Academic Performance Prediction in Universities using Ensemble Algorithms: A Literature Review

One of the main challenges faced by higher education institutions is offering services with quality that are influenced by different variables such as the academic performance of their students. Due to the complexity and variety of factors that affect this parameter, national and international research projects have been carried out to analyze said factors including the intrinsic characteristics of students and external elements related to the environment and social relationships. This document details a literature review regarding machine learning techniques, particularly ensemble algorithms, for the early prediction of academic performance. The discussed factors are classified into academic, socio-demographic, psychosocial and online learning, and the most commonly used ensemble algorithms in academic performance prediction are identified.