Ir al contenido

Documat


Understanding AI adoption in education: A tam perspective on students’ and teachers’ perceptions

  • Gabriel Marín Díaz [1] ; José Javier Galán Hernández [1] ; Raquel Gómez Medina [1] ; José Alberto Aijón Jiménez [1]
    1. [1] Universidad Europea de Madrid

      Universidad Europea de Madrid

      Madrid, España

  • Localización: Construyendo el futuro de la educación superior en la era digital / coord. por Eva Jiménez García; Paloma J. Velasco Quintana (aut.) Árbol académico, 2024, ISBN 978-84-1070-680-4, págs. 369-380
  • Idioma: inglés
  • Enlaces
  • Resumen
    • Over the past 30 years, we have experienced exponential growth. The advent of the Internet marked a significant shift in how we work and access information. We are now in a new phase, where the speed of information processing and storage capacity have prompted another exponential change.

      The arrival of new technologies such as mobile applications, Big Data, and artificial intelligence (AI) is transforming the university environment.

      These innovations aim to enhance the educational experience, optimize administrative processes, and support academic research. The effectiveness of these technologies depends on their acceptance by students and faculty, making it crucial to evaluate user adaptation. Despite extensive research on technology development, there is a lack of studies validating their impact and acceptance in academic settings. This research addresses this deficiency by presenting a new model based on the Technology Acceptance Model (TAM) tailored for university students and faculty. The study introduces an assessment system for digital maturity levels using a fuzzy 2-tuple linguistic model and the analytic hierarchy process (AHP). The results demonstrate a significant correlation between the use of AI and the enhancement of the academic experience in universities.

  • Referencias bibliográficas
    • Al-Qaysi, N., Mohamad-Nordin, N., & Al-Emran, M. (2020). Employing the technology acceptance model in social media: A systematic review....
    • Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model...
    • Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational...
    • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management...
    • Herrera, F., & Martínez, L. (2000). A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy...
    • Ikhsan, K. (2020). Technology Acceptance Model, Social Influence and Perceived Risk in Using Mobile Applications: Empirical Evidence in Online...
    • Lin, Y., & Yu, Z. (2023). Extending Technology Acceptance Model to higher-education students’ use of digital academic reading tools on...
    • Marín Díaz, G., Galdón Salvador, J. L., & Galán Hernández, J. J. (2023). Smart Cities and Citizen Adoption: Exploring Tourist Digital...
    • UNESCO. (2023). Digital learning and transformation of education. https://www.unesco. org/en/digital-education
    • Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions Subject Areas: Design Characteristics,...
    • Wang, Y., Yu, L., & Yu, Z. (2022). An extended CCtalk technology acceptance model in EFL education. Education and Information Technologies,...

Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno