La integración de recursos y actividades apoyados en la tecnología en los planes de estudio universitarios requiere una reestructuración de los programas de enseñanza. Para lograr un efecto sinérgico, los métodos convencionales deben ser sustituidos por enfoques de aprendizaje activo que ofrezcan a los estudiantes formas innovadoras, motivadoras y colaborativas de construir conocimiento, adaptadas a la sociedad contemporánea. La realidad virtual (VR) se encuentra entre las innovaciones tecnológicas llamadas a transformar la educación en entornos de aprendizaje interactivos e inmersivos. Este artículo analiza si la integración de la VR en los cursos universitarios puede, en opinión de los estudiantes, aumentar su interés por una comprensión más profunda de fenómenos complejos y si esto podría traducirse en un mayor compromiso y en una mejora en el logro de los resultados de aprendizaje. Los desafíos de implementar este tipo de diseño instruccional se examinan a partir de un análisis de las respuestas de estudiantes de grado y máster de la Universidad Tecnológica de Gdansk (Gdańsk Tech), recogidas en junio y julio de 2025.

Perceived usefulness (PU) is one of the most important determinants for the acceptance of technologies as it strongly influences both the intention to use and the actual use of the technology. As large language models (LLMs), such as ChatGPT, are increasingly used in higher education, it is important to understand what factors influence students’ perceptions of the usefulness of LLMs for academic learning. Based on the Technology Acceptance Model (TAM), this study investigated the role of relevance to academic learning, perceived enjoyment, and perceived ease of use (PEOU) on students’ perceptions of the usefulness of LLMs. The study involved 102 students from a Croatian university. The data were analyzed using Spearman correlation and multivariate regression analysis. The correlation analysis showed that all three factors had a statistically significant positive correlation with the perceived usefulness of LLMs. However, the regression analysis showed that only relevance to academic learning and perceived enjoyment of using LLMs for learning were significant positive predictors, while perceived ease of use played a minor role. Together, these two variables explained 71.8% of the variance in students’ perceptions of the usefulness of LLMs. The results emphasize the importance of identifying the factors that shape students’ perceptions of the usefulness of LLMs as they are an important predictor of intention to use the technology. The findings suggest that there is a need to develop LLM-based tools that are pedagogically relevant and engaging for students and that can serve as guidelines for their successful integration into higher education.