
AbstractThe widespread use of computing and communications technologies has enabled the popularity of social networks oriented to learn. In this work, we study the nature and strength of associations between students using an online social network embedded in a learning management system. With datasets from three offerings of the same course, we mined the sequences of questions and answers posted by the students to identify structural properties of the social graph, patterns of collaboration among students and factors influencing the final academic achievements. The results show some hints to understand how users react to incentives in online social learning systems, useful for instance to measure the effectiveness of the learning tasks based on the patterns of students’ participation in the platform and adapt their design, or as early predictors of academic performance.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
