Authors : Mechelle M. Debalucos; Marivel B. Go

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/yc5fzdsy

Scribd : https://tinyurl.com/cdphuc2s

DOI : https://doi.org/10.38124/ijisrt/26apr1784

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This study investigated elementary teachers’ utilization of ChatGPT in developing instructional materials, using the Technology Acceptance Model (TAM) as the guiding framework. A mixed-method research design was employed to capture teachers’ perceptions, behaviors, and experiences. Quantitative data were gathered using validated Likert-scaled questionnaires measuring perceived usefulness, perceived ease of use, attitude toward use, behavioral intention to use, and actual system use. Qualitative data, on the other hand, were collected through semi-structured interviews, focus group discussions (FGDs), and Learning Action Cell (LAC) sessions to capture deeper insights into teachers’ challenges and practical strategies. Forty elementary teachers from selected schools in the Alcantara District, Cebu, participated in the study. Findings revealed that teachers—mostly young, female, and mid-career—perceived ChatGPT as highly useful in reducing workload, enhancing efficiency, and improving the quality of instructional materials. Teachers also found the tool intuitive and user-friendly. Although teachers displayed strong positive attitudes and a high intention to use ChatGPT, actual system use remained moderate. Factors such as limited prompting skills, internet instability, occasional AI inaccuracies, and concerns about content reliability influenced the frequency of use. Significant differences were found when respondents were grouped by age, grade level handled, and number of subjects taught. Correlation analysis further confirmed strong, positive relationships among TAM constructs, demonstrating their predictive influence on actual use. Overall, the results highlight the need for structured training aimed at strengthening teachers’ AI literacy, prompting proficiency, verification habits, and pedagogical integration.

Keywords : ChatGPT, Elementary Teachers, Instructional Materials, TAM, AI in Education.

References :

1. American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). American Psychological Association.
2. Ayanwale, O., Bello, T., & Oladejo, A. (2022). Technology adoption and digital literacy among elementary teachers. Journal of Educational Technology Research, 15(2), 45–60.
3. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
4. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
5. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
6. Gonzales, R., & Gonzales, M. (2024). Application of the Technology Acceptance Model to AI adoption among teachers. International Journal of Educational Innovation, 10(1), 12–29.
7. Karpouzis, K., Pantazatos, S., Taouki, K., & Meli, D. (2024). Generative AI for lesson planning in primary education. Computers & Education, 202, 104–118. https://doi.org/10.1016/j.compedu.2023.104118
8. Khoo, Y., & Jamaludin, A. (2025). Teacher acceptance of artificial intelligence using the Technology Acceptance Model. Education and Information Technologies, 30(1), 145–162. https://doi.org/10.1007/s10639-024-11512-3
9. Lin, H., Zhang, S., & Liu, Y. (2023). TAM-based analysis of AI adoption in education. Journal of Educational Computing Research, 61(5), 1205–1226. https://doi.org/10.1177/07356331231100012
10. Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). SAGE Publications.
11. Rahiman, S., Ismail, N., & Yusuf, F. (2023). Digital literacy and generative AI adoption in schools: Challenges and strategies. Journal of Educational Technology Development, 21(3), 78–94.
12. Riordan, B., Echeverria, A., Jin, H., Yan, Z., Swiecki, Z., Gašević, D., & Martinez Maldonado, R. (2023). Human-centered AI in education: Challenges of accuracy and trust. Learning Analytics Review, 12(1), 34–51.
13. Xue, H., Ghazali, S., & Mahat, N. (2025). Teacher adoption of AI in education: A review using TAM. Computers in Human Behavior, 136, 107–122. https://doi.org/10.1016/j.chb.2024.107122