## 4 Results
### Study 2: Is It Possible to Identify Study Groups in a Classroom?
#### 4.2.1 Types of Behaviour  
This section contrasts the authors' results (final score, mark generated by the teacher in a non-automatic way) in relation to their behaviour category. Figure 7 plots the results for each course per author, with the final score on the \(x\)-axis and the mutual average intensity value on the \(y\)-axis. The boundaries of the different categories (on the \(y\)-axis, from bottom to top) \(\{\text{Q}_{\text{individuals}},\text{Q}_{\text{soft}},\text{Q}_{\text{hard}}\}\) and \(\text{Q}_{\text{cheat}}\)) are marked with a red line. From the observation of the graphs, we can highlight that the best marks were obtained for the academic year 2017-2018, while for the rest of the academic years, the best marks were between 7 and 8. In general, it can be underlined that most of the authors were in the soft range (values on the \(y\)-axis between 0.5 and 1.5) including those who obtained the best marks. This result shows that most of the authors had an honest collaborative behaviour. In the case of the top scorers, we can observe a different behaviour in their collaboration patterns for each year, which we study in more detail in Section 4.3. In Figure 7, the vertices with high knowledge transfer relationships (\(\text{Q}_{\text{hard}}\) and \(\text{Q}_{\text{cheat}}\)) were concentrated in authors with very low academic performance, with the authors in the \(\text{Q}_{\text{cheat}}\) category practically at 0, i.e., these authors \"absorb\" the results of the exercises developed by other authors without contributing any knowledge. This indicated that they did not acquire any knowledge in the development of the subject and, in some cases, substituted the effort of studying and following up on the subject with dishonest behaviour. It is precisely on the \(\text{Q}_{\text{hard}}\) vs. \(\text{Q}_{\text{cheat}}\) borderline that we placed the dishonest behaviour practised by authors in the \(\text{Q}_{\text{cheat}}\) category. Figure 7: \(Cont\). Another interesting result is that the regression of the data showed a slight linear trend with very low explanatory power of the variability (\(R^{2}\)), which even in the 2016-2017 academic year means that the regression parameters were not significantly different from 0. We now look at the relationships among authors resulting from the accumulation of similarities with the documents generated by their classmates. The relationships were considered according to the values in Table 1 (_Similar_cod_). If there was more than one relationship (i.e., similarity was higher than 1 in more than one document), the values were added, obtaining the \"_mutual aggregate intensity_\". In addition, we recorded the number of documents in which there was some similarity in the categories considered, and we obtained the attribute \"documents number\". Taking into account both attributes, we calculated the value of the attribute \"_mutual average intensities_\". The summary by academic year of the metrics for the different behaviours is shown in Table 4.  
In this social network, there was a group of authors whose practical work had a very low similarity with their peers, i.e., those in the \"Individuals\" category (Qindividuals). These were authors who effectively carried out their practical work individually. They are not represented in the graph. The others were grouped together and were studied separately. In these study groups, there were subgroups of authors who, among themselves, had stronger relationships with some peers and weaker relationships with the rest. The analysis of these results is given in the next section. Figure 7: Global view of authors’ behaviour and final score; \(x\). _final score_, \(y\). _average intensity_ (_behaviour_). Horizontal red lines separate the four classes of _behaviour categories_ {Qindividual, Qsoft, Qhard, Qcheal}. This social map was built for each course, given that the practical assignments were different from course to course, so that authors cannot copy from students from previous years.