Learning Analytics to Identify the Socio-affective Scenarios in a Virtual Learning Environment

Abstract

A growing number of virtual courses are being offered by Brazilian educational institutions, requiring the development of technological resources and research to assist in Distance Education (DE) teaching and learning processes. Analysis of students’ socio-affective profiles in Virtual Learning Environments (VLE) enables possibilities to develop methodologies and resources to better understand them. The Social Map (SM) and Affective Map (AM), both features of the Cooperative Learning Network (in Portuguese: ROODA), provide inferences and graphic presentations of students’ socio-affective profiles. This article aims to identify the possible recurrent socio-affective scenarios in a VLE utilizing Learning Analytics (LA). LA is defined as the measurement, collection, and analysis of data. The qualitative and quantitative research approach used in this work was carried out based on 10 case studies. The target audience was 219 students including undergraduate, graduate, teachers, and elderly people who participated in teaching activities at a university. Data collected from the SM and AM were extracted in order to identify the relationship between these two aspects. As a result, 38 socio-affective scenarios were created using LA to contribute to the analysis of the students’ learning profiles, allowing teachers to develop pedagogical strategies consistent with the needs of each individual.