Exploring attitudes toward chatGPT among college students: An empirical analysis of cognitive, affective, and behavioral components using path analysis

• Autores: Huamaní Jordan, Olger, Acosta-Enriquez, Benicio Gonzalo, Arbulú P´erez Vargas, Carmen Graciela, Arbulú Ballesteros, Marco Agustín, Paredes Morales, Ana Elizabeth
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad Tecnológica del Perú
• Repositorio: UTP-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.utp.edu.pe:20.500.12867/14504
• Enlace del recurso: https://hdl.handle.net/20.500.12867/14504; https://doi.org/10.1016/j.caeai.2024.100320
• Nivel de acceso: acceso abierto
• Materia: ChatGPT; University students; Cognitive component; Behavioral component; https://purl.org/pe-repo/ocde/ford#2.11.04

The advent of generative artificial intelligence (AI) applications, such as ChatGPT, has significantly impacted various aspects of human life, including higher education. This study explores university students’ attitudes toward ChatGPT, focusing on the cognitive, affective, and behavioral components of attitudes, on the basis of Mitcham’s philosophical framework of attitudes toward technology. A total of 595 university students from six public and private universities in northern Peru participated in an online survey. The results of the structural equation modeling (SEM) analysis revealed that the affective component (β = 0.672***) and the cognitive component (β = 0.260**) positively influence the behavioral component of students’ attitudes when ChatGPT is used. Moreover, the cognitive component (β = 0.931***) positively influences the affective component of students’ attitudes. However, gender and age did not have significant moderating effects on the relationships between the cognitive and affective components and the behavioral component. The discussion highlights that these findings contribute to understanding the psychological mechanisms underlying the adoption of ChatGPT in educational settings and offer valuable guidance for implementing this technology in teaching and learning processes. In conclusion, this study represents a significant advancement in comprehending attitudes toward generative AI technologies in higher education and opens new avenues for future research in this field.