ORIGINAL RESEARCH article
Front. Educ.
Sec. Higher Education
Volume 10 - 2025 | doi: 10.3389/feduc.2025.1649034
This article is part of the Research TopicReimagining Higher Education: Responding Proactively to 21st Century Global ShiftsView all 3 articles
Sociodemographic Predictors and Usability Perceptions Explaining Academic Use Intention of ChatGPT Among University Students in Ecuador
Provisionally accepted
EDGAR ROLANDO MORALES-CALUÑA1,2*
Dario Javier Cervantes Diaz3Cristian Ismael Morales Caluña4Fernando Xavier Altamirano Capelo5- 1Faculty of Health Sciences, State University of Milagro, Milagro, Ecuador
- 2Universidad Estatal de Milagro, Milagro, Ecuador
- 3Faculty of Social Sciences, Business Education and Law, State University of Milagro, Milagro, Ecuador
- 4Technical University of Ambato, Information Technology Department, Ambato, Ecuador
- 5Faculty of Public Health, Chimborazo Polytechnic School, Riobamba, Ecuador
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Background: The rapid integration of artificial intelligence (AI) in higher education has transformed how students interact with academic content. ChatGPT, as a prominent AI-based language model, has been increasingly adopted by students to support learning tasks. However, the factors influencing its academic use intention remain underexplored in Latin American contexts. Objective: This study aims to identify the sociodemographic and perceptual predictors that explain the academic use intention of ChatGPT among university students in Ecuador. Methods: A cross-sectional, analytical study was conducted with 210 students from seven Ecuadorian universities. Data were collected through a validated questionnaire encompassing six constructs: compatibility with students' learning styles, efficiency, perceived ease of use, perceived usefulness, satisfaction, and intention of continued use. Descriptive statistics, exploratory factor analysis, binary logistic regression, and k-means clustering were performed using Python in Google Colab. Results: The logistic regression model revealed that perceived usefulness (OR = 2.37) and compatibility with learning style (OR = 1.87) were the most significant predictors of high academic use intention. Cluster analysis identified three user profiles: enthusiastic adopters, neutral users, and reluctant adopters. Sociodemographic factors showed limited predictive power. Conclusions: Students' perceptions of the academic value and alignment of ChatGPT with their learning preferences are stronger predictors of usage intention than sociodemographic characteristics. These findings highlight the need for pedagogically aligned and inclusive AI integration strategies in higher education.
Keywords: ChatGPT, higher education, technology acceptance, usability, university students
Received: 18 Jun 2025; Accepted: 21 Jul 2025.
Copyright: © 2025 ROLANDO MORALES-CALUÑA, Cervantes Diaz, Morales Caluña and Altamirano Capelo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: EDGAR ROLANDO MORALES-CALUÑA, Faculty of Health Sciences, State University of Milagro, Milagro, Ecuador
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