Study of the impact of social learning and gamification methodologies on learning results in higher education

In this study, as the last step of a longitudinal study of the impact of social learning and gamification methodologies on learning results in higher education, we have recorded the activity in a software platform based on Moodie, specially built for encouraging online participation of the students to design, carry out and evaluate a set of learning tasks and games, during two consecutive editions of an undergraduate course. Our aim is to confirm the relationships between the patterns of accomplishment of the gamified activities and the network structure of the social graphs associated with the online forums with knowledge acquisition and final outcomes. For this purpose, we have offered two learning paths, traditional and novel, to our students. We have identified course variables that quantitatively explain the improvements reported when using the innovative methodologies integrated into the course design, and we have applied techniques from the social network analysis (SNA) and the machine learning/deep learning (ML/DL) domains to conduct success/failure classification methods finding that, generally, very good results are obtained when an ensemble approach is used, that is, when we blend the predictions made by different classifiers. The proposed methodology can be used over reduced datasets and variable time windows for having early estimates that allow pedagogical interventions. Finally, we have applied other statistical tests to our datasets, that confirm the influence of the learning path on learning results.