Integrating learning styles and popularity in learning objects recommendations

Abstract

This paper proposes a knowledge management strategy in the educational context, emphasizing the integration of Learning Styles (LS) and the Popularity of Learning Objects (LO) in Recommender Systems. Considering that specific characteristics of LO can influence students' learning processes, given their varied LS, this study aims to analyze the incorporation of these styles to enhance LO recommendations. Given the widespread availability of LO in various repositories, this work presents a hybrid model that personalizes recommendations, taking into account not only students' LS but also the popularity of LO in the educational environment. An experiment conducted with 55 students and involving 25 variations of LO highlighted the model's utility, outperforming traditional recommendation approaches.