Analysis of academic performance based on sociograms: A case study with students from at risk groups

Abstract

The present work analyzes the academic performance of students from at-risk groups from the perspective of Social Network Analysis (SNA), studying the academic and interaction information of 45 students belonging to at-risk groups who attended a pilot socio-academic course during one academic term. This information was used to create a sociogram, which served as the basis for determining the centrality metrics of the SNA. The relationships between these metrics and the academic variables were then studied by means of correlation analysis and linear regression with LASSO standardization. As a preview of the results, it was determined that the academic performance of the students in the pilot course was influenced, on the one hand, by their academic knowledge prior to being admitted to the university, represented by the score on the Mathematics and Geometry section of the diagnostic test, and on the other hand, by the dynamics of the social network in which they interacted in the classroom, represented by the eigenvector centrality. These results have significant potential for explaining the academic performance according to SNA metrics, and they provide evidence to support the implementation of practices that promote a healthy social environment in an academic context.