Abstract

Personal networks for modeling relationships among a group of individuals have been widely used in the social sciences, especially in Sociology. Nevertheless, this type of approach covers other areas of scientific knowledge. In the case of education, for example, the use of personal networks can serve as a basis for the mapping of the relational field that involves a particular individual, considering their different educational spaces. In this sense, it is assumed that the use of personal networks can serve as a methodological tool for the identification of the relational fields that permeate a student’s school performance during their schooling. Therefore, the objective of this work is to analyze the relationship between personal networks and school performance with students of the High School Series of the Santos Dumont State School, located in the municipality of Parnamirim, Rio Grande do Norte, Brazil. In order to reach this goal, the methodology adopted consisted of five specific procedures: 1) A literature review on personal networks and school performance, with emphasis on the concepts of density (degree of network connectivity) and the number of clicks (clustering of nodes, from three or more actors who maintain links between them.); 2) Application of a questionnaire to collect the data of personal networks, through which the students mentioned the name of 45 people they knew; the degree of proximity and the type of relationship they had with each of the 45 people mentioned; 3) Calculation of density values and number of clicks (network indicators); 4) Obtaining the notes of Portuguese and Mathematics of the students; and 5) Application of the logistic regression model to identify the likely relationships between the personal network and the school performance of each student investigated. The results obtained showed that students with very dense networks tend to take low grades in Portuguese, while students with networks that have many clicks show a certain tendency to take low grades in Mathematics.

Keywords: Education; personal networks; school performance