Tag Archives: higher education

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.

Theorising Technology in Digital Education

These are my notes taken during the presentation and then tidied up a bit in terms of spelling and sense – so they may well be limit, partial and mistaken!

Welcome from Sian Bayne with the drama of the day “fire! Toilets!” and confirmed that the event is being livestreamed and the video is available here.
Lesley Gourlay as chair for the day also welcomed participants from across the UK and  Copenhagen. Seeking to provide a forum for a more theorised and critical perspective technology in higher education in the SRHE (Society for Research in Higher Education). Prof Richard Edwards at the School of Education gained funding for international speakers for today’s events. Unfortunately Richard is ill and can’t be here.

The theme of the event is developing the theoretical, ethical, political and social analysis of digital technologies and shift away from an instrumentalist perspective. The event Twitter hashtag is #shre

The first presentation is by Alex Juhasz on distributed online FemTechNet. FemTechNet as a network does not often speak to be field of education so this is a welcome opportunity (she has also blogged on the event here)

FemTechNet is an active network of scholars, technologist and artists interested in technology and feminism. The network is focused on both the history and future of women in technology sectors and practices. FemTechNet is structured through committees and has a deep process-focused approach to its work that is in important in terms of feminist practices. Projects involve the production of a white paper, teaching and teaching practices, workshops, open office hours, co-teaching, etc. models the interaction of theory and practice. But it has been difficult to engage students in collaborative projects while staff/ professors are much more engaged. Town halls are events for collaborative discussion events with an upcoming event on Gamergate to include a teach-in. FemTechNet have also produced a ‘rocking’ manifesto as “feminist academic hacktivism” and “cyberfeminist praxis”.
FemTechNet values are made manifest in Distributed Open Collaborative Courses (DOCCs) themes on Dialogues on Feminism and Technology (2013) and Collaborations in Feminism and Technology (2014). DOCCs against the xMOOC model to promote a participative approach to course design and distributed approaches to collaboration. DOCC was labelled as the Feminist anti-MOOC based on deep feminist principles including wikistorming, and has much press and other interest, some positive and some ‘silly’ (Fox News). FemTechNet has lots of notes on using tools and teaching approaches that can be used across lots of different critical topics beyond feminism alone.
DOCCs are designed to be distributed and with a flatter hierarchy with less of a focus on massiveness. Using technology in an open way to co-create knowledge beyond transmission. More details on the DOCC as a learning commons vs course can be found here.
The FemTechNet commons is now housed and redesigned at the University of Michigan although this may be a way of universities avoiding Title 9 violations. But as a result, the newer commons has become less open and collaborative as an online space.
Much of FemTechNet work involved overcoming technological hurdles and was based on the unpaid work of members. FemTechNet engage with critique of lobour practices and contexts in higher education.
The DOCC networks involve a wide scope of different types of universities from Ivey League and community colleges and community organisations collaborately working.
Student numbers are fairly small with approx 200 students but very high completion rates and very positive feedback and evaluations. Between 2013-4 there was not really growth of scale partly due to limitations of infrastructure. Now with the support of University of Michigan, there is an increased aspiration to develop international collaborative work.
DOCCs involve networking courses from many different fields of study involving both on-campus to fully online courses. Basic components of courses are keynote dialogue videos, smaller keywords dialogues and five shared learning activities. See also the situated knowledge map [link]. There is a big emphasis on share resources, cross-displinarity and inter-institutional working and learning.
So while DOCCs emerged from a feminist network, the tools, models and approaches can be used in many subject areas.

After lunch

Ben Williamson is prsenting on Calculating Academics: theorising the algorithmic organisationan of the digital university. The open slide isof a conceptualisation of a digital university university that can react to data and information that it receives. Ben will be prsenting on a shift t understanding of the university as mediated by the digital and focus on the role of algorithms.
One of the major terms being used is in terms of the smart university based on big data to enhance teaching, engagement, research, enterprise to optimise and utilise the data universities generate. This turn is situation in the wider concept of ‘smart cities’.
Smart cities are ‘fabricated spaces’ that are imaginary and unrealised and perhaps unrealisable. Fabricated spaces serve as models to aspire to realise.
Smart universities are fabricated through
technical devicecs, softre, code,
social actors including software producers, government and
discourses of text and materials.
Algorithm is seen in compsci as a set of processes to produce a desired output. But algorithms are black boxed hidden in IP and impenetrable code. It is also hidden in wider heterogeneous systems involving languages, regulation and law, standards etc.
Also algorithms emerge and change overtime and are, to an extent, out of comtrol, and are complex and emergent.
Socio-algorithmic relationality as algorithms co-constitute social practice (Bucher 2012); generate patterns, order and coordination (mackenzie 2006) and are social products of specific political, social and cultureal contexts and go on to produce by temselves.
Involve translation of human action through mathematical logics (Neyland 2014). Gillespie (2014) argues for a sociological analysis of algorithms as social, poitical as well as technical accomplishments.
Algorithms offer (Gillespie 2014): technical solutions; as synedoche – an abbreviation for a much wider socio-technical system; as stand-in for something else around corporate ownership for example; commitment to procedure as they privilige qualitification and proceduralisation.
Big data and the smart university is a problem area in this idea of the smart university. Is there a different epistemology for big data. Big data cannot exist without algorithms and has generated a number of discourses. Wired mag has suggested that big data is leading to the end of theory as there is no need to create a hypothesis as big data will locate patterns and results and this is a challenge to traditional academic practice. Also there is the rise of commercial social science such as the Facebook social science team often linked to nudging behaviours and “engineering the public” (Tufecki 2014). This is replicated in policy development such as the centre for analysis of social media at Demos using new big data sets. We’re also seeing new academic initiatives such as social physics at MIT and building a predictive model of human behaviour. Also see MIT laboratory for social machines in partnership with Twitter.
This raises the question of what expertise is being harnessed for smarter universities. Points ot the rise of alternative centres of expertise that can conduct big data analysis that are labelled as algorithmist Mayer0Schonberger and Cukier. Such skills and interdisciplinarity does not fit well in university. Sees the rise of non-sociologist sociologists doing better social research?
Mayer0Schonberger and Cukier Learning with Big data – predictive learning analytics, new learning platforms, et.\c. that is reflected in the discourses on the smarter university. Bid data generates the university in immediate and real time- doesn’t have to wait for assessment returns. See for example, IBM education for a smarter planet focused on smarter and prescriptive analytics based on big data.
Knewton talks of inferred student data that suggests the algorithm is objective and consistent. But as Seaver (2014) points out, these algorithms are created and changed through ‘human hands’.
So we’re seeing a big data epistemology that uses statistics that explain and predict human behaviour (Kitchin 2014): algorithms can find patterns where science cannot that you don’t need subject knowledge to understand the data. But he goes on that this is based on fallacies of big data- big data is partial, based on samples, what analysis is selected, what data is or can be captured. Jurgenson (2014) also argues for the understanding of the wider socio-economic networks that create the algorithms – the capture of data points is governed by political choices.
How assumptions of bid=g data are influenceing academic research practices. Increasingly algor entwinned in knowledge production when working with data – sch as Nvivo, SPSS, google scholar – Beer 2012 – algorthimic creation of social knowledge.Also seeing the emergence of digital social research around big data and social media. eg social software studies initiative – soc sci increasingy dep on digital infrrastructure not of our making.
Noortje Marres rethink social research as distributed and share accomplishment involving human and non-human.
In turn influences academic self-assessment and identity through snowball metrics on citation scores, researchfish etc. translating academic work in to metrics. See Eysenback (2011) study linking Tweets and rates of citation. So academics are subject to increasing quantified control mediated through software and algorithms. Seeing the emergence of the quantified academi self. Yet academics are socialised and by these social media networks that exacerbtes this e-surviellance (Lupton 2014). While share research develops its own lib=vely social life outside of the originator’s control.
Hall (2013) points to new epistemic environment that academics are being more social (media) entrepreneurial. Lyotard (1979) points to the importance and constraints of computerisation of research.
Finish with Q
– how do cog based classrooms learn?
–  what data is collected to teach?
– should academics learn to code?

