Home⇛International Journal of Transformative Multidisciplinary Studies⇛vol. 2 no. 2 (2026)

Perceived Usefulness and Ease of Use as Predictors of Behavioral Intention to Adopt ChatGPT in Higher Education

Merrill Chavez | Michelle De Asis | Melchorie Bepinoso | Rhea Calvo

Discipline: Education

 

Abstract:

1 Fellowship Baptist College, Kabankalan City, Philippines 2 Western Visayas State University- Himamaylan Campus, Himamaylan City, Philippines * calvo_rhea@fbc.ph. education Volume 2, Issue 2, June 2026 Integration of AI-powered tools in higher education requires examining how students perceive their practicality, usability, and willingness to engage. This research explored the use of ChatGPT among 538 undergraduates from two institutions in Southern Negros, Philippines, guided by the Technology Acceptance Model (TAM). Findings revealed that, while the intention to continue use was moderate, learners generally acknowledged its academic value and user-friendliness. Significant differences emerged across training status, year level, and usage frequency, with senior and formally trained participants reporting stronger scores. Regression analysis within the TAM framework demonstrated that perceived utility (β = .567) and ease of interaction (β = .286) were both significant predictors of intention, jointly accounting for 64.5% of variance (R2 = .645). Exploratory factor analysis of the 15-item subset produced a clear three-factor solution, with each construct loading distinctly, thereby affirming the discriminant validity of usefulness, usability, and behavioral intention.



References:

  1. American Psychological Association. (2002). Ethical principles of psychologists and code of conduct. American Psychologist, 57(12), 1060–1073. https://cir.nii.ac.jp/crid/1360011143665271552
  2. Committee on Publication Ethics. (1999). Guidelines on good publication practice. https://publicationethics.org/files/u7141/1999pdf13.pdf
  3. 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
  4. Estrellado, C. P., & Millar, G. B. (2023). ChatGPT: Towards educational technology micro-level framework. International Journal of Science, Technology, Engineering and Mathematics, 3(4), 101–127. https://doi.org/10.53378/353035
  5. Firat, M. (2023). How ChatGPT can transform autodidactic experiences and open education? [Preprint]. OSF Preprints. https://doi.org/10.31219/osf.io/9ge8m
  6. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley. https://philpapers.org/rec/FISBAI?all_versions=1
  7. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson Prentice Hall. https://www.scirp.org/reference/ReferencesPapers?ReferenceID=1841396
  8. Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., . . . Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
  9. Kuhail, M. A., Alturki, N., Alramlawi, S., & Alhejori, K. (2023). Interacting with educational chatbots: A systematic review. Education and Information Technologies, 28(1), 973–1018. https://doi.org/10.1007/s10639-022-11177-3
  10. Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
  11. Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News, 40(3), 26–29. https://doi.org/10.1108/LHTN-01-2023-0009
  12. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill. https://www.scirp.org/reference/ReferencesPapers?ReferenceID=1867797
  13. Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbot applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033
  14. Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9), 5783. https://doi.org/10.3390/app13095783
  15. Sok, S., & Heng, K. (2024). Opportunities, challenges, and strategies for using ChatGPT in higher education: A literature review. Journal of Digital Educational Technology, 4(1), ep2401. https://doi.org/10.30935/jdet/14027
  16. Strzelecki, A. (2024). To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology. Interactive Learning Environments, 32(9), 5142–5155. https://doi.org/10.1080/10494820.2023.2209881
  17. Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel? ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x
  18. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
  19. Wollny, S., Schneider, J., Di Mitri, D., Weidlich, J., Rittberger, M., & Drachsler, H. (2021). Are we there yet? A systematic literature review on chatbots in education. Frontiers in Artificial Intelligence, 4, 654924. https://doi.org/10.3389/frai.2021.654924

Tools


Copyright © 2026  KITE Digital Educational Solutions |  Exclusively distributed by CE-Logic