Characterizing Super-Posters in a MOOC for Teachers’ Professional Development

Authors

DOI:

https://doi.org/10.24059/olj.v22i4.1503

Keywords:

MOOCs for Teachers, Participation Inequality in Forums, Super-posters, High Active Participants in MOOCs, Most Active Users, MOOC Forums, Qualitative Research

Abstract

Massive Open Online Courses (MOOCs) attract thousands of participants who each exercise autonomy by engaging with resources and with other participants to whatever degree they wish. When analyzing participants’ patterns of engagement in MOOCs it is possible to notice that certain participants exhibit high levels of participation, actively engaging with others in forums. This study focuses on characterizing these highly active participants, and understanding their contributions back to the network in a MOOC designed for teachers’ professional development. Connectivism is used as theoretical lens to describe super-posters’ engagement in forums. Data from participants’ demographics, click-data, and forum posts are used to identify these highly active users. Qualitative content analysis is used to categorize the content of their posts, and social network analysis is used to represent their patterns of engagement. Results show that super-posters are generators of engagement, repurposing the content learned from the MOOC and feeding-forward new resources to the network. Super-posters can be seen as representatives of participation inequality in forums. They position themselves as the most prestigious and most influential nodes in the networks created by participants as they engage in forums. In some networks super-posters served as bridges, connecting people from different discussion threads and helping information to flow through the network. This study provides to MOOC designers and MOOC instructors an affordable method to identify and classify super-posters in any MOOC. Findings of this study could be used by MOOC designers and MOOC instructors to develop pedagogical interventions to give these participants a special role in the next MOOC cohort, which may foster engagement in MOOC forums and nurture the cyclical process of learning described in Connectivism. Regarding implications for research, this study attends the need for qualitative methods when analyzing participants’ engagement in MOOC forums and contributes to our knowledge of participation inequality. It also extends the literature of super-posters by showing their characterization in a MOOC focused on teachers’ professional development.

Author Biography

Fernanda Cesar Bonafini, The Pennsylvania State University

Fernanda Bonafini earned a Ph.D. in Curriculum and Instruction (Mathematics Education), a Masters degree in mathematics education from São Paulo State University, and a Masters degree in Applied Statistics from Penn State University. She studies Massive Open Online Courses for teachers, online professional development for teachers, and teaching and learning with technology in both face-to-face and online environments.

References

Anderson, A., Huttenlocher, D., Kleinberg, J., & Leskovec, J. (2014). Engaging with massive online courses. In C. W. Chung et al. (Ed.), 23rd International Conference on World Wide Web (WWW '14), (pp. 687–698). Seoul, Korea

Bonafini, F. (2017). The effects of participants’ engagement with videos and forums in a MOOC for teachers’ professional development. Open Praxis, 9(4), 433-447. doi: http://dx.doi.org/10.5944/openpraxis.9.4.637

Bonafini, F. C., Chae, C., Park, E., & Jablokow, K. W. (2017). How much does student engagement with videos and forums in a MOOC affect their achievement? Online Learning, 21(4), 223-240. doi: 10.24059/olj.v21i4.1270

Bozkurt, A. & Aydın, C. H. (2015). Satisfaction, Preferences and Problems of a MOOC Participants. In Proceedings of The Association for Educational Communications and Technology (AECT) 2015 International Convention, (pp. 35-41). 3-7 November 2015, Indianapolis, Indiana, USA

Breslow, L., Pritchard, D. E., Deboer, J., Stump, G. S., Ho, A. D. & Seaton, D. T. (2013). Studying learning in the worldwide classroom research into edX’s first MOOC. Research & Practice in Assessment, 8 (1), 13-25.

Coetzee, D., Fox, A., Hearst, M. A., & Hartmann, B. (2014). Should your MOOC forum use a reputation system? In Proceeding of the 17th ACM conference on Computer Supported Cooperative Work & social computing CSCW 2014 (pp. 1176–1187). New York: ACM Press.

Cormier, D., & Siemens, G. (2010). The open course: Through the open door–open courses as research, learning, and engagement. Educause Review Online, 45(4), 30–32.

Dey, P., & Roy, S. (2016). Social Network Analysis. In: Meghanathan N. (Eds.). Advanced Methods for Complex Network Analysis. Hershey, PA: IGI Global. p. 237-265

de Waard, I., Abajian, S. C., Gallagher, M. S., Hogue, R. J., Keskin, N. O., Koutropoulos, A., & Rodriguez, C. O. (2011). Using mLearning and MOOCs to understand chaos, emergence, and complexity in education. The International Review of Research in Open and Distance Learning, 12(7), 94-115. Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1046/2026

Dubosson, M., & Emad, S. (2015). The Forum Community, the Connectivist Element of an xMOOC. Universal Journal of Educational Research, 3(10), 680-690. DOI: 10.13189/ujer.2015.031004

Everetta, M. G., & Valente, T. M. (2016). Bridging, brokerage and betweenness. Social Networks, 44, 202–208. doi: 10.1016/j.socnet.2015.09.001

Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software – Practice and Experience, 21, 1129–1164. Retrieved from http://www.mathe2.uni-bayreuth.de/axel/papers/reingold:graph_drawing_by_force_directed_placement.pdf

Gao, F. (2014). Exploring the Use of Discussion Strategies and Labels in Asynchronous Online Discussion. Online Learning, 18(3). doi:http://dx.doi.org/10.24059/olj.v18i3.460

Goldberg, L. R., Bell, E., King, C., O'Mara, C., McInerney, F., Robinson, A., et al. (2015). Relationship between participants’ level of education and engagement in their completion of the understanding dementia Massive Open Online Course. BMC medical Education, 15(1), 60. doi:10.1186/s12909-015-0344-z.

