Chatgpt In Higher Education: Structural Relationships between the Compatibility of Learning Styles, Perceived Usefulness and Continued Use Intention

The integration of generative artificial intelligence (AI) tools, such as ChatGPT, is transforming learning dynamics in higher education. In this context, the aim of the present study was to analyze the structural relationships between the compatibility of ChatGPT with learning styles, ease of use and perceived usefulness (EUPU), and continued use intention among teacher-training university students and to explore possible gender-based variations. The research was developed via a quantitative approach, with a nonexperimental, cross-sectional and correlational-explanatory design. University students were selected for participation by nonprobabilistic convenience sampling, and data collection was performed using a structured questionnaire. A structural equation model (SEM) was used for data analysis. The results revealed that compatibility with learning styles positively and significantly predicted EUPU. Similarly, EUPU significantly predicted continued use intention. However, the direct path from CLS to continued use intention was positive but not statistically significant, suggesting that the influence of compatibility operates mainly through EUPU. The exploratory multigroup analysis showed small descriptive variations by gender, which should be interpreted with caution. These findings indicate that students have a greater predisposition to continue using ChatGPT when they perceive that the tool adapts to their learning needs, is simple to use and provides concrete academic benefits. In addition, the potential of ChatGPT to support information search, resolve doubts and promote autonomous learning was identified. ChatGPT has important use potential in higher education contexts.