Personalized Learning: an Adaptive Approach Based on the VARK Model to Improve Distance Education

Abstract

Objective: This research designs a virtual course that adapts to different learning styles according to the VARK model and evaluates students' academic performance and satisfaction. Additionally, it provides an educational environment that optimizes learning through personalization. Theoretical Framework: This study is based on the VARK model, which classifies learning styles, allowing a better understanding of students' information processing. The research also reviews theories on distance education and adaptive learning. Method: A mixed-method approach is employed, using surveys and interviews to collect data on students' learning experiences before and after the course implementation. Results are analyzed using statistical tools and content analysis. Results and Discussion: The results show that students who participated in the adaptive course exhibited a significant improvement in academic performance and satisfaction levels. Differences in the effectiveness of teaching strategies were observed based on the predominant learning style. These findings suggest that personalization in education can have a positive impact on learning. Research Implications: This research is relevant for curriculum design and teacher training, as it promotes the inclusion of adaptive approaches in higher education. Educational institutions are encouraged to consider diverse learning styles when implementing virtual courses to maximize student potential. Originality/Value: This study provides an innovative approach to using the VARK model in virtual education, highlighting the importance of tailoring learning to students' individual needs. Its originality lies in the practical implementation of this model, which can serve as a reference for future research and educational developments.