Validation of a UTAUT-based scale for the use of AI in university students
DOI:
https://doi.org/10.32870/Ap.v17n2.2678Keywords:
Artificial intelligence, Psychometrics, Education, University studentsAbstract
This study aimed to develop and validate a psychometric instrument based on the UTAUT model to assess the acceptance and use of artificial intelligence (AI) among Mexican university students. It was quantitative, cross-sectional, and instrumental research, using a convenience sample of 213 students from the University of Sonora. Analyses included reliability (Cronbach’s alpha), confirmatory factor analysis, and Rasch modeling. Results showed that the instrument had solid psychometric properties, with strong internal consistency, construct validity, and ítem fit. Significant correlations were found, especially between performance expectancy, attitude towards technology, and behavioral intention. Study limitations included the non-probabilistic sampling and the underrepresentation of senior students. The main contribution was the validation of a context-specific scale for assessing AI use in Mexican higher education. It was concluded that the instrument is reliable and valuable for future research and educational interventions aimed at fostering the ethical and effective use of AIReferences
Castillo-Martínez, I., Flores-Bueno, D., Gómez-Puente, S., & Vite-León, V. (2024). AI in higher education: A systematic literature review. Frontiers in Education, 9, 1391485. https://doi.org/10.3389/feduc.2024.1391485
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Davis, F. (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
Goel, A., & Joyner, D. (2017). Using AI to teach AI: Lessons from an online AI class. AI Magazine, 38(2), 48–59. https://doi.org/10.1609/aimag.v38i2.2732
Hernández, J., Espinosa, J., Peñaloza, M., Rodríguez, J., Chacón, J., Toloza, C., Arenas, M., Carrillo, S., & Bermúdez, V. (2018). Sobre el uso adecuado del coeficiente de correlación de Pearson: definición, propiedades y suposiciones. Archivos Venezolanos de Farmacología y Terapéutica, 37(5), 587–595. http://saber.ucv.ve/ojs/index.php/rev_aavft/article/view/16165
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. https://discovery.ucl.ac.uk/id/eprint/10139722/
Kasneci, E., Sessler, K., Gröschner, A., Chen, W., & Golla, D. (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
Kline, R. (2016). Principles and practice of structural equation modeling. Canadian Psychology, 40(3), 381.
Linacre, J. (2007). Winsteps® Rasch measurement computer program user’s guide (Version 3.61.2). Winsteps.com.
Luckin, R., & Holmes, W. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education. https://discovery.ucl.ac.uk/id/eprint/1475756/
Marangunić, N., & Granić, A. (2015). Technology acceptance model: A literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81–95. https://doi.org/10.1007/s10209-014-0348-1
Marchewka, J., Liu, C., & Kostiwa, K. (2007). An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA, 7(2), 93–104.
Marsh, H., Hau, K.-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and
Bentler’s (1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11(3), 320–341. https://doi.org/10.1207/s15328007sem1103_2
Michel, M., Torres, L., & Quevedo, L. (2012). Estudio de traducción y confiabilidad del instrumento de la Teoría Unificada de la Aceptación y Uso de la Tecnología (UTAUT). Apertura, 4(2), 96–105.
Oshlyansky, L., Cairns, P., & Thimbleby, H. (2007). Validating the Unified Theory of Acceptance and Use of Technology (UTAUT) tool cross-culturally. Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI... but not as we know it. 2, 83–86. British Computer Society.
Selwyn, N. (2022). The future of AI and education: Some cautionary notes. European Journal of Education, 57, 620–631. https://doi.org/10.1111/ejed.12532
Susnjak, T. (2022). ChatGPT: The End of Online Exam Integrity?. ArXiv. DOI:
https://doi.org/10.48550/arXiv.2212.09292
UNESCO. (2021). Recommendation on the ethics of artificial intelligence. https://unesdoc.unesco.org/ark:/48223/pf0000381137
Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Woolf, B. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann. https://dl.acm.org/doi/10.5555/2155693
Zawacki-Richter, O., Marín, V., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0
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