# Gamifying Massive Online Courses: Effects on the Social Networks and Course Completion Rates
## 5 Discussion and Conclusions  
Regarding the influence of gamification in the structure of the social network (RQ1), we observe substantially more connections in the experimental group and many nodes with a large number of connections. This suggests a redistribution in the flow of communication among students that widens and changes the patterns of participation as previously reported [32], but that in this study is found in a massive online course. We also see that the social network of the gamified group presents the structural characteristics such as low density and short average paths that are also common in networks that involve human social interactions [48]. Descriptive statistics of the structural properties of the networks then suggest that there are differences between the treatment and comparison groups. However, we can also observe that the proportion of nodes with at least one connection is still small for each group (39% for comparison and 59% for treatment) and that the number of students that complete the course is a very small proportion, as is common in MOOCs. This suggests that a substantial number of students do not participate. The results of the PCA show that F1 includes most variables for both groups, suggesting that F1 is a good representation of students' work on the platform and students' position and influence in the network. Personal activity and structural centrality in the educational social-network are correlated, as also shown in previous studies about social networking sites [49]. We also note that the variability explained by the first component (F1) is higher for the experimental group. This suggests that the gamification features and the two variables included to measure it (points and achievements) contribute to explaining the students' work, providing a better statistical description of the gamified group. To analyze the relationship between gamification and course completion (RQ2), we investigated the difference in overall success probability (the probability of getting a certificate) in both groups and found that probability increased from 3.28% in the comparison group to 5.25% in the treatment group. We further investigated the relationship between gamification and course completion by building a mathematical model to describe completion as a function of the amount of work, characterized as a function of the factor scores of F1 obtained from the PCA. The results suggest that F1 is a good predictor of the probability of completing the course for both groups. A closer examination of the models highlights the differences among groups. For students who engaged heavily, the probability of getting a certificate increased to almost 70% in the experimental group, while it was around 35% in the control group. This suggests that, besides the effect of gamification in participation and the structure of the network, gamification may also impact on learning success. Previous studies point to  
Figure 7: The plot of Certificate probability vs. F1 with the linear fit for the control group with a sample size of the probability estimate \(n=21\). correlations between social networking and learning success [29] and between gamification-driven social networking and learning success [38; 50], which our study confirms in a large-scale course. We also show that F1, in addition to being a good representation of a student's work and position in the network, is a reliable estimator of the probability of success. Future work can community detection to further analyze the relationships between learning communities and their impact on course completion [51]. Our study has several limitations. First, it is essential to note that the causal relationship between the effect of social networking and gamification in learning performance is not proven. It may be that if students carry out the activities that increase the scores in the variables mentioned above, they will improve their chances of getting a certificate.