A lot of discssion on the last question. It was also pointed out that its not asked should coders learn to be sociologists?
Also pointed out that people demonstrate the importanc of embodoed experiences through protests, demonstrations, that reflects what is loss in the turn to data.

After a short break, we now have Norm Friesen on Education Technology or Education as always-already Technological”. Talking about educational technology as not new but as going through a series of entwinements over time. Norm will look at older technologies of the text book and the lecture as looking back at older recognisable forms.
Looking back we can argue that educational technologies now are not presenting particularly novel problems for higher education. Rather higher education has always been constituative with educational practices then we can see how practices can adapt to newer technologies now.
Tech in education have always been about inscription, symbols as well as performance. If we understand the university as a discourse networks – see Kipler’s discourse network in analysis of publishing in 19 Century. Institutions like universities are closely linked to technology in storing and using technologies and modifying technologies for their practices.
In the example of tablets going back to ancient times or the horn book or other forms that is tigtly couple with institutions of learning and education. Such as clay tablets dating back to 2500 – 2000 BCE that show student work and teacher corrects as symbolic inscriptions of teaching and learning practices. And such tablets work at the scale of individual student work or as larger epic literatures. Can see a continued institution symbolic practices through to the iPad. Here technologies may include epistemic technologies such as knowledge of multiplication tables, procedures of a lecture – technologies as a means ot an end – so technologies are ‘cultural techniques’.

For the rest of the presentation will focus on the textbook and lecture as technologies that are particularly under attack in the revisioning of the university. Ideas of the fipped classroom still priviliges the lecture through video capture. Similarly the text book has yet to be overtaken by the e-textbook. Both provide continuities fromover 800 years of practice and performance.
The lecture goes back to the earliest university as originally to recite a text, so for transmission rather than generation of knowledge with a focus on the retention of knowledge. Developing ones own ideas in a lecture was unknown and student work involved extensive note taking from oral teaching (see Blair 2008). The lecture is about textual reproduction. Even following the printing press, this lecture practice continued although slowly, the lecturers own commentary on the text was introduced manifested as interlines between lines written from the dictated text. Educational practice tended to  not change as rapidly as the technologies of printing such that education was about 100 years behind.
But in 1800  saw the first lectures only from the lecturers own notes. so the lecture was recast around the individual as the creator of knowledge. So the individual lecturer and student not the official text became the authoritative sources of knowledge. Also the notion of the performance becomes increasingly important in the procedure of the lecture.
In textbooks we see pedagogical practice embedded in the text as end of chapter questions for the student to reflect and respond to (the Pestalozzian method, 1863). This approach can be seen in Vygotsky, Mead and self-regulated learning.
Specific technological configurations supported the increased emphasis on performance such as podcasting, powerPoint, projectors, etc. (see TED talks).
In the text book, similar innovations are happening in term sof layout, multimedia, personalised questioning (using algorithms). The text book becomes an interactional experience but continue from much older forms of the textbook. What is central is what are the familiar forms – that underlying structures have persisted.

But it is also the case that lectures nolonger espouse their own theories, they do not create new knowedge in the lecture.

Unbundling higher education

These are my notes from a seminar by Amy Collier, Stanford University  titled The Good, the Bad and the Unbundled on 27 August 2014. These notes were taken live and then cleaned up a bit, links added etc. but they remain a bit partial and sketchy in places.  For a more thoughtful and reflective take on the presentation, see Hazel Christie’s post here. Amy’s own post on her visit  can be found here.

The presentation is looking at this emerging phenomenon in the US Higher Education sector and the possible lessons for UK Higher Education.

Amy has been at Stanford for two half years working on MOOCs and on supporting the increasing interest in online learning at Stanford from a position of a weak tradition of online learning. Her role initially focused on the operational aspects of course design. She now has developed a more strategic role asking what they’re doing, who is being targeted and why adopting online learning.

