Innovating Personalized Learning in Virtual Education Through AI - Luis Fletscher; Jhon Mercado; Alvaro Gómez; Carlos Mendoza-Cardenas (Multimodal Technologies and Interaction, 2025)
The rapid expansion of virtual education has highlighted both its opportunities and limitations. Conventional virtual learning environments tend to lack flexibility, often applying standardized methods that do not account for individual learning differences. In contrast, Artificial Intelligence (AI) empowers the creation of customized educational experiences that address specific student needs. Such personalization is essential to mitigate educational inequalities, particularly in areas with limited infrastructure, scarce access to trained educators, and varying levels of digital literacy. This study explores the role of AI in advancing virtual education, with particular emphasis on supporting differentiated learning. It begins by selecting an appropriate pedagogical model to guide personalization strategies and proceeds to investigate the application of AI techniques across three key areas: the characterization of educational resources, the detection of learning styles, and the recommendation of tailored content. The primary contribution of this research is the development of a scalable framework that can be adapted to a variety of educational contexts, with the goal of enhancing the effectiveness and personalization of virtual learning environments through AI.