The aim of this article is to identify the socio-affective aspects of higher education students in a Virtual Learning Environment (VLE) during the process of preparing Digital Educational Materials (DEM). DEM is understood in this work as the construction of materials by students, using tools with free versions available on the internet. The inference of socio-affective aspects in VLEs is one of the possibilities for developing methodologies, materials or resources that make it possible to understand the profile of students in higher education. In this context, the Affective Map and the Social Map, tools belonging to the VLE Cooperative Learning Network (abbreviated in Portuguese: ROODA), enable the analysis and graphical presentation of students' affective and social profiles. The Affective Map shows the moods (animated, discouraged, satisfied, dissatisfied and undefined affective) of the students involved in a course. The Social Map illustrates the exchanges established in the VLE in the form of sociograms and has seven indicators (absence, collaboration, distance from the class, drop out, informal groups, popularity and undefined social). Socio-affective Scenarios were then inferred, which are the intersection of moods and social indicators. These aspects make it possible to monitor student learning during the development of DEMs. The research methodology was developed using a qualitative case study approach. The target audience was 16 undergraduate students who took part in two face-to-face subjects at a public university in Brazil. Data was collected through the students' Socio-affective Scenarios, while they were taking the subjects and preparing the DEMs. As a result, 27 Socio-affective Scenarios were identified, with the highest number of times for: undefined affective and collaboration (n=78); satisfied and collaboration (n=33) and animated and collaboration (n=26). In addition, seven DEMs were developed and made available for use by other teachers. Therefore, based on socio-affective aspects, the teacher can personalize the teaching-learning process for each student or for the whole class.

Keywords: Moods, social indicators, Distance Education, Virtual Learning Environment, Digital Educational Materials.