# ABS-SOCI: An Agent-Based Simulator of Student Sociograms
## 2 Background  
Sociograms graphically represent the social relations among individuals. Sociograms can analyze several kinds of relations, such as selections and rejections. Selection relations can be obtained by asking for example \"Who would you choose as a workmate?\", while rejection relations can be obtained with questions such as \"Who would you avoid to work with?\" Sociograms [8] have proven to be especially useful for analyzing group dynamics, performing comparisons between groups, and studying the repercussion of the moderator (or instructor) technique. Several works associated the analysis of social networks with the group performance. For instance, [PERSON] [9] presented a detailed analysis of the different network structures and their relation with the team performance. The results of a league of soccer teams were used as experimental basis to measure the performance, and this was compared with the known measures of network structures such as network intensity (passes per minute) and network centralization. Furthermore, the work of [PERSON] and [PERSON] [10] not only related the network with the performance, but also increased the performance based on the network. In particular, this work presented a tool-supported technique for improving academic performance of students being aware of social networks through the analysis of sociograms. In online formative assessments, their system recommended students with low results to strengthen their social connections and academically collaborate with their closest peers. Their study showed that their system improved academic performance. However, none of these works allowed practitioners to simulate the evolution of these sociograms through time in a realistic way so that some possible sociogram structures could be forecasted given certain students with certain profiles. There are different ways of analyzing sociograms. In particular, sociometrics are useful for performing this analysis. For instance, [PERSON] and [PERSON] [11] proposed a metric for measuring subgroup insularity or segregation, in order to quantify the separation between subgroups. In addition, [PERSON] and [PERSON] [12] proposed a software application that measured a wide range of sociometrics in sociograms. They proposed sociometrics that measured (a) different factors of the social status of each individual as well as (b) group properties such as cohesion and dissociation. The current approach used some of these metrics for measuring the simulation outcomes. Several works have used sociograms in education. For example, [PERSON] (2005) extracted sociograms from a group of students to analyze the influence of the teacher when encouraging student interaction. She performed their analysis in the nursing education, and she analyzed the activity roles of student. She provided some hints about how to encourage student interaction from her experience. In addition, [PERSON] et al. [PERSON] et al. (2013) used the sociograms for analyzing the interpersonal relations of young students in sport lessons. Their goal was to promote cooperation skills among children in order to evoke positive attitude towards learning and avoiding negative emotions in isolated ones. The current work shares some of the goals with these works, and its innovation is the proposal of a simulator tool for predicting sociograms of students beforehand. Moreover, some works have studied the influence of grouping in education. For example, [PERSON] et al. [PERSON] et al. (2014) performed a study in a large city in China, and showed how the low academic-level students increased their performance when they were included in heterogeneous academic-level groups. Furthermore, [PERSON] et al. [PERSON] et al. (2015) applied a Genetic Algorithm (GA) to group partners based on the analysis of a social network, considering sociometrics for assessing the social statuses of students. They applied the GA to optimize the grouping satisfying certain constraints related to the diversity of grades, social status and genders.