Category Archives: work

Creating Living Knowledge: the Connected Communities programme and what it tells us about university-community partnership

These are my notes from a Digital Education Seminar at the University of Edinburgh by Professor Keri Facer on the Connected Communities research programme.

As ever with these posts, my record is partial and bias and possibly includes some inaccuracies (but not on purpose). 

The seminar was opened by Prof Sian Bayne to introduce Keri as Professor of Educational and Social Futures at Bristol University and was previously Research Director at FutureLab. Her research takes a critical stance on digital education and on the role of educational institutions in society. Today she’ll be talking about her work onConnected Communities and the newly released Creating Living Knowledge report on lessons learnt from the Connected Communities programme.
Keri Facer:
The main questions that will be explored today include: what is Connected Communities and what is shaping university-community partnership, what they are creating and the implications for the future trajectories of universities and their interface with their communities?
CC is a research council UK programme led by AHRC and currently funds 324 different projects. Projects range from 6 months to five years and involving working with external organisations from creative economy, environment, health and well-being etc…
The bigger picture of the programme is to address question of how university and community knowledge be combined to generate better research. Underpinned by the assumption that co-produced research is a ‘good thing’. The RCs are making huge claims on the potential for the co-production mode of research in terms of research quality and impact while others are concerned that this agenda is concerned with the instrumentalisation and marketisation of research.
CC enters a massively uneven playing field between large institutions through to voluntary community activists, freelancers, community organisations, etc. The HE sector is also very diversified between research/ teaching intensive interacting with socio-cultural diversity. Also, CC works with a wide diversity of motivation for engaging with research: generalists and learners engaged by interdisciplinary research; makers wanting to make something happen; scholars with a particular topic orientation; entrepreneurs interested in funding available; accidental wanderers caught up in projects; advocates for new knowledge landscape arguing for a rethink of how knowledge is generated.
The are also different research traditions in:
– participatory, collaborative, community engaged research developing grass-roots capacity
– development traditions – changing policy
– people’s history, feminist and civil rights interested in alternative narratives of history
– innovative co-design changing services and products
– open/ crowd and open innovation creating something new
– participatory arts where unsettling and exploration is the purpose.
These different traditions mobilise different performances of community and ‘publicness’. Also involving different participants and audiences and different working practices. Again, these shape the landscape of collab
Social networks and funding. Raises questions of access to social networks and how and where conversations happen. Over 50% of partners had already worked inside universities. So other possible partners face a barrier to entry to these collaborative opportunities while intensive workshops can discriminate with caring responsibilities.
So the injunction to co-produced research can reproduce and intensify existing inequalities.
Important to acknowledge that the cultures of universities can be very diverse and not only a culture of critique, e.g., engineers want to make stuff
Different groups want different things from one another: from practical help, personal value and friendships and symbolic benefits e.g., of offering authenticity and credibility and status. Everyone has to negotiate the ‘fantasy’ of the university and the community. Beyond the quick gains between partners leads to difficult questions around, e.g., the legitimacy of knowledge production or the representativeness of community groups.
Different modes of collaboration emerge:
  1. division of labour – keep to our own silos
  2. relational expertise – can we see the issue through each others eyes
  3. remake identities – about learning each others skills and knowledge so we can take on each others’ roles.
  4. colonisation – unsettled identities but no learning. Academics attempting community work or community groups attempting research data collection.
Where works well, collaboration leads to the breakdown of division and new roles are mobilised such as catalysers; integrators; designers; broker; facilitator; project managers; data gatherers; diplomats (makes things work in and between institutions); accountants; conscience; nurturer; loudhailer.
This requires time to develop trust; understand each others’ expertise, etc. so that these projects can do a different sort of work where  “The adventure of thought meets the adventure of action” (A.N Whitehead)
While their is strong legacy from these collaborations, this legacy is precarious due to key staff being junior staff and in precarious employment. This is linked to the funding environment. Short-term project funding can disturb the work of small organisations as well as disturb personal relationships. Also, the funding requires working with HEI systems that are not fit for working with smaller and precarious partner organisations. These negative effects are exacerbated by trends in HE towards marketisation
We cannot state whether such projects will democratise knowledge production as that depends on many other variables. Similarly, the idea that co-production leads to better research – well, its another set of methods but collaboration can, if done mindfully, lead to better quality research in terms of needs of all of those involved.
Recommendations from the research (from the report):
  1. improve the infrastructure
  2. recognise the need for time for collaboration
  3. explicitly address the risk of enhancing inequalities
  4. invest in and support civic society’s public learning infrastructure.

