Dimensiones latentes en la adopción de ChatGPT en la universidad: modelo CHASSIS
Contenido principal del artículo
Resumen
Detalles del artículo

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Autoría: En la lista de autores firmantes deben figurar únicamente aquellas personas que han contribuido intelectualmente al desarrollo del trabajo. Haber colaborado en la recolección de datos no es, por sí mismo, criterio suficiente de autoría. “Alteridad” declina cualquier responsabilidad sobre posibles conflictos derivados de la autoría de los trabajos que se publiquen.
Copyright: La Universidad Politécnica Salesiana conserva los derechos patrimoniales (copyright) de los artículos publicados, y favorece y permite la reutilización de las mismas bajo la licencia Creative Commons Atribución-NoComercial-CompartirIgual 3.0 Ecuador. Se pueden copiar, usar, difundir, transmitir y exponer públicamente, siempre que: i) se cite la autoría y la fuente original de su publicación (revista, editorial y URL de la obra); ii) no se usen para fines comerciales; iii) se mencione la existencia y especificaciones de esta licencia de uso.
Referencias
Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D., Mohammed, A. H., Hassan, B. A. R., Wayyes, A. M., Farhan, S. S., Khatib, S. E., Rahal, M., Sahban, A., Abdelaziz, D. H., Mansour, N. O., AlZayer, R., Khalil, R., Fekih-Romdhane, F., Hallit, R., Hallit, S., & Sallam, M. (2024). A multinational study on the factors influencing university students’ attitudes and usage of ChatGPT. Scientific Reports, 14(1), 19831. https://doi.org/10.1038/s41598-024-52549-8
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. En J. Kuhl & J. Beckmann (Eds.), Action-control: From cognition to behavior (pp. 11-39). Heidelberg: Springer.
Akhtar-Danesh, N. (2023) Impact of factor rotation on Q-methodology analysis. PLoS ONE, 18(9), e0290728. https://doi.org/10.1371/journal.pone.0290728
Al-Abdullatif, A. M., & Alsubaie, M. A. (2024). ChatGPT in learning: Assessing students’ use intentions through the lens of perceived value and the influence of AI literacy. Behavioral Sciences, 14(9), 845. https://doi.org/10.3390/bs14090845
Bartlett, M. S. (1951). The effect of standardization on a χ² approximation in factor analysis. Biometrika, 38(3/4), 337–344. https://doi.org/10.2307/2332580
Bettayeb, A. M., Abu Talib, M., Sobhe Altayasinah, A. Z., & Dakalbab, F. (2024). Exploring the impact of ChatGPT: Conversational AI in education. Frontiers in Education, 9, 1379796. https://doi.org/10.3389/feduc.2024.1379796
Bilquise, G., Ibrahim, S., & Salhieh, S. M. (2023). Investigación sobre la aceptación de un chatbot de asesoramiento académico por parte de los estudiantes en instituciones de educación superior. Educación y Tecnologías de la Información, 29(5), 6357–6382. https://doi.org/10.1007/s10639-023-12076-x
Bolívar-Cruz, A. & Verano-Tacoronte, D. (2025). Is Anxiety Affecting the Adoption of ChatGPT in University Teaching? A Gender Perspective. Tech Know Learn, 9(4), 1-20. https://doi.org/10.1007/s10758-025-09830-0
Bosnjak, M., Ajzen, I., & Schmidt, P. (2020). The Theory of Planned Behavior: Selected recent advances and applications. Europe's Journal of Psychology, 16(3), 352–356. https://doi.org/10.5964/ejop.v16i3.3107
Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press.