Unbundling is an increasingly prominent topic in US  higher education. It should also be noted that unbundling has a long presence in UK HE in particular through the Open University.

The Unbundling idea has taken hold in the US as part of a wider discourse of ‘disruption’. The US has a weird love affair with the term ‘disruption’. This love affair is based on a ‘dis-ease’ with how things are currently done. Higher education is ‘broken’ and should be disrupted and that disruption is often undertaken through unbundling. Yet, that discourse of  dis-ease with a broken education system is often promoted by others as means to sell ‘solutions’.

Unbundling is the separation of ownership of infrastructure and processes of service provision to gain efficiencies and savings. So unbundling involves the compartmentalism of components of HE that are then outsourced to other providers rather than the traditional model of being provided by a single institution.

As an example, the music industry as traditionally produce a bundled product such as the album, but then iTunes disrupted this product by allowing the purchasing of single songs, users creating their own playlists, etc… Apple and iTunes allowed us as customer to do things with the purchased products independently of music businesses. This development lead on to Pandora and Spotify and took place within a discourse of ‘freedom’ and ‘access to artists’ and hence as the democratisation of the music industry. Similarly, we’e seeing an emerging discourse on the democratisation of higher education in US.

So what is the problem? What is lost when we unbundle? In the case of the music industry, we can see a counter-trend with the return of the cassette as a ‘product’ as a piece of art that cannot be unbundled (popular in Portland – who knew?), it is a single, indivisable and cohesive piece of art. Similar examples of rebundling can be seen in the examples of free music when you buy phone X or in playlists created by Pandora. So unbundling and then rebundling leads to a loss of control and more importantly, a loss of a sense of the whole – replaced by another interpretation of that whole – the art of the album. Also, while obscure artists can be found online they don’t have the sales volumes to make money through these unbundled services.

How does this apply to HE? Returning to the notion of HE as broken is “disaster porn” such as the  IPPR report, An Avalanche is Coming. The IPPR report cites the diversity of pressures on HE in terms of purpose, funding, public policy in the context of a globalised economy where HE is no longer fit for purpose. HE should, therefore, look to technological solutions and these are to be found in the private sector.

A particular recent emphasis is on questioning the value of university, is it worth going? The degree is dead, reimagining higher education. Jose Ferriera (at Knewton) claims bundling works to trick people in to believing a service is worth more than it is and hiding the real cost-benefit.

Unbundling in HE may involve splitting: content; social networks; accreditation; delivery; testing; and research (see Henry Brady, UC Berkeley). But what are the tensions then between economic efficiencies and the holistic integrity of education?

MOOCs have inflated this discussion of disruption and unbundling. Clay Shirky argues that HE is being, and should be disrupted and, returning to the music industry analogy, the “MP3 is our MOOC“.

And we can see examples of MOOCs unbundle accreditation from HE now. The American Council of Education is offering credientialisation of MOOCs through member HEIs so separating/ unbundling the delivery and accreditation of courses. Antioch College told its own students that they could receive credit for MOOCs thereby unbundled content, credit and, in this case, the tutoring and support of learning.

But the concept of unbundling has been going on in HE at least since the 19th Century, for example, in unbundling academics from the pastoral roles.

The problems of unbundling:

While a lot of the authors of the disruption discourse make this comparison to the music industry, as George Siemens states, education is a social and cultural as well as content ‘industry’. In taking that perspective, a number of problems with, or questions on, unbundling can be identified:

1. Who, how and what of rebundling? Who does the rebundling and what power are they taking through rebundling? Things that get unbundled tend to be rebundled with a change of ownership and control and what does this mean, for example, on the student experience?

The Minerva project provides access to higher education at reduced cost by focusing on (transferable) skills rather than content/ domain knowledge. They rely on MOOCs for domain knowledge for introductory courses. So Minerva are rebundling MOOCs provided by others while focusing on project-based and experiential learning..

A dark-side of this is that there will still be very bundled education institutions and there is a danger that these highly bundled experiences become the expensive premium service for an elite minority. So the unbundling and rebundling ‘disruptions’ will increase the divisions on access to high quality education.

