Model to evaluate the acceptance of the ChatGPT tool in generation Z

Authors

DOI:

https://doi.org/10.29105/vtga10.5-1069

Keywords:

artificial intelligence, factorial analysis, AI Acceptance

Abstract

The objective of this study is to validate an instrument designed to assess the factors of acceptance of the artificial intelligence tool ChatGPT among Generation Z youth in Colima. The theoretical framework is based on a modified version of the AIDUA model, designed to assess the acceptance of artificial intelligence devices. The model and its constructs were adapted to the Spanish language, resulting in 12 factors and 42 items. A pilot test was carried out using an online questionnaire, applied to participants with previous experience using ChatGPT in the municipality of Colima. The sample size was calculated with a subject-to-variable ratio of 5:1. Using this information, a PLS-SEM analysis was performed. The reliability of the questionnaire revealed robust internal consistency. Among the findings, a significant relationship was found between affective and cognitive attitudes towards the acceptance of ChatGPT in studies. This study contributes to the description of the phenomenon of acceptance of intelligent technologies among Generation Z youth.

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References

Antonov, A. (2022). Gestionar la complejidad: la contribución de la UE a la gobernanza de la inteligencia artificial. Revista CIDOB d’Afers Internacionals. (131), 41-68. https://doi.org/10.24241/rcai.2022.131.2.41 DOI: https://doi.org/10.24241/rcai.2022.131.2.41

Bhuiyan, K. H., Ahmed, S., y Jahan, I. (2024). Consumer attitude toward using artificial intelligence (AI) devices in hospitality services. Journal Of Hospitality And Tourism Insights. https://doi.org/10.1108/jhti-08-2023-0551 DOI: https://doi.org/10.1108/JHTI-08-2023-0551

Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., y Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey. Education And Information Technologies. https://doi.org/10.1007/s10639-023-12405-0 DOI: https://doi.org/10.1007/s10639-023-12405-0

Brown, S.A. y Venkatesh, V. (2005). Model of Adoption of Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle. MIS Quarterly, 29 (3), 399-426. http://dx.doi.org/10.2307/25148690 DOI: https://doi.org/10.2307/25148690

Chatterjee, S., y Bhattacharjee, K. K. (2020). Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling. Education And Information Technologies, 25(5), 3443-3463. https://doi.org/10.1007/s10639-020-10159-7 DOI: https://doi.org/10.1007/s10639-020-10159-7

Chi, O.H., Gursoy, D., Chi, C.G., (2020). Tourists’ attitudes toward the use of artificially intelligent (AI) devices in tourism service delivery: moderating role of service value seeking. J. Travel Research, 61(1), 170-185 https://doi.org/10.1177/0047287520971054" DOI: https://doi.org/10.1177/0047287520971054

Coffey, L. (2023). Most students outrunning faculty in AI use, study finds. Inside Higher Ed | Higher Education News, Events And Jobs. https://www.insidehighered.com/news/tech-innovation/artificial-intelligence/2023/10/31/most-students-outrunning-faculty-ai-use

Cortez, P. M., Ong, A. K. S., Diaz, J. F., German, J. D., y Jagdeep, S. J. S. S. (2024). Analyzing Preceding factors affecting behavioral intention on communicational artificial intelligence as an educational tool. Heliyon, 10(3), e25896. https://doi.org/10.1016/j.heliyon.2024.e25896 DOI: https://doi.org/10.1016/j.heliyon.2024.e25896

De la Luz, Antúnez, K. E. (2020). ¿Quiénes son y cómo aprenden los jóvenes pertenecientes a la generación Z? https://repositorio.iberopuebla.mx/handle/20.500.11777/4641?gad_source=1&gclid=CjwKCAjw_e2wBhAEEiwAyFFFo2X2IJZnnkYdJ_MUJhYOBByNDRY0exlNQVyx_ChAIj8dNtA7EMiR5BoCGxoQAvD_BwE

Fornell, C. y Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of marketing research, 39-50. https://doi.org/10.1177/002224378101800104 DOI: https://doi.org/10.1177/002224378101800104

Gansser, O., y Reich, C. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology In Society, 65, 101535. https://doi.org/10.1016/j.techsoc.2021.101535 DOI: https://doi.org/10.1016/j.techsoc.2021.101535

García Peñalvo, F. J., Llorens Largo, F., y Vidal, J. (2024). La nueva realidad de la educación ante los avances de la inteligencia artificial generativa. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 9-39. DOI: https://doi.org/10.5944/ried.27.1.37716

Giannini, S. (2023). Reflexiones sobre la IA generativa y el futuro de la educación. © UNESCO 2023

Guenther, P., Guenther, M., Ringle, C. M., Zaefarian, G., y Cartwright, S. (2023). Improving PLS-SEM use for business marketing research. Industrial Marketing Management, 111, 127-142. https://doi.org/10.1016/j.indmarman.2023.03.010 DOI: https://doi.org/10.1016/j.indmarman.2023.03.010

Gürsoy, D., Hengxuan, O., Lu, L., y Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal Of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.03.008

Gutiérrez, J. (2023, 27 enero). En sólo 5 días, Chat GPT-3 consiguió un millón de usuarios. La Jornada. https://www.jornada.com.mx/notas/2023/01/27/economia/en-solo-5-dias-chat-gpt-3-consiguio-un-millon-de-usuarios/

Hasan Emon, M. M., Hassan, F., Hoque Nahid, M., y Rattanawiboonsom, V. (2023). Predicting Adoption Intention of Artificial Intelligence ChatGPT. The AIUB Journal Of Science And Engineering, 22(2), 189-199. https://doi.org/10.53799/ajse.v22i2.797 DOI: https://doi.org/10.53799/ajse.v22i2.797

Islam, M., Rahman, M. M., Taher, M. A., Quaosar, G. M. A. A., y Uddin, M. A. (2024). Using artificial intelligence for hiring talents in a moderated mechanism. Future Business Journal (Online), 10(1). https://doi.org/10.1186/s43093-024-00303-x DOI: https://doi.org/10.1186/s43093-024-00303-x

Kalla, D., Smith, N. Samaah, F., y Kuraku, S. (2023). Study and Analysis of Chat GPT and its Impact on Different Fields of Study . International Journal of Innovative Science and Research, 8(3). https://ssrn.com/abstract=4402499

Kelly, S., Kaye, S., & Oviedo-Trespalacios, Ó. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics And Informatics, 77(101925). https://doi.org/10.1016/j.tele.2022.101925 DOI: https://doi.org/10.1016/j.tele.2022.101925

Lakens, D. (2022). Sample size justification. Collabra. Psychology, 8(1). https://doi.org/10.1525/collabra.33267 DOI: https://doi.org/10.1525/collabra.33267

Li, M., y Suh, A. (2021). Machinelike or Humanlike? A Literature Review of Anthropomorphism in AI-Enabled Technology. Proceedings Of The Annual Hawaii International Conference On System Sciences. https://doi.org/10.24251/hicss.2021.493" DOI: https://doi.org/10.24251/HICSS.2021.493

Ma, X., y Huo, Y. (2023). Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework. Technology In Society, 75, (102362). https://doi.org/10.1016/j.techsoc.2023.102362 DOI: https://doi.org/10.1016/j.techsoc.2023.102362

Martínez Cenalmor, A. (2023). Impacto de Chat GPT en el entorno educativo: posibilidades y riesgos. http://hdl.handle.net/10651/69004

McKinsey y Company. (2023). El estado de la IA en 2023: El año clave de la IA generativa. https://www.mckinsey.com/featured-insights/destacados/el-estado-de-la-ia-en-2023-el-ano-clave-de-la-ia-generativa/es#research

Microsoft Education Team. (2021). Explore insights from the AI in Education Report. Microsoft Education Blog. https://educationblog.microsoft.com/en-us/2024/04/explore-insights-from-the-ai-in-education-report

Murthy, S. R., y Mani, M. (2013). Discerning Rejection of Technology. SAGE Open, 3(2), 215824401348524. https://doi.org/10.1177/2158244013485248 DOI: https://doi.org/10.1177/2158244013485248

OpenAI. (2018, junio). Improving language understanding with unsupervised learning. https://openai.com/research/language-unsupervised

OpenAI. (2019, febrero). Better language models and their implications. https://openai.com/research/better-language-models

Salifu, I., Arthur, F., Arkorful, V., Nortey, S. A., y Osei-Yaw, R. S. (2024). Economics students’ behavioural intention and usage of ChatGPT in higher education: a hybrid structural equation modelling-artificial neural network approach. Cogent Social Sciences, 10(1). https://doi.org/10.1080/23311886.2023.2300177 DOI: https://doi.org/10.1080/23311886.2023.2300177

Schroth, H. (2019). Are you ready for Gen Z in the workplace?. California Management Review, 61(3), 5-18. DOI: https://doi.org/10.1177/0008125619841006

Szymkowiak, A., Melović, B., Dabić, M., Jeganathan, K., y Kundi, G. S. (2021). Information technology and Gen Z: The role of teachers, the internet, and technology in the education of young people. Technology In Society, 65 (101565). https://doi.org/10.1016/j.techsoc.2021.101565 DOI: https://doi.org/10.1016/j.techsoc.2021.101565

V. Venkatesh, M.G. Morris, G.B. Davis, F.D. Davis, User acceptance of information technology: toward a unified view, MIS Q. (2003) 425–478. DOI: https://doi.org/10.2307/30036540

Zúñiga Vásquez, F. G., Mora Poveda, D. A. y Molina Mora, D. P. (2023).La importancia de la inteligencia artificial en las comunicaciones en los procesos marketing.Vivat Academia, 156, 19-39 DOI: https://doi.org/10.15178/va.2023.156.e1474

Published

2024-09-30

How to Cite

Rodríguez-Gutiérrez, S. A., Vidrio-Barón, S. B., & Vásquez Sánchez, J. R. (2024). Model to evaluate the acceptance of the ChatGPT tool in generation Z. Vinculategica Efan, 10(5), 138–154. https://doi.org/10.29105/vtga10.5-1069