Haklay, M. (2016). Why is participation inequality important? In C. Capineri, M. Haklay, H. Huang, V. Antoniou, J. Kettunen, F. Ostermann & R. Purves (Eds.), European handbook of crowdsourced geographic information. London: Ubiquity Press.

Hansen, D., Smith, M. (2015). How to use NodeXL. In J. Golbeck (Ed.), Introduction to Social Media Investigation (pp. 237-253). Watham, MA: Elsevier Science.

Hsieh, H. & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative Health Research, 15(9), 1277-1288. doi: 10.1177/1049732305276687.

Hollands, F., & Tirthali, D. (2014). MOOCs e expectations and reality. Retrieved from: http://www.academicpartnerships.com/sites/default/files/MOOCs_Expectations_and_Reality.pdf.

Huang, J., Dasgupta, A., Ghosh, A., Manning, J., & Sanders, M. (2014). Superposter behavior in MOOC forums. In Proceedings of the First ACM Conference on Learning@Scale (L@S). doi:10.1145/2556325.2566249

Lang, Q. C. (2010). Analysing high school students’ participation and interaction in an asynchronous online project-based learning environment. Australasian Journal of Educational Technology, 26(3), 327-340.

Ke, F. & Xie, K. (2009). Online Discussion Design on Adult Students’ Learning Perceptions and Patterns of Online Interaction. In C. O'Malley, D. Suthers, P. Reimann, A. Dimitracopoulou (Eds.), Proceedings of the International Conference of Computer-Supported Collaborative Learning, 1 (pp. 219-226). Rhodes, Greece. Island of Rhodes: International Society of the Learning Sciences.

Kellogg, S., Booth, S., & Oliver, K. (2014). A social network perspective on peer supported learning in MOOCs for educators. International Review of Research in Open and Distributed Learning, 15 (5).

Kizilcec, R. F., Piech, C., & Schneider, E. (2013). Deconstructing disengagement: analyzing learner subpopulations in massive open online courses. In Proceeding of the third international conference on Learning Analytics and Knowledge (pp. 170-179). New York: ACM. Retrieved from http://web.stanford.edu/~cpiech/bio/papers/deconstructingDisengagement.pdf

Kleinman, G., Wolf, M. & Frye, D. (2013). The digital learning transition MOOC for educators: exploring a scalable approach to professional development, [online]. Retrieved from http://all4ed.org/reports-factsheets/the-digital-learning-transition-mooc-for-educators-exploring-a-scalable-approach-to-professional-development/

Kop, R., & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past? The International Review of Research in Open and Distance Learning, 9(3).

Mackness, J., Mak, S. F. J., & Williams, R. (2010). The ideals and reality of participating in a MOOC. In Proceedings of the 7th International Conference on Networked Learning. (Eds.) Dirckinck-Holmfeld L, Hodgson V, Jones C, de Laat M, McConnell D & Ryberg T. (pp. 266-274). Aarlborg. Retrieved from http://www.lancs.ac.uk/fss/organisations/netlc/past/nlc2010/abstracts/Mackness.html

Mayring, P. (2000). Qualitative Content Analysis. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 1(2). Retrieved from http://www.qualitative-research.net/index.php/fqs/article/view/1089/2385

Nielsen, J. (2006). Participation inequality: Encouraging more users to contribute. Jakob Nielsen’s alertbox, 9. Retrieved from https://www.nngroup.com/articles/participation-inequality/

Otte, E., & Rousseau, R. (2002). Social network analysis: a powerful strategy, also for the information sciences. Journal of Information Science, 28(6), 441 – 453. https://doi.org/10.1177/016555150202800601

Ruberg, L. F., Moore, D. M. & Taylor, C. D. (1996). Student participation, interaction, and regulation in a computer-mediated communication environment: a qualitative study. Journal of Educational Computing Research, 14 (3), 243-268.

Russo, T. C., & Koesten, J. (2005). Prestige, Centrality, and Learning: A Social Network Analysis of an Online Class. Communication Education, 54(3), 254-261.

Siemens, G. (2004). Connectivism: A learning theory for the digital age. Elearnspace (2004). Retrieved from http://www.elearnspace.org/Articles/connectivism.htm

Siemens, G., & Downes, S. (2011, January). What is Connectivism? [Web log comment]. Retrieved from http://cck11.mooc.ca/how.htm

Soliman, M., Nasraoui, O., & Cooper, N. G. F. (2016). Analysis and visualization of a literature-mined glaucoma gene interaction network. Paper presented at IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Francisco, CA, pp. 669-676.

doi: 10.1109/ASONAM.2016.7752309

Thomas, D. R. (2006). A General Inductive Approach for Analyzing Qualitative Evaluation Data. American Journal of Evaluation, 27(2), 237-246. DOI: 10.1177/1098214005283748

Wong, J.-S., Pursel, B., Divinsky, A., & Jansen, B. J. (2015). An analysis of MOOC discussion forum interactions from the most active users. In N. Agarwal, K. Xu, & N. Osgood (Eds.), Social Computing, Behavioral-Cultural Modeling, and Prediction (pp. 452–457). Switzerland: Springer International Publishing. http://doi.org/10.1007/978-3- 319-16268-3_58

Young, J. R. (2012). Providers of Free MOOC’s Now Charge Employers for Access to Student Data. Chronicle of Higher Education. Retrieved from http://chronicle.com/article/ProvidersofFreeMOOCsNow/136117/.

Downloads

Published

2019-01-25

Issue

Section

Special Conference Issue: AERA Online Teaching and Learning SIG