Recommendation Systems in Education: A review of Recommendation Mechanisms in E-learning Environments

• Published in: Revista ingenierías (Medellín, Colombia) Vol. 20; no. 38; pp. 147 - 158
• Main Authors: Otero Cano, Paola Andrea, Pedraza Alarcón, Edgar Camilo
• Format: Journal Article
• Language: English; Portuguese
• Published: Universidad de Medellín 01-06-2021
• Subjects: ENGINEERING, MULTIDISCIPLINARY; MOOC; education; e-learning; learning styles; environments; educación; aprendizaje de máquina; entornos; estilos de aprendizaje; machine learning; aprendizaje virtual
• ISSN: 1692-3324; 2248-4094; 2248-4094
• DOI: 10.22395/rium.v20n38a9

In recent years, new trends and methodologies have emerged that greatly favor the education sector. E-learning as an alternative to regular teaching and learning processes has transformed the educational dynamics thanks to the inclusion of MOOCs, personal learning environments, allowing the educational process to be carried out at a personalized level where the focus is on learning styles and the profile of the student. This article presents a review of current works around machine learning mechanisms to make recommendations in the educational environment, where it is found that besides the discovery of the student’s learning style, it is important to know their level of knowledge and learning speed, in addition to the tools used by the student to carry out their studies. Finally, the opportunity for implementation and research of these issues in Colombia is highlighted.