Factors Influencing Satisfaction and Continued Use Intention of ChatGPT in the Academic Context: Analysis Using Structural Equation Modeling

Edgar Rolando Morales Caluña, Dario Javier Cervantes Diaz, Cristian Ismael Morales Caluña and Fernando Xavier Altamirano Capelo

Data and Metadata, 2025, vol. 4, 728

Abstract: Artificial intelligence tools like ChatGPT have transformed higher education by facilitating academic tasks and improving autonomous learning. However, their acceptance and continued use depend on factors such as compatibility, efficiency, satisfaction, and intention to use. This study applies Structural Equation Modeling (SEM) to evaluate these relationships. To analyze how these factors influence user satisfaction and continued use intentions of ChatGPT among university students. Study involved 210 students from Ecuadorian universities. Validated surveys were used to assess six constructs: compatibility, efficiency, perceived ease of use, perceived usefulness, satisfaction, and continued use intention. Data were analyzed using Exploratory and Confirmatory Factor Analysis, followed by SEM for model adjustment. The findings identified a four-factor structure explaining 63% of the variance. Fit indices were acceptable (CFI = 0.876, SRMR = 0.064), with significant factor loadings (p

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:4:y:2025:i::p:728:id:1056294dm2025728

DOI: 10.56294/dm2025728

Access Statistics for this article

More articles in Data and Metadata from AG Editor
Bibliographic data for series maintained by Javier Gonzalez-Argote ().