So, while it remains the case that for some students the unbundled experience may be what they want and need, a key question remains that if unbundling is about raising access to HE then who for and to what form of HE?

Also, bundled and unbundled experiences collected data. HEIs are generally trusted to handle data with care and respect but what happens when services are unbundled and rebundled with the concomitant opportunities for the commercial exploitation of student data. For example, the backlash on the recent Facebook experiment was not just against Facebook but also Cornell University for their role in analysing the data.

2. Impacts on teaching and other staff.
We can see the unbundling of the academics’ role eg, in support development of student social networks, advising, admissions, instruction design,teaching, research etc . especially to para-academics, but this is problematic if you view the academics’ role as holistic.
In the case of MOOCs, courses are being designed by people who may not deliver/ teach on them. But this approach can also be seen in the development of Online & Distance Learning (ODL)  programmes from the 1990s as they considered how learning technologists interacted with academic staff. Different models of ODL can be seen:

(i) craft model where faculty did it all; (ii) collegial model where academics helped each other; and (iii) where a virtual assembly line was created the produced a course for  academics to deliver. The craft model is where academics identified themselves as autonomous experts whereas this identity was lost in the assembly line model. So unbundling also affects academic self-identification.

But why is an integrated faculty role of value? Because it engages academics in their work and highlights the integrative role of research and teaching. On the other hand, unbundling does allow faculty to focus on individual areas of strength – why force a shy researcher in to teaching?

There are other models such as Patricia Ianuzzi’s (University of Nevada) team-based model involving the co-production between academics and para-academics of student experiences.

3. the lost art of the University: what happens when unbundling leads to loss of serendipity and synergies of the bundled student experience?

On a positive note, unbundling may provide opportunities for the redesign of HE and to challenge assumptions of the institutions.

Examples of redesigning rather than unbundling has changed HE
1. domain of one’s own at the University Mary Washington as a push-back against VLEs and MLEs. Each student was provided with a domain for students to use any tools they wanted and use for their learning. This initiative allows students to experiment with online learning both personally and in groups. Another initiative is Thought Vectors at Virginia Commonwealth University enabling student learning on open websites.

2. the Stanford 2025 project involved both students and staff to consider the redesign of Stanford for 2025. For example, redesigned away from semester and academic years to a much more flexible programme structure built around micro-learning opportunities as Paced Education. In effect this is unbundling the curriculum and is being implemented through The Impact Lab. This social innovation is focused on the food system and involves students researching (immersion), prototyping and piloting implementations of interventions in the food system.

The key point of this talk is to examine the issues and opportunities in the unbundling of higher education.

Q: Can you separate the neo-liberal drivers of the rise of idea of unbundling and the more positive opportunities of redesign? How suspicious should we be of unbundling in HE?
A: I’m very suspicious mainly because I work in Silicon Valley and see unbundling projected as way for start-ups to access investment and government  to ‘solve’ higher education through the private sector.

Q: Can you comment on the adjunct faculty in the US as it appears to be linked?
A: Unbundling the faculty role leads to the deskilling of the faculty so seeing rise of adjunct faculty as having very specialist skills along with precarious employment positions. See the alt ac movement in US (alternative academic).

Q: Comments Music Industry to suggest that senior managers saw that the internet would change their business but didn’t know how to change. Also, the UK has the experience of the OU for the team development of courses. Finally, HEI is very diverse but that is hidden to many of us. Some HEIs rebundle through eg, accreditation of prior learning (cites military in US as example of this)
A: RPEL is really important. A key danger of unbundling is that it imposes a monolithic view of HE and that a sense diversity is lost.

Q: Interested in your views of a model from Cornell University of a faculty housing model of free housing if you live with the students as a rebundling of student services?
A: Stanford has strong ethos of living on campus and the creation of a learning community.

Q: Who is the customer and what is the product? Are students viewed as a product and society the customer?
A: The student as customer is a strong aspect of the unbundling discourse. People have changed their ideas of education as a public good and the promotion of citizenship – now less of a priority given the end of the Cold War.

