# ABS-SOCI: An Agent-Based Simulator of Student Sociograms
## 4 Experimentation  
The current approach has been evaluated with several scenarios related to groups of students. These scenarios were extracted from both (a) external works reported in [5; 12; 30] and (b) an experiment of one of the current authors in a Programming Course in the University of Zaragoza. The simulations have been tested starting from both (1) initial sociograms with only neutral relations (in the scenarios from the external works); and (2) an initial existing sociogram where people already knew each other and there were different kinds of relations (in the Programming Course scenario). The current approach has been evaluated in both online education [30] and face-to-face education (in the other scenarios). The goal of the scenarios extracted from the literature was to assess the prediction capability of the ABS-SOCI tool. In these scenarios, ABS-SOCI could have been used for estimating potential students in risk of isolation and the possible group cohesion in order to reinforce the courses with collaborative activities. In the experiment of the Programming Course, ABS-SOCI was actually used to estimate the cohesion of the group and the social structures represented as sociograms. The teacher added some collaborative exercises in his teaching schedule in order to reinforce collaboration among students and ameliorate the potential isolation cases. Firstly, ABS-SOCI has been calibrated with two real sociogram cases, which are the ones presented in the work of [PERSON] and [PERSON] [12] and the work of [PERSON] [5]. These sociograms are different in terms of sample size, and some constants and matrix values have been adjusted to obtain similar results. This calibration of constants and matrix values has been performed following the White Box Calibration method proposed by [PERSON] et al. [31]. According to this calibration method, the current approach determines their main influence of these internal values in the simulation results. In particular, this approach considers the direct influence of the Suitable matrix on (1) the selection relations between individuals of certain types and on (2) the cohesion sociometric in general. It also considers the opposite influence of the Unsuitable matrix in these two aspects. It takes into account the influence of the Change matrix and the \(CST_{T}REND\) value in the evolution of sociometrics for a specific number  
Figure 7: Dataflow diagram for updating the relationships according to their trends. of iterations. Finally, it adjusts the \(CST\_COHEREENCE\) value considering its repercussion in the coherence sociometric. This calibration phase can also be considered as a training phase. Table 1 determines these internal constant values depending on the sample size after this calibration phase. As an example, Figure 8 visually shows the values of Suitable and Unsuitable matrices for the large groups (i.e., size \(\geq\)9) after the calibration phase. All of these values were the results of the calibration phase, and were used as the setting of the simulator for running the next simulations. After the calibration, ABS-SOCI was run and validated with the new scenario introduced by [PERSON] [30], besides the aforementioned works. There were 100 executions for each case for obtaining a representative set of results. Table 2 presents the input parameters of the scenarios of these experiments and the remaining ones. The number of iterations was 50 representing 50 h of teaching activities in all of the scenarios except one. The number of iterations from the first three scenarios correspond to the common number of teaching hours of these subjects in the corresponding academic level and countries reported by the original sources. In particular, the subjects belonged to either higher education or university education, from either Spain or United Kingdom.