Impact of Information Technologies on Modeling the Interrelationships among Learning Factors

Abstract

This article offers a systematic review of studies related to different models derived from the establishment of relationships between factors involved in the learning process. It examines how information and communication technologies influence the development of these relationships and the construction of models. The PRISMA method was used to select articles from two databases, IEEE Xplore and SCOPUS, covering the period from 2018 to 2024. After applying the necessary filters, 20 articles were read and analyzed. These articles met specific criteria, including reporting research that aimed to establish relationships or correlations between elements or factors affecting the teaching-learning process or measuring the impact of certain educational aspects on the academic performance of university students. They also expressed these relationships through models. Twenty-five percent of the studies employed Artificial Intelligence algorithms to assess the influence of LMS, social networks, YouTube, and self-assessment on academic performance. It was found that compulsive use of social networks negatively impacts school performance. Conversely, automated assessment combined with effective communication with peers and teachers enables students to receive feedback, which encourages continued engagement in their studies.