Structural limitations of learning in a crowd: Communication vulnerability and information diffusion in MOOCs

Scientific Reports

Volumn 4, Issue , 2014, Pages

  Gillani, Nabeel ^a   Yasseri, Taha ^b   Eynon, Rebecca ^b   Hjorth, Isis ^b  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EDUCATION; HUMAN; INFORMATION DISSEMINATION; INTERNET; INTERPERSONAL COMMUNICATION; KNOWLEDGE; LEARNING; PEER GROUP; PROCEDURES;

COMMUNICATION; EDUCATION, DISTANCE; HUMANS; INFORMATION DISSEMINATION; INTERNET; KNOWLEDGE; LEARNING; PEER GROUP;

EID: 84923356212     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep06447     Document Type: Article

References (30)

1. Littlejohn, A. Understanding Massive Open Online Courses. CEMCA EdTech Notes (2013).
2. Stahl, G. K. T. & S. D. [Computer-supported collaborative learning: An historical perspective] Cambridge handbook of the learning sciences [Sawyer, R. K. (ed)] [409-426] (Cambridge University Press, Cambridge, 2006).
3. Vaquero, L. & Cebrian,M. The rich club phenomenon in the classroom. Sci. Rep. 3, 1174 (2013).
4. Ezekiel, E. J. Online education: MOOCs taken by educated few. Nature 503, 342 (2013).
5. Breslow, L. et al. Studying Learning In the Worldwide Classroom: Research into edX's First MOOC. Res. Practice Assess. 8, 13-25 (2013).
6. Kizilcec, R. F., Piece, C. & Schneider, E. Deconstructing Disengagement: Analyzing Learner Subpopulations in Massive Open Online Courses. Paper presented at Third International Conference on Learning Analytics and Knowledge: LAK '13, Leuven. New York: ACM (2013).
7. Yang, D., Sinha, T., Adamson, D. & Rose, C. P. "Turn on, Tune in, Drop out": Anticipating student dropouts in Massive Open Online Courses. Paper presented at Neural Information Processing Systems: Workshop on Data Driven Education, Tahoe, NV (2013).
8. Brinton, C. G. et al. Learning about social learning in MOOCs: From statistical analysis to generative model. arXiv:1312.2159v2 (2013).
9. Anderson, A., Huttenlocher, D., Kleinberg, J. & Leskovec, J. Engaging with Massive Open Online Courses. Paper presented at the 23rd International World Wide Web Conference: WWW '14, Seoul, Korea. New York: ACM (2014).
10. Vygotsky, L. Mind in Society (Harvard University Press, Cambridge, MA, 1978).
11. Siemens, G. Connectivism: A Learning for a Digital Age. Int. J. Instr. Tech. Distance Learn. 2, 3-10 (2005).
12. Colley, H., Hodkinson, P. & Malcolm, J. Non-formal learning: mapping the conceptual terrain. A consultation report. Leeds: University of Leeds Lifelong Learning Institute (2002).
13. Goodman, P. S. & Dabbish, L. A. Methodological Issues in Measuring Group Learning. Small Group Res. 42, 379-404 (2011).
14. Trognon,A.M.&Batt, M. [Group dynamics and learning] The Encyclopedia of the Sciences of Learning [Seel, N. M. (ed)] [1388-1391]. (Springer, US, 2012), pp. 1388-1391.
15. Tay, W. Y. Conceptualising learning in social and virtual worlds: an ethnography of three groups in Second Life. Doctoral Dissertation, Oxford University (2012).
16. Butler, B. S. Membership size, communication activity, and sustainability: A resource-based model of online social structures. Inf. Syst. Res. 12, 346-362 (2001).
17. Psorakis, I., Roberts, S. J., Rezek, I. & Sheldon, B. C. Inferring social network structure in ecological systems from spatio-temporal data streams. J. R. Soc. Interface 9, 3055-3066 (2012).
18. Li, M. X. et. al. Statistically Validated mobile communication networks: Evolution of motifs in European and Chinese data. arXiv:1403.3785 (2014).
19. Blondel, V. D., Guillaume, J. L., Lambiotte, R. & Lefebvre, E. Fast unfolding of communities in large networks. J. Stat. Mech. Theor. Exp. 10 (2008).
20. Albert, R., Jeong, H. & Barabasi, A. L. Error and attack tolerance of complex networks. Letters to Nature 406, 378-382 (2000).
21. Simonsen, I., Buzna, L., Peters, K., Bornholdt, S. & Helbing, D. Transient Dynamics Increasing Network Vulnerability to Cascading Failures. Phys. Rev. Lett. 100, 218701 (2008).
22. Kermack, W. O. & McKendrick, A. G. A Contribution to the Mathematical Theory of Epidemics. Roy. Soc. Lond. A. Matt. P. 115, 700-721 (1972).
23. Catanzaro, M., Bogulna, M. & Pastor-Satorras, R. Generation of uncorrelated random scale-free networks. Phys. Rev. E. 71, 027103 (2005).
24. Onella, J. P. et al. Structure and tie strengths in mobile communication networks. Proc. Natl. Acad. Sci. U.S.A 104, 7332-7336 (2007).
25. Gillani, N., Eynon, R., Osborne, M., Hjorth, I. & Roberts, S. J. Communication Communities in MOOCs. arxiv:1403.4640 (2014).
26. Anderson, R. M. & May, R. M. Infectious Diseases of Humans: Dynamics and Control (Oxford Science Publications, Oxford, 1992).
27. Karsai, M. M., Kivela, M., Pan, R. K., Kaski, K., Kertesz, J., Barabasi, A. L. & Saramaki, J. Small but slow world: How network topology and burstiness slow down spreading. Phys. Rev. E 83, 025102 (2011).
28. Newman, M. E. J. Modularity and community structure in networks. Proc. of the Nat. Acad. of Sciences 103, 8577-8582 (2006).
29. Lambiotte, R., Delvenne, J.-C. & Barahona, M. Laplacian Dynamics and Multiscale Modular Structure in Networks. arxiv:0812.1770 (2009).
30. Newman, M. E. J. Networks: an introduction (Oxford University Press, Oxford, 2010).