Digital Twins in Higher Education: Applications, Challenges, and Future Perspectives

The Fourth Industrial Revolution has introduced emerging technologies that are reshaping educational models, among them digital twins, originally developed in the aerospace industry as virtual representations of real systems. Their integration into higher education now enables the simulation of complex learning environments, monitoring of student performance, and personalization of learning processes. However, their adoption within university settings remains incipient, fragmented, and lacking in standardization, which limits their transformative potential. This situation underscores the need to systematize dispersed knowledge on their educational use. This study presents a review with a descriptive and exploratory approach, based on peer-reviewed scientific articles selected from databases such as Scopus, IEEE Xplore, ScienceDirect, SpringerLink, and Web of Science, published between 2018 and 2024. The findings indicate that digital twins are primarily applied for simulations (68%), learning monitoring (52%), and educational personalization (44%). Reported outcomes highlight improvements not only in learner autonomy, motivation, and acquisition of practical skills, but also in conceptual understanding, problem-solving abilities, and collaboration among students in project-based environments. At the institutional level, benefits include greater efficiency in resource management, reduction of physical laboratory costs, and continuity of teaching in hybrid or remote learning contexts. Nevertheless, challenges remain, including limited connectivity, high implementation costs, insufficient teacher training, and ethical risks. Digital twins represent a strategic technology for transforming higher education into more flexible, personalized, and sustainable models, provided they are supported by inclusive policies and adequate investment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.