Abstract
This paper aims to explore the use of common learning analytics methods, such as activity metrics and network analytics, in order to study and analyse the activity of users and the communication flow in discussion forums that serve Massive Open Online Courses (MOOCS). We particularly seek to identify trends and patterns that may potentially be used to support the communication and information exchange between MOOCs participants. To that end, we applied existing metrics and methods on the log files of a discussion forum that supported participants’ communication for a Coursera MOOC. We present the methodology of the study as well as the results and findings with respect to knowledge exchange and information flow in the case of a massive online course.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kay, J., Reimann, P., Diebold, E., Kummerfeld, B.: MOOCs: so many learners, so much potential. IEEE Intell. Syst. 28, 70–77 (2013)
Gillani, N., Yasseri, T., Eynon, R., Hjorth, I.: Structural limitations of learning in a crowd: communication vulnerability and information diffusion in MOOCs. Sci. Rep. 4, (2014)
Siemens, G., Long, P.: Penetrating the fog: analytics in learning and education. Educ. Rev. 46, 30 (2011)
Mayer, M.: Innovation at Google: the physics of data. In: PARC Forum (2009)
Voyiatzaki, E., Avouris, N.: Support for the teacher in technology-enhanced collaborative classroom. Educ. Inf. Technol. 19, 129–154 (2014)
Hoppe, H.U., Engler, J., Weinbrenner, S.: The impact of structural characteristics of concept maps on automatic quality measurement. In: International Conference of the Learning Sciences (ICLS 2012), Sydney, Australia (2012)
Chounta, I.-A., Hecking, T., Hoppe, H.U., Avouris, N.: Two make a network: using graphs to assess the quality of collaboration of dyads. In: Baloian, N., Burstein, F., Ogata, H., Santoro, F., Zurita, G. (eds.) CRIWG 2014. LNCS, vol. 8658, pp. 53–66. Springer, Heidelberg (2014)
Zhang, J., Ackerman, M.S., Adamic, L.: Expertise networks in online communities: structure and algorithms. In: Proceedings of the 16th international conference on World Wide Web. pp. 221–230. ACM (2007)
Clow, D.: MOOCs and the funnel of participation. In: Proceedings of the Third International Conference on Learning Analytics and Knowledge. pp. 185–189. ACM (2013)
Wong, J.-S., Pursel, B., Divinsky, A., Jansen, B.J.: An Analysis of MOOC Discussion Forum Interactions from the Most Active Users. In: Agarwal, N., Xu, K., Osgood, N. (eds.) SBP 2015. LNCS, vol. 9021, pp. 452–457. Springer, Heidelberg (2015)
Rossi, L.A., Gnawali, O.: Language Independent Analysis and Classification of Discussion Threads in Coursera MOOC Forums
Kim, S.N., Wang, L., Baldwin, T.: Tagging and linking web forum posts. In: Proceedings of the Fourteenth Conference on Computational Natural Language Learning, pp. 192–202. Association for Computational Linguistics (2010)
Stump, G.S., DeBoer, J., Whittinghill, J., Breslow, L.: Development of a framework to classify MOOC discussion forum posts: methodology and challenges. In: NIPS Workshop on Data Driven Education (2013)
Hoppe, H.U., Göhnert, T., Steinert, L., Charles, C.: A web-based tool for communication flow analysis of online chats. Networks 11, 39–63 (2014)
Harrer, A., Hever, R., Ziebarth, S.: Empowering researchers to detect interaction patterns in e-collaboration. Front. Artif. Intell. Appl. 158, 503 (2007)
Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. ACM JACM. 46, 604–632 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Chounta, IA., Hecking, T., Hoppe, H.U. (2015). Every Answer Has a Question: Exploring Communication and Knowledge Exchange in MOOCs Through Learning Analytics. In: Baloian, N., Zorian, Y., Taslakian, P., Shoukouryan, S. (eds) Collaboration and Technology. CRIWG 2015. Lecture Notes in Computer Science(), vol 9334. Springer, Cham. https://doi.org/10.1007/978-3-319-22747-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-22747-4_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22746-7
Online ISBN: 978-3-319-22747-4
eBook Packages: Computer ScienceComputer Science (R0)