A social learning network (SLN) is a type of social network that results from interaction between learners, teachers, and modules of learning.[1] The modules and actors who form the SLN are defined by the specific social learning process taking place.[2]

The set of learners and the set of teachers in an SLN cannot be disjoint. Rather, an SLN is an evolving peer learning process in which learners acquire, master, and then themselves disseminate knowledge to others over time. At any given time, an actor in an SLN is a teacher of concepts she has mastered, and a learner of those she is not yet familiar with.

Collaborative learning has been identified as an important part of SLN formation, because actors can work together and combine their respective skills to solve problems.[3]

Applications

A number of learning scenarios that give rise to social learning networks have been identified. Some of these have a designated teacher and/or teaching staff, while others rely entirely on peer-based instruction:

Graph types

The structure and dynamics of a social learning network can be represented through a graph. Different combinations of node types and link/weight definitions will yield different properties about the network. Dynamic functionalities on top of these graphs, meaning how they evolve over time in terms of the number of nodes, links, and weights, can be captured too.

At least four graph types have been identified:[1]

See also

References

  1. ^ a b Brinton, Christopher G., and Mung Chiang. "Social learning networks: A brief survey." Information Sciences and Systems (CISS), 2014 48th Annual Conference on. IEEE, 2014.
  2. ^ Haythornthwaite, Caroline, and Maarten De Laat. "Social networks and learning networks: Using social network perspectives to understand social learning." 7th International Conference on Networked Learning. 2010.
  3. ^ Huang, Jeff JS, et al. "Social Learning Networks: Build Mobile Learning Networks Based on Collaborative Services." Educational Technology & Society 13.3 (2010): 78-92.
  4. ^ Christopher Brinton, Mung Chiang, Shaili Jain, Henry Lam, Zhenming Liu, and Felix Ming Fai Wong. "Learning about social learning in moocs: From statistical analysis to generative model." arXiv preprint arXiv:1312.2159 (2013).
  5. ^ Glance, David George, Martin Forsey, and Myles Riley. "The pedagogical foundations of massive open online courses." First Monday 18.5 (2013).
  6. ^ Herreid, Clyde Freeman, and Nancy A. Schiller. "Case studies and the flipped classroom." Journal of College Science Teaching 42.5 (2013): 62-66.
  7. ^ DiMicco, Joan, et al. "Motivations for social networking at work." Proceedings of the 2008 ACM conference on Computer supported cooperative work. ACM, 2008.
  8. ^ Anderson, Ashton, et al. "Discovering value from community activity on focused question answering sites: a case study of stack overflow." Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2012.
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