Optimizing Elementary School Teachers' Competence in AI-Based Learning Media Development through Artificial Intelligence Training
DOI:
https://doi.org/10.32585/cognitive.v4i1.67Keywords:
Artificial Intelligence, Teacher Training, Elementary School, Digital Learning, Instructional MediaAbstract
The rapid development of digital technology, particularly Artificial Intelligence (AI), has significantly influenced educational practices, including at the elementary school level. However, many teachers still face challenges in utilizing AI effectively due to limited digital literacy and a lack of training. This study aims to optimize the use of AI in learning through a structured training program for elementary school teachers. The research employed a quantitative approach with a pretest-posttest design involving a group of elementary school teachers as participants. Data were collected through questionnaires, tests, and observations to measure changes in teachers’ knowledge and skills before and after the training. The results indicate a significant improvement in teachers’ understanding and ability to use AI tools for developing instructional media, preparing teaching materials, and conducting assessments. The findings suggest that AI training effectively enhances teachers’ digital competence and supports more innovative and efficient learning processes. The training introduced teachers to various Artificial Intelligence applications, including AI-assisted presentation generators, AI video creators, quiz generators, image generators, and large language models for developing teaching materials. Participants practiced creating learning videos, digital teaching materials, interactive quizzes, presentation slides, and classroom assessments. The results showed significant improvements in teachers’ digital competence and confidence in integrating AI into elementary classroom instruction.
References
Cheikh Youssef, S., Haram, K., Noël, J., Patel, V., Porter, J., Dasgupta, P., & Hachach-Haram, N. (2023). Evolution of the digital operating room: the place of video technology in surgery. In Langenbeck’s Archives of Surgery. https://doi.org/10.1007/s00423-023-02830-7
Fakhar, H., Lamrabet, M., Echantoufi, N., El Khattabi, K., & Ajana, L. (2024). Artificial Intelligence from Teachers’ Perspectives and Understanding: Moroccan Study. International Journal of Information and Education Technology. https://doi.org/10.18178/ijiet.2024.14.6.2111
Galindo-Domínguez, H., Delgado, N., Losada, D., & Etxabe, J. M. (2024). An analysis of the use of artificial intelligence in education in Spain: The in-service teacher’s perspective. Journal of Digital Learning in Teacher Education. https://doi.org/10.1080/21532974.2023.2284726
Huallpa, J. J., Flores Arocutipa, J. P., Panduro, W. D., Huete, L. C., Flores Limo, F. A., Herrera, E. E., Alba Callacna, R. A., Ariza Flores, V. A., Medina Romero, M. Á., Quispe, I. M., & Hernández Hernández, F. A. (2023). Exploring the ethical considerations of using Chat GPT in university education. Periodicals of Engineering and Natural Sciences. https://doi.org/10.21533/pen.v11i4.3770
Kim, D., Hwang, W., Bae, J., Park, H., & Kim, K. G. (2021). Video archiving and communication system (Vacs): A progressive approach, design, implementation, and benefits for surgical videos. Healthcare Informatics Research. https://doi.org/10.4258/HIR.2021.27.2.162
Lee, S. J., & Kwon, K. (2024). A systematic review of AI education in K-12 classrooms from 2018 to 2023: Topics, strategies, and learning outcomes. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2024.100211
Leong, W. Y., Leong, Y. Z., & Leong, W. S. (2024). Artificial Intelligence in Education. IET Conference Proceedings. https://doi.org/10.1049/icp.2024.4341
Mercan, G. (2025). Google VEO 3 As A Pedagogical Partner AI-Driven Storytelling For Conceptual, Affective, And Critical Learning in Science Education. Sinop Üniversitesi Sosyal Bilimler Dergisi. https://doi.org/10.30561/sinopusd.1749874
Niu, S. J., Luo, J., Niemi, H., Li, X., & Lu, Y. (2022). Teachers’ and Students’ Views of Using an AI-Aided Educational Platform for Supporting Teaching and Learning at Chinese Schools. Education Sciences. https://doi.org/10.3390/educsci12120858
Ocak, C., Kopcha, T. J., & Dey, R. (2023). An AI-enhanced pattern recognition approach to temporal and spatial analysis of children’s embodied interactions. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2023.100146
Ossiannilsson, E., Cazarez, R. L. U., Goode, C., Mansour, C., & DE GUSMÃO, C. M. G. (2024). Artificial Intelligence Use to Empower the Implementation of OER and the UNESCO OER Recommendation. Open Praxis. https://doi.org/10.55982/openpraxis.16.2.650
Saad, S., Ahmed, S., Ayub Khan, M. N., & Khan, M. I. (2026). Exploring the digital competencies of clinical educators: a framework-based qualitative study. BMC Medical Education. https://doi.org/10.1186/s12909-025-08389-9
Verma, N., Getenet, D. S., Dann, D. C., & Shaik, T. (2023). Designing an artificial intelligence tool to understand student engagement based on teacher’s behaviours and movements in video conferencing. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2023.100187
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Hamda Kharisma Putra, Singgih Subiyantoro, Syifa Fauziah, Akhmad Setyawan
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
This work is licensed under a Creative Commons Attribution 4.0 International License.
