Name
Abstract | ||
|---|---|---|
In the last few years, social learning, i.e., learning based on the analysis and discussion of topics by means of social collaborative systems, mainly social network services such as Facebook or Twitter, has acquired a great importance and led many instructors and institutions to deploy courses that include activities to be performed in them. For effective learning, both teachers and learners are required to gain insight into how the interaction takes place and how the learning process evolves over the time. Given that the nature of this kind of learning is inherently social, the Social Network Analysis (SNA) theory is perfectly suitable for this purpose. Therefore, this paper proposes the use of sociograms, SNA representations, to answer many of the questions that both learners and teachers need to know to make the best decisions and act accordingly. Furthermore, several network settings are suggested and the interpretation of the most relevant centrality measures when applied to online social learning is provided. Finally, the usefulness of sociograms is shown by means of the analysis of the activity performed in a MOOC course hosted in OpenMOOC platform. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s10758-019-09416-7 | Technology, Knowledge and Learning |
Keywords | Field | DocType |
Social network analysis, Social learning analytics, Graph mining, Social learning | Data science,Social network,Social learning analytics,Collaboration,Computer science,Social network analysis,Centrality,Need to know,Social learning,Sociogram | Journal |
Volume | Issue | ISSN |
24 | 4 | 2211-1662 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marta E. Zorrilla | 1 | 51 | 16.05 |
| Mariana de Lima Silva | 2 | 0 | 0.34 |