Budhathoki, T., Zirar, A., Njoya, E. T., & Timsina, A. (2024). ChatGPT adoption and anxiety: a cross-country analysis utilising the unified theory of acceptance and use of technology (UTAUT). Studies in Higher Education, 49(5), 831–846. https://doi.org/10.1080/03075079.2024.2333937
Choudhury, A., & Shamszare, H. (2023). Investigating the impact of user trust on the adoption and use of ChatGPT: Survey analysis. JMIR Human Factors, 25, e47184. https://doi.org/10.2196/47184
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. https://doi.org/10.1007/BF02310555
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
Din Bandhu, M., Murali Mohan, M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024). Theories of motivation: A comprehensive analysis of human behavior drivers. Acta Psychologica, 244, 104177. https://doi.org/10.1016/j.actpsy.2024.104177
Farhi, F., Jeljeli, R., Aburezeq, I., Dweikat, F. F., Al-shami, S. A., & Slamene, R. (2023). Analyzing the students' views, concerns, and perceived ethics about ChatGPT usage. Computers and Education: Artificial Intelligence, 5, 100180. https://doi.org/10.1016/j.caeai.2023.100180
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
García-Alonso, E.M.; León-Mejía, A.C.; Sánchez-Cabrero, R.; Guzmán-Ordaz, R. (2024). Training and Technology Acceptance of ChatGPT in University Students of Social Sciences: A Netcoincidental Analysis. Behav. Sci., 14, 612. https://doi.org/10.3390/bs14070612
Gupta, B., Mufti, T., Sohail, SS y Madsen, D. Ø. (2023). ChatGPT: una breve revisión narrativa. Cogent Business & Management, 10 (3), 2275851. https://doi.org/10.1080/23311975.2023.2275851
Gupta, V. (2024). An Empirical Evaluation of a Generative Artificial Intelligence Technology Adoption Model from Entrepreneurs’ Perspectives. Systems, 12(3), 103. https://doi.org/10.3390/systems12030103
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning.
Heredia-Carroza, J., Chavarría-Ortiz, C., López-Estrada, S., & Zacharewicz, T. (2024). How to enhance the entrepreneurial intentions of the young population in rural areas: An approach from personal values and the socioeconomic environment. European Research on Management and Business Economics, 30(3), 100261. https://doi.org/10.1016/j.iedeen.2024.100261
Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. https://doi.org/10.1177/001316446002000116
Kaiser, H. F. (1970). A second generation little jiffy. Psychometrika, 35(4), 401–415. https://doi.org/10.1007/BF02291817
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575
Klimova, B. & de Campos, V. P. L. (2024). University undergraduates’ perceptions on the use of ChatGPT for academic purposes: evidence from a university in Czech Republic. Cogent Education, 11(1), 2373512. https://doi.org/10.1080/2331186X.2024.2373512
Lai, C. Y., Cheung, K. Y., Chan, C. S., & Law, K. K. (2024). Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students. Computers and Education: Artificial Intelligence, 6, 100246. https://doi.org/10.1016/j.caeai.2024.100246
Latif, E. & Zhai, X. (2024). Fine-tuning ChatGPT for automatic scoring. Computers and Education: Artificial Intelligence, 6, 100210. https://doi.org/10.1016/j.caeai.2024.100210
Leng, L. (2024). Challenge, integration, and change: ChatGPT and future anatomical education. Medical Education Online, 29, 2304973. https://doi.org/10.1080/10872981.2024.2304973
Menon, D., & Shilpa, K. (2023). “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to use the OpenAI's ChatGPT using the UTAUT model. Heliyon, 9(11), e20962. https://doi.org/10.1016/j.heliyon.2023.e20962
Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154. https://doi.org/10.1016/j.iotcps.2023.04.003
Romero Rodríguez, J. M., Ramírez Montoya, M. S., Buenestado Fernández, M., & Lara-Lara, F. (2023). Uso de ChatGPT en la universidad como herramienta para el pensamiento complejo: Utilidad percibida por los estudiantes. Journal of New Approaches in Educational Research, 12, 323–339. https://doi.org/10.7821/naer.2023.7.1458
Roumeliotis, K. I., & Tselikas, N. D. (2023). ChatGPT and Open-AI Models: A Preliminary Review. Future Internet, 15(6), 192. https://doi.org/10.3390/fi15060192
Sallam, M., Salim, N., Barakat, M., Al-Mahzoum, K., Al-Tammemi, A., Malaeb, D., Hallit, R., & Hallit, S. (2023). Assessing health students' attitudes and usage of ChatGPT in Jordan: Validation study. JMIR Medical Education, 9, e48254. https://doi.org/10.2196/48254
Shahzad, M.F., Xu, S. & Javed, I. (2024). ChatGPT awareness, acceptance, and adoption in higher education: the role of trust as a cornerstone. Int J Educ Technol High Educ, 21(46), 1-23. https://doi.org/10.1186/s41239-024-00478-x
Stahl, B. C., & Eke, D. (2024). The ethics of ChatGPT – Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700. https://doi.org/10.1016/j.ijinfomgt.2023.102700
Strzelecki, A. (2024) Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology. Innov High Educ, 49 223–245. https://doi.org/10.1007/s10755-023-09686-1
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International Journal of Medical Education, 2, 53-55. http://doi.org.10.5116/ijme.4dfb.8dfd
Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
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
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