Digital Badges

Initial sketch for structure of Digital Badges

Initial sketch for structure of Digital Badges

I’m currently working on an open content course – the learner proposes the learning activities, the evidence they will gather and how they will demonstrate that they have met the agreed learning outcomes. It is pretty interesting stuff and opens up huge opportunities for experimenting on learning and education. To help in keeping students on track in the course, we are looking at developing a couple of sets of process-based digital badges and this is an early sketch of the possible structure of the badges.

IT Futures at Edinburgh

I’m attending the IT Futures conference at Edinburgh today. These notes are not intended to be a comprehensive record of the conference but to highlight points of interest to me and so will be subjective and partial.

A full recoding of the conference will be available at the IT Futures website

The conference opens with an address from the Principal, Sir Timothy O’Shea with an opening perspective:

Points to the strengths of the University in computing research, super-computing and so on, and ‘ludicrously’ strong in e-learning with 60 plus online postgraduate programmes. In these areas, our main competitors are in the US rather than the UK.

Beginning with a history of computing from the 19402 onwards. Points to Smallwood and using computers to self-improving teaching and Papert on computing/ e-learning for self-expression. 1980s/90s digital education was dominated by the OU. 1990s the rise of online collaborative learning was an unexpected development that addressed the criticisms that e-learning (computer assisted learning) lacked interactive/ personalisation elements.

2000 saw the rise of OERs and MOOCs as a form of providing learning structure around OERs. Also noted the success of OLPC in Uruguay as one of the few countries to effectively implement OLPC.

Argues that the expansion of digital education has been pushed by technological change rather than pedagogical innovation. We still refer to the constructivism of Vygotsky while technology innovation has been massive.

How big is a MOOC?
– 100 MOOCs is about the equivalent in study hours of a BA Hons. A MOOC is made up of a 1000 minnows (I think this means small units of learning. MOOCs are good for access as tasters and to test e-learning propositions. They also contribute to the development of other learning initiatives, enhance the institutional reputations including relevance through ‘real-time MOOCs’ such as on the Scottish referendum. MOOCs provide a resource for learning analytics.

So e-learning is mature, not new, and blended learning is ‘the new normal’ and dominated by the leading university brands of MIT, Stanford, etc. A huge contribution of e-learning is access.

A research agenda: to include modelling individual learning, including predictive learning support; speed of feedback; effective visualisation; supporting collaboration; understanding Natural Language; location of the hybrid boundary (eg, in practical tests); personal programming (coding) and how realistic is it for meaningful coding skills for the non-geeks to  be developed.

Open questions are around data integrity and ownership; issues of digital curation; integration of data sources; who owns the analysis; should all researchers be programmers?; and how to implement the concept of the learner as researcher?


Question about artificial intelligence: Answer – Tim O’Shea’s initial research interest was in developing programmes that would teach intelligently – self-improving teachers – but using AI was too difficult and switched towards MIT’s focus on self-expression and for programmers to understand what their codes were doing. Still thinks the AI route is too difficult to apply to educational systems.

Q: surprised by an absence of gaming for learning?

A: clearly they can and cites Stanford on influence of games on learning motivation

Q: on academic credit and MOOCs

A: Thinks this is inevitable and points to Arizona State University which is attempting to develop a full degree through MOOCs. Can see inclusion of MOOCs in particular postgraduate programmes – heuristic of about a third of a Masters delivered via (external) MOOCs but more likely to be taken forward by more vocational universities in the UK – but using MIT or Stanford MOOCs replacing staff!.

