ZML Didaktik / Innovative Learning Scenarios

Reflecting the SNA14-MOOC on Coursera using a footprint of emergence

Posted on: December 26, 2014

Before Christmas I got the message that I successfully completed the Social Network Analysis course of Lada Adamic, Univ Michigan on Coursera. So it’s time to discuss my footprint of SNA14.

The course was a typical Coursera MOOC with videos, articles, weekly homeworks and an exam of 2 hours at the end. I discussed the SNA14-MOOC in a previous post. About 2 weeks after I finalized the MOOC I created a footprint of my learning experience asking myself how prescribed or open I experienced the learning process in the SNA14-MOOC.

footprint of emergence consists of four clusters. In the „open/structure“ cluster I’m looking at the learning experience from a certain distance, in the cluster „interactive environment“ I’m discussing how learning took place in the MOOC, and how emergent learning was supported by the framework. The cluster „agency“ challenges me to discuss my own learning development and in the cluster „presence/writing“ I’m reflecting how it was possible to bring myself into the SNA14-MOOC.

Reflecting the Social Network Analysis MOOC

A first view at the footprint tells me that I like it. The footprint has open parts – in the clusters openness/structure and agency – whereas especially in the cluster learning environment more prescribed values of the factors prevail.

This is how I evaluated my learning experience in the SNA14-MOOC:

Cluster Open/structure

  • I valued the factors risk, liminality and ambiguity rather highly. There were too many different topics to learn for me and I felt a high risk to drop out. The contents were very rich, there were the models of SNA themselves but furthermore a lot of reading material in the fields of biology, sociology, food, commerce, … and I needed my mathematical background to understand the theory, – therefore my high value for the liminality factor. And what and how to proceed in the SNA14-MOOC was ambivalent with regard to the use of data in simulations who didn’t work accurately, with ambivalent homework questions, with no clear hints how to learn for the final exam. Also the factor self-correction has a high value as I had to develop my learning strategy during the SNA14-MOOC and I was changing my learning strategy for several times.
  • The values of the factors in the cluster „Interactive environment“ were mostly near or in the prescribed zone. I didn’t experience that the Coursera environment was flexible, that the system adapted to us learners or that there was the possibility of co-evolution. Nevertheless there had to be a large trust towards us learners that we will proceed successfully in our learning processes.
  • In the cluster „agency“ with regard to the factors  self organization“ and „autonomy“ I was on the edge of chaos. For me it was a big challenge to include learning in the SNA14-MOOC into my every day business also because I needed more time than the recommended 6-8 hours per week. Furthermore until then I didn’t have a strategy how to learn via videos and I don’t like videos for learning. So I had to overcome my feelings and develop a new approach (in the end I wrote an extensive script). On the other hand in this MOOC I didn’t have possibilities to negotiate the outcomes or to adopt different identities.
  • I was challenged by solitude and contemplation in the cluster „presence/writing“ as I felt alone and missed the community (my values for FIN-frequent interact and networking and Net-network encounters were very low as well).

Summarizing my footprint I’m astonished about it. As the SNA14-MOOC was a classical xMOOC with a strict pedagogical approach I expected a footprint with factors mainly in the prescribed zone whereas my footprint is a rather open one. In my process of creating footprints of emergence at the moment I believe that the footprints depend much more on the person who created it than the learning environment. And in the Social Network Analysis course – a closed xMOOC – I succeeded to learn in an open way.

But what about analyzing footprints to get feedback about the learning design if they mainly depend on the learners ??

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