….. A counter narrative of open online education
This is the title of a new paper, co-authored with Mariana Funes and published today in Learning Media and Technology, by Taylor & Francis Online.
Abstract
Open education aspires to democratize education, promote inclusion and effect change through social justice. These aspirations are difficult to realise in open, online environments, which enable multiple, and often conflicting, perspectives. This paper proposes a counter-narrative that surfaces certain operational norms of the internet and foregrounds their exclusionary nature. We offer an illustrative inventory of some social media interactional patterns to examine communication used in open online education communities. This examination leads us to conclude that language online is subject to a dialectical tension that both includes and excludes. We conclude that a different language is needed in open online educational environments; one that embraces exclusionary structures and strategic ambiguity, as well as the aspirations to further democratise education via digital means.
This paper is the culmination of 17 months’ work with Mariana and many long and wide ranging discussions. I have found the paper really interesting and thought-provoking to work on, and have particularly enjoyed collaborating with Mariana.
The final version of the paper is on the Learning, Media and Technology website – https://www.tandfonline.com/doi/full/10.1080/17439884.2018.1444638
But in line with Taylor and Francis’ Green Open Access policy (https://authorservices.taylorandfrancis.com/sharing-your-work/) we are able to post here the ‘preprint’, i.e. the final, accepted version of the paper, before being formatted by Learning, Media and Technology. This is virtually identical (bar the formatting and some tightening of reference citations) to the published article.
When Inclusion Excludes MF:JM 280218
We are very grateful to Stephen Downes, Lisa Lane and Carmen Tschofen for reviewing the paper for us before submission and making suggestions for improvement. We also thank the two anonymous reviewers for further detailed feedback, which helped us arrive at the final version.
We would welcome any comments or dialogue about the paper.
Jenny Connected 
Dear Jenny and Mariana,
I am not sure where to start with my reply to your article. First of all, it is a great article!
You do not simply set out to write a counter-narrative to dominant discourses within the field of open education, but you also explain how you go about this in a very detailed way. It is in your love for detail that I find most pleasure in your article. I agree with you that counter-narratives to existing discourses about inclusion and social justice in open education are overdue. In fact, I felt at the #OER17 conference that there are already many counter-narratives existing, but they tend to be touched on only very lightly and get smoothed over in the attempt to build a ‘community’.
For me, ‘community’ is the bone of contention that ‘open’ is in your article. An (the?) idea of ‘community’ seems to inform most (research) approaches to understand what happens in networked learning and learning in networks. In line with you, I also agree that more attention should be paid to what actually happens in networks, in particular in social media networks such as Twitter.
I prefer the term ‘network’ to the ideology-ridden term ‘community’, as I find that most authors who write about community soon refer to ‘communities of practice’ and quote Etienne Wenger (sometimes forgetting the earlier work with his co-author Jean Lave, which annoys me immensely). For me, focusing on networks instead of communities offers the opportunity to investigate how a network operates and to step away from the (all too) human element, that is but a part of the complex workings that operate in the act of tweeting, for example. I have not read Mejias (2013) yet, but what you write about his work echoes thoughts and concerns expressed by van Dijck and Poell (2013) in their article ‘Understanding Social Media Logic’ (Google provides a link to a pdf). In my own thesis I built on their ideas and thoughts expressed by Baym (2013, 2015) and others to develop my understanding of Twitter as a Deleuzo-Guattarian machine, which is intersecting and re-directing tweets and favours certain tweets over others.
Interestingly, the approach you take in your article to develop your counter-narratives is not far from my own methodological approach, which involved following the rhizomatic movements of tweets within and beyond Twitter. Based on my data analysis, I can relate to most of the patterns you developed in your ‘Inventory’ (Table 1 in your article), although occasionally I could offer yet other counter-narratives. For instance, I am not sure about the desire to become a central node (pattern “Fawning Adoration”). Apart from a different possible interpretation of the examples you provide, becoming a central node in a (Twitter) network does not rely entirely on human actions but also on the relational human and non-human workings of tweeting. Twitter algorithms certainly are part of this, but so are other elements in the situated activity of tweeting.
So much for today. Now I need to get back to my thesis, which I am going to submit this month. 😉
Best wishes
Martina
Thank you Martina for these comments and it is good to hear that you have an alternative perspective on some of the content. Different interpretations are of course always possible, and that was one of the points of writing the article in the first place. And yes of course Twitter algorithms must be a part of it.
It was interesting in writing the paper to know what to include and what to leave out. We did briefly discuss what is hidden in online participation and mentioned the potential for algorithms to promote the loudest voices, a finding we published in a previous paper – Participant association and emergent curriculum in a MOOC: Can the community be the curriculum? I recognise that it’s possible to say much more about this and look forward to reading your PhD, where I’m sure you must discuss this.
Your comment about communities and networks is interesting. You will know that Wenger et al. distinguish between communities and networks and I have heard Wenger say that all communities are networks but not all networks are communities. I agree with you that the idea of a community can be a problem in online networks. There can be a tendency to resort to group think and echo chambers. Stephen Downes, in the days of CCK08, used to discuss the differences between groups and networks and I think communities can have the characteristics of groups.
I haven’t read the van Dijck and Poell (2013) article, so I will look forward to that and although I have a couple of Baym articles in my library I don’t have the ones you mention, so I will look for those too.
I hope the rest of your PhD goes well and that you will successfully submit it this month. Jenny
Hi Jenny
Here are the references I mentioned above:
Baym, N. K. (2013). Data not seen: The uses and shortcomings of social media metrics. First Monday, 18(10). Retrieved from http://journals.uic.edu/ojs/index.php/fm/article/view/4873
Baym, N. K. (2015). Connect with your audience! The relational labor of connection. The Communication Review, 18(1), 14-22. Retrieved from http://nancybaym.com/BaymCommReview2015PrepubVersion.pdf
Many thanks Martina.