Now moving on to Susan Halford on ‘Knowing Social Worlds in the Digital Revolution’:

Researches organisational change and work and digital innovation. Has not directly researched changes in academic work but has experienced them through digital innovation. Digital innovation has kick-started a revolution in  research through data volume, tracking, analyse and visualise all sorts of data. So data becomes no longer used to research something but is the object of social research.

Digital traces may tell us lots about how people live, live together, politics, attitudes, etc. Data capturing social activities in real time and over time rather than replying on reporting of activities in interviews, surveys and so. At least, that is the promise and there are a set of challenges to be addressed to realise the potential of these data (also see this paper from Prof Halford).

Three key challenges: definition; methods and interdisciplinarity

Definition–  what are these digital data: these are not naturally occurring and do not provide a telescope to social reality. Digital data is generated through mediation by technology and so is not naturally occurring. In the case of Twitter, a huge amount of data, but is mediated by technological infrastructure that packages the data. The world is, therefore, presented according to the categories of the software – interesting but not naturally-occurring data. Also, social media generate particular behaviours and are not simply mirrors of independent social behaviour – gives the example of the ReTweet.

Also, there is the issue of prominence and ownership of data. Survey data often is transparent in the methods used to generate data and therefore, the limits of the claims that can be made from the data. But social media data is not transparent in how it is generated – the data is privately owned where data categories and data stream construction is not transparent. We know that there is a difference between official and unofficial data. We do not know what Twitter is doing with its data but that it is part of an emerging data economy. So this data is not neutral and is the product of a series of technological and social decision-making that shapes the data. We need to understand the socio-technical infrastructure that created them.

Method – the idea that in big data, the numbers speak for themselves is wrong: numbers are interpreted. The methods we have are not good for analysis of large data. Research tends towards small scale content analysis or large scale social network analysis but neither are particularly effective at understanding the emergence of the social over time – to harness the dynamic nature of the data. A lot of big data research on Twitter is limited to mathematical structures and data mining (and is a-theoretical)  but is weak on the social aspects of social media data.

Built a tool and Southampton to dynamically map data flows through ReTweeting.

Interdisciplinariety: but is a challenge to operationalise inter-disciplinarity.

Disciplines imagine their object of study in (very) different ways and with different forms of cultural capital (what is the knowledge that counts – ontological and epistemological differences). So the development of interdisciplinarity involves changes on both sides – researchers need to understand programming and computer scientists need to understand social theory. But also need to recognise that some areas cannot be reconciled.

Interdisciplinarity leads to questions of power-relations in academia that need to be addressed and challenged for inter-disciplinarity to work.

But this work is exciting and promising as a field in formation. But also rises for responsibilities: ethical responsibilities involved in representing social groups and societies and data analytics; recognising digital data excludes those who are not digitally connected; data alone is inadequate as social change involves politics and power.

Now Sian Bayne is responding to Prof Halford’s talk: welcomes the socio technical perspective taken and points to a recent paper: “The moral character of cryptographic work” as  generating interest across technical and social scientists.

Welcomes the emphasis of interdisciplinarity while recognising the dangers of disciplinary imperialism.


What actions can be taken to support interdisciplinarity?

A: share resources and shared commitments are important. Also academic structures are important and refers to the REF structures against people submitting against multiple subjects. (but is is pointed out that joint submissions are possible).

Time for a break ….


We’re back with Bernard Schafer of the School of Law talking on the legal issues of automated databases. Partly this is drawn from a PG course on the legal issues of robotics.

The main reference on the regulation of robots is Terminator but this is less worrying than Short Circuit, eg, when the robot reads a book, does it create a copy of it, does the licence allow the mining of the data of the book, etc. See the Qentis hoax. UK is the only country to recognise copyright ownership of automatically generated works/ outputs but this can be problematic for research, can we use this data for research?

