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Pass the Idea Please: The Relationship between Network Position, Direct Engagement, and Course Performance in MOOCs

Published:12 April 2017Publication History

ABSTRACT

Extant research suggests that learner engagement in discussion forums is positively correlated with learner performance. In this paper we investigate which types of forum engagement are most strongly associated with final performance in MOOC courses. In particular, we compare the correlation between course final grade and two types of learner engagement: direct measures, which count the number of interactions, and indirect measures, which capture learners position in a social network. We found that direct measures have stronger correlations with final grade. However, in preliminary analyses, we also found that course instructors score higher than learners on some indirect measures. We discuss the implications of these findings and our plans for developing the work further in the future.

References

  1. Bettencourt, L. M., Cintrón-Arias, A., Kaiser, D. I., and Castillo-Chávez, C. The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models. Physica A: Statistical Mechanics and its Applications 364 (2006), 513--536. Google ScholarGoogle ScholarCross RefCross Ref
  2. Cho, H., Gay, G., Davidson, B., and Ingraffea, A. Social networks, communication styles, and learning performance in a cscl community. Computers & Education 49, 2 (2007), 309--329. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Dowell, N. M., Skrypnyk, O., Joksimovic, S., Graesser, A. C., Dawson, S., Ga\vsevic, D., Hennis, T. A., de Vries, P., and Kovanovic, V. Modeling learners' social centrality and performance through language and discourse. International Educational Data Mining Society (2015).Google ScholarGoogle Scholar
  4. Gasevic, D., Kovanovic, V., Joksimovic, S., and Siemens, G. Where is research on massive open online courses headed? a data analysis of the mooc research initiative. The International Review of Research in Open and Distributed Learning 15, 5 (2014). Google ScholarGoogle ScholarCross RefCross Ref
  5. Ga\vsević, D., Zouaq, A., and Janzen, R. Choose your classmates, your gpa is at stake!: The association of cross-class social ties and academic performance. American Behavioral Scientist (2013), 0002764213479362.Google ScholarGoogle Scholar
  6. Gillani, N., and Eynon, R. Communication patterns in massively open online courses. The Internet and Higher Education 23 (2014), 18--26. Google ScholarGoogle ScholarCross RefCross Ref
  7. Gillani, N., Yasseri, T., Eynon, R., and Hjorth, I. Structural limitations of learning in a crowd: communication vulnerability and information diffusion in MOOCs. Scientific reports 4 (2014), 6447. Google ScholarGoogle ScholarCross RefCross Ref
  8. Jiang, S., Fitzhugh, S. M., and Warschauer, M. Social positioning and performance in moocs. In Workshop on Graph-Based Educational Data Mining (2014), 14.Google ScholarGoogle Scholar
  9. Laat, M., Lally, V., Lipponen, L., and Simons, R.-J. Investigating patterns of interaction in networked learning and computer-supported collaborative learning: A role for Social Network Analysis. International Journal of Computer-Supported Collaborative Learning 2, 1 (2007), 87--103. Google ScholarGoogle ScholarCross RefCross Ref
  10. Martınez, A., Dimitriadis, Y., Rubia, B., Gómez, E., and De La Fuente, P. Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers & Education 41, 4 (2003), 353--368. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Nekovee, M., Moreno, Y., Bianconi, G., and Marsili, M. Theory of rumour spreading in complex social networks. Physica A: Statistical Mechanics and its Applications 374, 1 (2007), 457--470. Google ScholarGoogle ScholarCross RefCross Ref
  12. Poquet, O., and Dawson, S. Analysis of MOOC Forum Participation. In Australasian Society for Computers in Learning and Tertiary Education (2015), 224--234.Google ScholarGoogle Scholar
  13. Romero, C., López, M.-I., Luna, J.-M., and Ventura, S. Predicting students' final performance from participation in on-line discussion forums. Computers & Education 68 (2013), 458--472. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Thomas, M. J. Learning within incoherent structures: The space of online discussion forums. Journal of Computer Assisted Learning 18, 3 (2002), 351--366. Google ScholarGoogle ScholarCross RefCross Ref
  15. Trusov, M., Bucklin, R. E., and Pauwels, K. Effects of word-of-mouth versus traditional marketing: findings from an internet social networking site. Journal of marketing 73, 5 (2009), 90--102. Google ScholarGoogle ScholarCross RefCross Ref
  16. Yang, D., Sinha, T., Adamson, D., and Rosé, C. P. Turn on, tune in, drop out: Anticipating student dropouts in massive open online courses. In Proceedings of the 2013 NIPS Data-driven education workshop, vol. 11 (2013), 14.Google ScholarGoogle Scholar

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  1. Pass the Idea Please: The Relationship between Network Position, Direct Engagement, and Course Performance in MOOCs

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    • Published in

      cover image ACM Conferences
      L@S '17: Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale
      April 2017
      352 pages
      ISBN:9781450344500
      DOI:10.1145/3051457

      Copyright © 2017 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 12 April 2017

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      L@S '17 Paper Acceptance Rate14of105submissions,13%Overall Acceptance Rate117of440submissions,27%

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