Application of Learning Analytics in Virtual Tutoring: Moving toward a Model Based on Interventions and Learning Performance Analysis

Abstract

The research area related to the use of Learning Analytics and the prediction of student performance is multidimensional; therefore, it can be explored and analyzed through different perspectives. This research addresses the relationship between pedagogical interventions based on Learning Analytics and student learning performance. The research problem of predicting student performance can be analyzed from various angles. This study presents an analysis based on the technique of Path Analysis (PA) and proposes a model based on the following variables: Mediation, Motivation, Communication, Learning Design, and Learning Performance. The study’s findings demonstrate the importance of the role of virtual tutors in carrying out pedagogical interventions thanks to the information retrieved from the Learning Analytics tools and its appropriate analysis.