FACTORS INFLUENCING PRE-SERVICE PRIMARY TEACHERS’ READINESS TO USE ARTIFICIAL INTELLIGENCE IN LESSON PLANNING
DOI:
https://doi.org/10.18173/2354-1075.2025-0091Keywords:
artificial intelligence, lesson planning, teacher education, technology adoption, pre-service primary teachersAbstract
This study examines factors influencing pre-service primary teachers’ willingness to use AI in lesson planning, as they are expected to lead technology integration in the classroom. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Technological Pedagogical Content Knowledge (TPACK) framework, a survey instrument with six components was developed and administered to 468 pre-service teachers at Hanoi Metropolitan University. Data were analyzed using exploratory factor analysis (EFA) in SPSS. Six key factors emerged: (1) expected effectiveness of AI in supporting lesson planning; (2) awareness and attitudes toward using AI in lesson planning; (3) AI-related skills in lesson design; (4) support from lecturers and the institution; (5) technological infrastructure and learning environment; and (6) ethical and legal understanding of AI in education. Among these, Performance Expectancy and AI-related Skills were the strongest predictors, aligning with TAM and UTAUT, while institutional support, infrastructure, and ethical awareness provided essential enabling conditions. The findings confirm classic technology adoption models while highlighting new requirements in teacher training under digital transformation. Practically, the study suggests integrating AI content into curricula, offering hands-on activities with modern AI tools, improving infrastructure, and enhancing faculty capacity.
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References
[1] Huang C, Cai H, Xu L, Xu B, Gu Y & Jiang L, (2019). Data-driven ontology generation and evolution towards intelligent service in manufacturing systems. Future Generation Computer Systems, 101, 197-207. https://doi.org/10.1016/j.future.2019.05.075
[2] 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
[3] Cui W, Xue Z & Thai KP, (2018). Performance comparison of an AI-based adaptive learning system in China. In 2018 Chinese automation congress (CAC), pp. 3170-3175, IEEE. https://doi.org/10.1109/CAC.2018.8623327
[4] Lu Y & Da Xu L, (2018). Internet of Things (IoT) cybersecurity research: A review of current research topics. IEEE Internet of Things Journal, 6(2), 2103-2115. https://doi.org/10.1109/JIOT.2018.2869847
[5] Veloso M, Balch T, Borrajo D, Reddy P & Shah S, (2021). Artificial intelligence research in finance: discussion and examples. Oxford Review of Economic Policy, 37(3), 564-584. https://doi.org/10.1093/oxrep/grab019
[6] Yang C, Huan S & Yang Y, (2020). A practical teaching mode for colleges supported by artificial intelligence. International Journal of Emerging Technologies in Learning (IJET), 15(17), 195-206. https://doi.org/10.3991/ijet.v15i17.16737
[7] Acquah BYS, Arthur F, Salifu I, Quayson E & Nortey SA, (2024). Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach. Computers and Education: Artificial Intelligence, 7, 100307. https://doi.org/10.1016/j.caeai.2024.100307
[8] Park J, Teo TW, Teo A, Chang J, Huang JS & Koo S, (2023). Integrating artificial intelligence into science lessons: Teachers’ experiences and views. International Journal of STEM Education, 10(1), 6. https://doi.org/10.1186/s40594-023-00454-3
[9] Pham TTH, (2022). Curriculum on designing lesson plans for the subject of Literature [In Vietnamese]. Hanoi: Vietnam National University of Education Publishing House.
[10] Ministry of Education and Training, (2021). Circular No. 2345/BGDĐT-GDTH dated June 7, 2021 on guiding the development of school education plans at the primary level.
[11] Venkatesh V, (2022). Adoption and use of AI tools: a research agenda grounded in UTAUT. Annals of Operations Research, 308(1), 641-652. https://doi.org/10.1007/s10479-020-03918-9
[12] Dwivedi YK, Rana NP, Chen H & Williams MD, (2011). A Meta-analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT). In Governance and Sustainability in Information Systems. Managing the Transfer and Diffusion of IT: IFIP WG 8.6 International Working Conference, Hamburg, Germany, September 22-24, 2011. Proceedings (pp. 155-170). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-24148-2_10
[13] Saif N, Khan SU, Shaheen I, Alotaibi FA, Alnfiai MM & Arif M, (2024). Chat-GPT; validating Technology Acceptance Model (TAM) in education sector via ubiquitous learning mechanism. Computers in Human Behavior, 154, 108097. https://doi.org/10.1016/j.chb.2023.108097
[14] Jiao J & Cao X, (2024). Research on designers’ behavioral intention toward Artificial Intelligence-Aided Design: integrating the Theory of Planned Behavior and the Technology Acceptance Model. Frontiers in Psychology, 15, 1450717. https://doi.org/10.3389/fpsyg.2024.1450717
[15] Knauder H & Koschmieder C, (2019). Individualized student support in primary school teaching: A review of influencing factors using the Theory of Planned Behavior (TPB). Teaching and Teacher Education, 77, 66-76. https://doi.org/10.1016/j.tate.2018.09.012
[16] Wang W, Schmidt-Crawford D & Jin Y, (2018). Preservice teachers' TPACK development: A review of literature. Journal of Digital Learning in Teacher Education, 34(4), 234-258. https://doi.org/10.1080/21532974.2018.1498039
[17] Wang C, Wang H, Li Y, Dai J, Gu X & Yu T, (2025). Factors influencing university students’ behavioral intention to use generative artificial intelligence: Integrating the theory of planned behavior and AI literacy. International Journal of Human–Computer Interaction, 41(11), 6649-6671. https://doi.org/10.1080/10447318.2024.2383033
[18] Chang A, (2012). UTAUT and UTAUT 2: A review and agenda for future research. Journal the WINNERS, 13(2), 10-114. https://doi.org/10.21512/tw.v13i2.656
[19] Zaim M, Arsyad S, Waluyo B, Ardi H, Al Hafizh M, Zakiyah M & Hardiah M, (2024). AI-powered EFL pedagogy: Integrating generative AI into university teaching preparation through UTAUT and activity theory. Computers and Education: Artificial Intelligence, 7, 100335.
[20] Cooper DR & Schindler P, (2014). Business research methods. McGraw-Hill.
[21] Granić A & Marangunić N, (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593. https://doi.org/10.1111/bjet.12864
[22] Ajzen I, (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
[23] Le TH, Van HT, Viet HP, Tran Q, Thanh HN, Duy BD & Duc MT, (2025). Integrating AI and IoT into STEM teacher training: A case study of secondary education in Vietnam. Edelweiss Applied Science and Technology, 9(4), 2439-2458. https://doi.org/10.55214/25768484.v9i4.6583