If information wants freedom, does current copyright and legal frameworks support and enable research, teaching, innovation, etc? Similar issues arose form the industrial revolution.

Robotics replacing labour – initially labour but now examples of the use of robots in teaching at all levels.

But can we automate the dull part of academic jobs. But this creates some interesting legal questions, ie, in Germany giving a mark is an administrative act similar to a police caution and is subject to judicial review, can a robot undertake an administrative act in this way?

Lots of interesting examples of automatic education and teaching digital services:Screen Shot 2015-12-17 at 12.10.02





Good question for copyright law is what does ‘creativity’ mean in a world share with automatons? For example, when does a computer shift from thinking to expressing an idea which is fundamental to copyright law?

Final key question is: “Is our legal system ready for automated generation and re-use of research?”

Now its Peter Murray-Rust on academic publishing and demonstrating text or content mining of chemistry texts.

…And that’s me for the day as I’m being dragged off to other commitments.

Getting stuff [and writing] done

I’ve recently started using Chris Winfield‘s technique of chunking tasks to 40 pomodoros per week which he describes here. I’m essentially using this technique for “maker” time – as described in this post from Paul Graham. I’ve found this technique works really well for writing (one I know what I’m going to write) as described as writing sprints here.

It may be the case that the “quieter summer” has made this easier and once the new academic year starts, I’ll find it harder to maintain this, but so far, I’ve found it impressively productive and not too tough to keep to.

Weeknotes 26062015

This has been a week of knuckling down at getting stuff done – but I also squeezed in one day off as the last day available before the schools break for summer (schools in Scotland start the holidays at the end of June but return mid-August which still feels so wrong to me). What I did this week:

attended a briefing session on the University’s process for academic promotion (lots of paperwork and pretty tough criteria)
had numerous dissertation supervision sessions on Skype
progress on my PhD writing an overview of research in to Twitter and the dominant approaches based on quantitative methods of statistical analysis and Social Network Analysis or studies based on conversation analysis. The comparative lack of qualitative research is a notable omission especially in considering the affective dimensions of online ‘communities’

A couple of links of interest from this week:
No, Sesame Street Was Not The First MOOC from Audrey Watters is a great post on open education, the history of MOOCs, the insurgency of venture capital in EdTech and the importance of theory and research in education (and some good pics of Bert & Ernie).

Mark Carrigan’s post on using a blog as a research journal is a useful overview of the purpose of a research journal as well as the benefits of working out loud.

Weeknotes 21062015

It has been a more hectic couple of weeks in some ways with

more exam boards as its that time of year
continuing planning course staffing for next year so my head was buried in spread sheets for a while
researching literature on communities on Twitter and how might the affective aspects of communities distinguish them from networks
meetings, lots or meetings …
assessing applications to be part of an exciting new initiative to launch in the New Year
reading up on Open Badges for possible inclusion in a new course launching in January 2016
attending the ReCon conference on open data and open publishing at Edinburgh University Business School . My notes on the conference can be found here
supervising a number of super dissertations which is great!

Weeknotes 05062015

It has been, in many ways, a fairly quiet week as I was working on:

exam boards as its that time of year
planning course staffing for next year so my head was buried in spread sheets for a while
researching literature on communities on Twitter and considering the role of hashtags and trending topics in generating a sense of being part of an imagined (virtual) community
in virtual meetings with various students and with Yulia Sidorova to discuss researching social media.

But I’ve mainly been feeling tired and a bit wiped out so could probably do with a break ….luckily, its the weekend!

Weeknotes 29052015

I would like to develop the habit of daily notes. In part so I don’t loose track of what has been done each day but also to support a return to blogging starting with summarising those daily notes in to weekly notes. What I need is to spend some serious time on forming and maintaining habits as discussed here, in particular as behaviour chains, process plans and perhaps far fewer “oh screw its” .

