A. (2025). Children’s Mental Models of AI Reasoning: Implications for AI Literacy Education. Proceedings of the 24th Interaction Design and Children. DOI: https://doi.org/10.1145/3713043.3728856
Dignum, V., Penagos, M., Pigmans, K., & Vosloo, S. (2021). Policy guidance on AI for children. Report, UNICEF, Office of Global Insight & Policy, United Nations Children’s Fund, 10017.
Druga, S., & Ko, A. J. (2021, June). How do children’s perceptions of machine intelligence change when training and coding smart programs?. In Proceedings of the 20th annual ACM interaction design and children conference (pp. 49-61). DOI: https://doi.org/10.1145/3459990.346071
EdTech Hub. (2025, May 21). AI tutors and teaching: How might the role of the teacher change in an age of AI? EdTech Hub. URL: https://edtechhub.org/
Flores, W., & Chiappe, A. (2025). Integrating AI into Education: Preparation Factors and Teachers’ Digital Competencies. Revista Colombiana de Educación, (97), e20825-e20825. DOI: https://doi.org/10.17227/rce.num97-20825
Holmes, W., & Porayska-Pomsta, K. (2023). The ethics of artificial intelligence in education. Lontoo: Routledge, 621-653. DOI: https://doi.org/10.4324/9780429329067
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education promises and implications for teaching and learning. Center for Curriculum Redesign.
Infocomm Media Development Authority. (2024). AI for Fun: National programme for primary schools. Government of Singapore. URL: https://www.imda.gov.sg/how-we-can-help/code-for-fun/ai-for-fun-primary
Kramska, Z., & Denysiuk, T. (2024). Development of digital competence of the future primary school teacher as a condition for ensuring a competitive specialist. Modern Engineering and Innovative Technologies, 1(36-01), 41-44. DOI: https://doi.org/10.30890/2567-5273.2024-36-00-090
Kwabena, B. W. (2025). From Blocks to Code: An AI-Driven Curriculum for Elementary Python Programming. Asian Journal of Education and Social Studies, 51(10), 892-902. DOI: https://doi.org/10.9734/ajess/2025/v51i102540
Long, D., & Magerko, B. (2020). What Is AI Literacy? Competencies and Design Considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-16). Association for Computing Machinery. DOI: https://doi.org/10.1145/3313831.3376727
Miao, F., & Holmes, W. (2021). AI and education: A guidance for policymakers. Unesco Publishing.
Minecraft Education. (2025). AI Foundations: Build digital skills and AI literacy with Minecraft. URL: https://education.minecraft.net/en-us/discover/ai
MIT Media Lab. (2023, May 18). Day of AI 2023. URL: https://media.mit.edu/events/day-of-ai-2023/
Muir, C., Lee, S., & Shin, H. (2023). Children’s reasoning about AI systems: Developmental perspectives. Computers & Education, 193, 104674. DOI: https://doi.org/10.1016/j.compedu.2022.104674
OECD (2025). Empowering learners for the age of AI: An AI literacy framework for primary and secondary education (Review draft). OECD. Paris. URL: https://ailiteracyframework.org
Park, Y., & Shin, Y. (2022). A block-based interactive programming environment for large-scale machine learning education. Applied Sciences, 12(24), 13008. DOI: https://doi.org/10.3390/app122413008
Robles Moral, F. J., & Fernández Dїaz, M. J. (2021). Future primary school teachers’ digital competence in teaching science through the use of social media. Sustainability, 13(5), 2816. DOI: https://doi.org/10.3390/su13052816
Shcherban, T., & Khoma, P. (2024). Formation of digital competence of future primary school teachers by using artificial intelligence. Humanities Studios: Pedagogy, Psychology, Philosophy, 3(12), 36-55. DOI: https://doi.org/10.33407/itlt.v94i2
Touretzky, D., Gardner-McCune, C., & Seehorn, D. (2023). Machine learning and the five big ideas in AI. International journal of artificial intelligence in education, 33(2), 233–266. DOI: https://doi.org/10.1007/s40593-022-00314-1
Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019, July). Envisioning AI for K-12: What should every child know about AI?. In Proceedings of the AAAI conference on artificial intelligence (Vol. 33, No. 01, pp. 9795-9799). DOI: https://doi.org/10.1609/aaai.v33i01.33019795
Tripathi, T., Sharma, S. R., Singh, V., Bhargava, P., & Raj, C. (2025, August). Teaching and learning with AI: a qualitative study on K-12 teachers’ use and engagement with artificial intelligence. In Frontiers in Education (Vol. 10, p. 1651217). Frontiers. DOI: https://doi.org/10.3389/feduc.2025.1651217
Yadav, A., Krist, C., Good, J., & Caeli, E. N. (2018). Computational thinking in elementary classrooms: Measuring teacher understanding of computational ideas for teaching science. Computer Science Education, 28(4), 371-400. DOI: https://doi.org/10.1080/08993408.2018.1560550
Yim, I.H.Y., Su, J. Artificial intelligence (AI) learning tools in K-12 education: A scoping review. J. Comput. Educ. 12, 93-131 (2025). DOI: https://doi.org/10.1007/s40692-023-00304-9
Zhang, S., Ganapathy Prasad, P., & Schroeder, N. L. (2025). Learning About AI: A Systematic Review of Reviews on AI Literacy. Journal of Educational Computing Research, 07356331251342081. DOI: https://doi.org/10.1177/07356331251342081
Zhou, X., Li, Y., Chai, C. S., & Chiu, T. K. (2025). Defining, enhancing, and assessing artificial intelligence literacy and competency in K-12 education from a systematic review. Interactive Learning Environments, 1-23. DOI: https://doi.org/10.1080/10494820.2025.2487538
