HOW TO ANALYZE PARTICIPATION IN A (C) MOOC?
In the US, 2012 was called the year of the massive open online courses (MOOC). In Europe, this phenomena is just spreading out while in the US nearly 20 to 50 MOOCs start every month. While the definition of massive open online courses seems so easy on the first view – many different variations have developed in the last years.
The paper takes a look at each of the different parts of the definition of MOOCs in order to work out the different categories of this quite new phenomena. For instance, the massiveness of MOOCs might not only refer to the number of participants but also to the number of tools and content [Do13]. In terms of participants, open online courses are defined as MOOCs as soon as they have more than 150 participants – an amount which refers to the so called Dunbar number, an anthropologist who found that human beings can manage social relationships to up to a number of 150 peers [Du93]. Findings which are confirmed by actual studies on the usage of social media such as twitter [GPV11]. But actual results on MOOCs show rather high withdrawal rates, so researcher suggest to measure the number of participants in week two or three of a course not by amount of registrations since many learner are rather interested in getting access to the material than to really participate in the course. This leads to a second question: What means active participation in a MOOC? [Do13] even points out, that a large number of participants might even result in less active learners since a small group of active learners (called inner circle) might develop which then intimidates a large number of others who turn into lurkers.
In order to get a better insight into the behavior of learners, studiumdigitale developed a tool which helps to analyze the contribution of participants in the so called cMOOCs. These are MOOCs which are fostering the active participation of learners in various tools and which are based on the concept of connectivism [Si05]. In order to better understand the specific needs for analyzing tools of the different types of MOOCs, an overview will be given over the various MOOC types and categories before a deeper look will be taken into the analysis of two cMOOCs, OPCO11 and OPCO12 which took place 2011 and 2012 [Br12].
[Br12] Bremer, C.: Open Online Course als Kursformat? Konzept und Ergebnisse des Kurses “Zukunft des Lernens” 2011. In: G. Csanyi, F. Reichl, A. Steiner (Ed.): Digitale Medien Werkzeuge für exzellente Forschung und Lehre. Waxmann: Münster, p. 153-164, 2012.
[Do13] Downes, Stephen: What Makes a MOOC Massive? In: Half an Hour, 17.1.2013. Online: http://halfanhour.blogspot.ca/2013/01/what-makes-mooc-massive.html [17.1.13]
[Du93] Dunbar, R. I. M.: Coevolution of neocortical size, group size and language in humans. In: Behavioral and Brain Sciences. 16 (4), p. 681-735, 1993.
[GPV11] Goncalves, B.; Perra; N., Vespignani, A.: Validation of Dunbar’s number in Twitter conversations. PLoS ONE 6(8), (2011) Online: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0022656#s3 [3.1.13]
[Si05] Siemens, G.: Connectivism: A Learning Theory for the Digital Age. In: International Journal of Instructional Technology and Distance Learning, Vol. 2 No. 1, Jan 2005
Online: http://www.itdl.org/Journal/Jan_05/article01.htm [10.7.2012]