So this week I have been:

  • attending meetings and listing tasks as I have a new academic management role.
  •  lots of marking and moderating marks and exam boards.
  •  meetings with students on Skype and Spreed
  •  reading and writing on the concept of communities on Twitter.
  •  presented at the #mscde  on the supervision process that students can look forward to as part of the programme dissertation festival in Second Life. A video of my presentation is available hereDissertation festival_001 and others will become available at the MSc in Digital Education programme YouTube Channel soon.
  • attended an excellent presentation by Dragan Gasevic on learning analytics and the importance of context in making sense of such analytics. The presentation emphasised the importance of data literacy among students, teaching staff and institutional leadership *if* learning analytics are to make an effective contribution to improving education.

weeknotes [20102014]

Over the last few weeks, I’ve been

further working through my research involving discourse analysis along with network and other sociomaterial methods for my PhD. I think I’m developing a stronger understanding of of the method “in action” and Technology Enhanced Learning.

I’m also continuing to enjoy the teaching on two courses: Digital Environments for Learning; and Course Design for Digital Environments.

I’m also continuing to contribute to the development of two initiatives which I’ll hopefully write about sometime soon.

Distributed governance of technological innovation through the case of WiBro in S. Korea.

I attended the Social Informatics Cluster meting to hear Jee Hyun Suh present on: Co evolution of an emerging mobile technology and mobile services: distributed governance of technological innovation through the case of WiBro in S. Korea. These are rough notes taken during the presentation.

She presented the story of WiBro and the implications for the governance of large scale technological innovations for technology companies and government. WiBro was initiated from 2001 as a national R&D programme for high speed portable internet, it was harmonised with national and international standards (WiMax) and went to a commercial launch in 2006. It is widely seen as a case of market failure despite a successful technological innovation.

The research objectives were initially to examine the socio-technical factors in the development of the technology and the gap between the visions and outcomes of the technology commercialisation and explore the governance of large scale and complex innovations. The technology’s development was interpreted through social learning processes with a particular focus on building alignments between the technology, service evolution, standardisation and social learning within a wider development arena of R&D.

Over the course of the research period, 2001 to date, the focus of interest shifts from design & development of the technologies to a commercial focus on then on to a focus of the service evolution. The WiBro development was linked to broader policy imperatives of positioning S.Korea as innovation leader.

The technology itself was predicated on a problematisation of the inefficient use of 2.3 GHz and then enrolment of stakeholders to co-shape a generic vision of the using bandwidth portable internet service. This became co-evolved with drive towards a High performance portable internet and processes of standardisation.Standard setting closely linked to bandwidth/ spectrum allocation. Became conceived as a seamlessly interlinked innovation process. but different interests and objectives across stakeholders remained unresolved especially between focus on tech dev vs commercial exploitation through existing technologies. Also shifting alignments around adoption of differing international standards. The technology had been successfully developed and as pre-commercial produce was show cased at APEC 2005.
Commercialisation occured around processes of spectrum licensing. Again, different visions for WiBro, eg as an extension of fixed line services, as a differentiated service and as a complementary service to existing mobile networks. These different visions were rolled into different commercial aims eg, early market advantage vs emphasis on interoperability, adoption or blocking of VoIP as well as the emergence of 3G services. The later development of 4G mobile resulted in shifts to the vision of WiBro and how it should evolve.
Also, the commercial focus bifurcated on domestic versus a global market focus. In the domestic market, there could be seen the dynamics of trail and error on finding niche markets for WiBro, eg, mobile routers, digital shipyards, WiBro-Taxi. This market learning processes occurred despite tensions between players and their visions for the service.
The argument presented was that the ‘problem’ of WiBro should be framed in terms of uncertainties in innovation processes rather than in terms of a failure in diffusion/ commercialisation. So the coordination challenges and dispersed arenas of innovation enabled key players to interact in the social shaping of this particular technology highlighting the importance of stakeholder reflexivity and flexibility in large-scale technological innovations.
It was also noted during the Q&A that WiBro coincided with the testing and general failure of attempts at developing national technology champions that could then be exported in to global markets.

For more on social learning processes in innovation diffusion, see: