Development of a measurement instrument for Acceptance of an artificial intelligence platform

Authors

DOI:

https://doi.org/10.29105/vtga11.3-1141

Keywords:

Artificial Intelligence, ChatGPT, AI Acceptance, Academic Development, Measurement Instrument

Abstract

Currently, Artificial Intelligence (AI) has been consolidated in the scientific, technological and educational fields. Tools such as ChatGPT help in the search for information and in the performance of various activities, having an interaction between humans and machines. The acceptance of this AI platform in the educational field, being a promising tool, encourages students to adopt it in their day-to-day lives, thus generating an impact on their academic development. Therefore, the present study aims to develop a measurement instrument for the acceptance of an artificial intelligence platform. It is important to mention that an exhaustive and systematic search of the literature was carried out to identify both the factors that affect the acceptance of the technology and those items for its measurement. Likewise, the type of research in this study is exploratory and descriptive, since, through the review of literature in specialized databases, it was possible to identify and define the phenomenon under study. Thanks to the results obtained, it was possible to develop a measurement instrument, as well as a causal model with which the level of acceptance of the application of AI can be measured.

Downloads

Download data is not yet available.

References

Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D. & Sallam, M. (2024). A multinational study on the factors influencing university students’ attitudes and usage of ChatGPT. Scientific Reports, 14(1), 1983. DOI: https://doi.org/10.1038/s41598-024-52549-8

Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human behavior and emerging technologies, 2(4), 314-324. DOI: https://doi.org/10.1002/hbe2.195

Ajzen, I., Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, Nueva Jersey, Prentice-Hall.

Bedregal-Alpaca, N., Cornejo-Aparicio, V., Tupacyupanqui-Jaén, D., & Flores-Silva, S. (2019). Evaluación de la percepción estudiantil en relación al uso de la plataforma Moodle desde la perspectiva del TAM. Ingeniare. Revista chilena de ingeniería, 27(4), 707-718. DOI: https://doi.org/10.4067/S0718-33052019000400707

Chaudhry, M. A., & Kazim, E. (2022). Artificial Intelligence in Education (AIEd): A high-level academic and industry note 2021. AI and Ethics, 2(1), 157-165. DOI: https://doi.org/10.1007/s43681-021-00074-z

Cheema, U., Rizwan, M., Jalal, R., Durrani, F., & Sohail, N. (2013). The trend of online shopping in 21st century: Impact of enjoyment in TAM Model. Asian journal of empirical research, 3(2), 131-141.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3):319-340. DOI: https://doi.org/10.2307/249008

Davis, F. D., Bagozzi, R. P., Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science 35(8):982-1003. DOI: https://doi.org/10.1287/mnsc.35.8.982

García-Peñalvo, F. J. (2023). La percepción de la Inteligencia Artificial en contextos educativos tras el lanzamiento de ChatGPT: disrupción o pánico. Education in the Knowledge Society (EKS), 24, e31279-e31279. DOI: https://doi.org/10.14201/eks.31279

Giansanti, D. (2023). Precision Medicine 2.0: How digital health and AI are changing the game. Journal of Personalized Medicine, 13(7), 1057. DOI: https://doi.org/10.3390/jpm13071057

Haleem, A., Javaid, M. y Singh, R. P. (2022). An era of ChatGPT as a significant futuris¬tic support tool: a study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2(4), 1-8. DOI: https://doi.org/10.1016/j.tbench.2023.100089

Hasanein, A. M., & Sobaih, A. E. E. (2023). Drivers and Consequences of ChatGPT Use in Higher Education: Key Stakeholder Perspectives. European Journal of Investigation in Health, Psychology and Education, 13(11), 2599-2614. DOI: https://doi.org/10.3390/ejihpe13110181

Hulleman, C. S., & Harackiewicz, J. M. (2009). Promoting interest and performance in high school science classes. science, 326(5958), 1410-1412. DOI: https://doi.org/10.1126/science.1177067

Ibrahim, H., Liu, F., Asim, R., Battu, B., Benabderrahmane, S., Alhafni, B. & Zaki, Y. (2023). Perception, performance, and detectability of conversational artificial intelligence across 32 university courses. Scientific Reports, 13(1), 12187. DOI: https://doi.org/10.1038/s41598-023-43998-8

Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), 12451. DOI: https://doi.org/10.3390/su151612451

Khechine, H., Raymond, B. y Augier, M. (2020). La adopción de un sistema de aprendizaje social: valor intrínseco en el modelo UTAUT. Revista británica de tecnología educativa, 51 (6), 2306–2325. DOI: https://doi.org/10.1111/bjet.12905 DOI: https://doi.org/10.1111/bjet.12905

Kim, S. G. (2023). Using ChatGPT for language editing in scientific articles. Maxillofacial plastic and reconstructive surgery, 45(1), 13. DOI: https://doi.org/10.1186/s40902-023-00381-x

Korteling, J. H., van de Boer-Visschedijk, G. C., Blankendaal, R. A., Boonekamp, R. C., & Eikelboom, A. R. (2021). Human-versus artificial intelligence. Frontiers in artificial intelligence, 4, 622364. DOI: https://doi.org/10.3389/frai.2021.622364

Lanlan, Z., Ahmi, A., & Popoola, O. M. J. (2019). Perceived ease of use, perceived usefulness and the usage of computerized accounting systems: A performance of micro and small enterprises (mses) in china. International Journal of Recent Technology and Engineering, 8(2), 324-331. DOI: https://doi.org/10.35940/ijrte.B1056.0782S219

Montenegro-Rueda, M., Fernández-Cerero, J., Fernández-Batanero, J. M., & López-Meneses, E. (2023). Impact of the implementation of ChatGPT in education: A systematic review. Computers, 12(8), 153. DOI: https://doi.org/10.3390/computers12080153

Nazir, A., & Wang, Z. (2023). A comprehensive survey of ChatGPT: advancements, applications, prospects, and challenges. Meta-radiology, 1(2), 100022. DOI: https://doi.org/10.1016/j.metrad.2023.100022

oJultNCHuAM&t=22s34nbq60

Ongena, G., van de Wijngaert, L., & Huizer, E. (2013). Acceptance of online audio-visual cultural heritage archive services: a study of the general public.

Ramírez-Correa, P. (2014). Uso de internet móvil en Chile: explorando los antecedentes de su aceptación a nivel individual. Ingeniare. Revista chilena de ingeniería, 22(4), 560-566. DOI: https://doi.org/10.4067/S0718-33052014000400011

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. DOI: https://doi.org/10.1016/j.iotcps.2023.04.003

Rubaceti, B., & Alida, N. (2021). La influencia social en el proceso de inclusión y bancarización fintech de usuarios emprendedores en Colombia a través del modelo de aceptación de tecnología Tam (Doctoral dissertation, Universidad Francisco de Paula Santander).

Sampieri, H., & Collado, R. F. (2010). C. y Baptista Lucio, P.(2010). Metodología de la investigación, 6.

Solano, A. V. C., Arboleda, L. D. C., García, C. C. C., & Dominguez, C. D. C. (2023). Benefits of artificial intelligence in companies. AG Managment, 1, 17-17. DOI: https://doi.org/10.62486/agma202317

Suárez-Escalona, R., Estrada-Domínguez, J. E., Infante-Alcántara, L. & Cavazos-Salazar, R. L. (2023). Análisis de la aceptación de una plataforma de enseñanza aprendizaje en la universidad. Formación universitaria, 16(1), 23-32. DOI: https://doi.org/10.4067/S0718-50062023000100023

Tong, Y. y Zhang, L. (2023). Descubriendo las tendencias de investigación en biología sintética de la próxima década. Biotecnología sintética y de sistemas, 8(2), 220–223.

UNESCO. (2019). Informe de los Objetivos de Desarrollo Sostenible. Recuperado de https://bit.ly/

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204. DOI: https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M., Davis, G., y Davis, F. (2003). User Acceptance of Information Technology: Towards a Unified View. MIS Quarterly, 27(3), 479–501. DOI: https://doi.org/10.2307/30036540

Wicaksono, A. R., Maulina, E., Rizal, M., & Purnomo, M. (2023). Technology Accepted Model (TAM): Applications in Accounting Systems. Journal of Law and Sustainable Development, 11(5), e547-e547. DOI: https://doi.org/10.55908/sdgs.v11i5.547

Zhang, P., & Tur, G. (2024). A systematic review of ChatGPT use in K‐12 education. European Journal of Education, 59(2), e12599. DOI: https://doi.org/10.1111/ejed.12599

Published

2025-05-30

How to Cite

Rodriguez-Amaya, D. K., & Estrada-Domínguez, J. E. (2025). Development of a measurement instrument for Acceptance of an artificial intelligence platform. Vinculategica Efan, 11(3), 179–193. https://doi.org/10.29105/vtga11.3-1141