Q: Worried that there may be an oversimplification of a good or bad unbundling and whether there is a need for a bigger discussion on what the university is for?
A: I’m not opposed to unbundling per se but more discussion is needed beyond the binary of good and bad but that allows the challenge of the assumptions of educational institutions

weeknotes [27062014]

Over the last couple of weeks I’ve been:

– Attending a seminar by Geoge Veletsianos on educational agents
– facilitated a workshop discussion on the internationalisation of higher education following a talk from Alison Phipps. This was a challenging talk on the dominant discourses found in university internationalisation strategies in general that reflected a broadly colonial sensibility presenting the educational institution as filling in a blank ‘other’. As a response, Alison suggested a consciously co-generative and collaborative approach to education with a focus on the quote “nothing about us without us is for us”. So the challenges seemed to be about breaking down the boundaries of the institution as a place where learning is delivered to learners in a form decided on by the institution but rather about developing practices of learning that “attend to” a multiplicity of voices and languages, race, inequality, oppression and expression. How such approaches can develop in the context of a university and its attendance to processes, standards and quality is the key question. The discussion component of the day was fairly brief but focused largely on internationalisation as an organisational culture issue with progress perhaps to come from *100 small changes* of habit and practice.
– related to this seminar, was another internal seminar labeled as learning from review and focused on developing the academic literacies of students as they transition in to (UK) higher education, between different stages of their education and onward as lifelong learners
– presented on some aspects of my research here
– contributing to the development of a couple of project ideas on course design and on professional learning but early days on both of these
– my main area of teaching and learning is in Masters’ dissertation supervision

Network Learning Conference: keynote from Steve Fuller

We’re now into the afternoon of the second day of the conference with Sian Bayne welcoming Steve Fuller but not knowing where to start or stop. Steve works in sociological methodology and epistemology. Steve has published widely on sociology, STS and post humanism.

Steve’s lecture is on the academic lecture 2.0.
His original training is in the history and sociology of science and main concern is in social epistemology. How knowledge is produced and distributed from a normative perspective. We can bring together more resources, distributed more wideley and people are better able to deal with or analyse such knowledge resources and so justifying the tab of the ‘knowledge society’. So what difference does a university make? HEIs are resilient but what is their distinction now beyond the simple bundling things together efficiently?
Steve is pro university in a classical notion of the university in Humbolt’s perspective of the academic as a transmitter of research through teaching. Prior to Humboldt (start C19) the interesting intellectual activity was occuring outside the university, eg, the enlightenment, the industrial revolution and the development of science – all outside the university. Humbolt incorporated the enlightenment spirit in to the university presenting the university as a dynamic institution. Before then, HE was to train people in the learned professions or as land/ wealth owner. Humbolt changed this, in part as part of a wider agenda promoting Prussia from being a second level country. HEI’s to do more than pass on tradition but to innovate.
So HEIs one of the earliest institutions to promote innovation. HEIs one of earliest corporations as self-organising with purposes of its own that extends beyond the life of the individuals involved so has a life and purpose and impact beyond a single human life.
So now are HEIs just about looking to preserve themselves or should and can they evolve? This was Humbolts idea that HEIs should evolve and produce graduates to go out to improve the world. Here the lecture was very important – the soul of the modern university.
Going back to the idea of before the enlightenment HEIs about transmitting traditional knowledge. But in C18 arose ideas of alternative forms of knowledge and so orthodoxy no longer good enough. The enlightenment about not just reproducing knowledge but that each individual can think for themselves as “dare to know” and make jusgements for themselves.
By the C19 could see revolutions and established orders were changing and market economies firmly established so what sort of leaders and thinkers do you knew. Humboldt driven by this alongside nation building. The points to the value of the lecture as not about the reliable transmission of knowledge given the range of media available, and the lecture is very authoritarian but its value in its asymmetry is that if the lecturer is good is the exmplification of the practice of ‘daring to know’. You do not want the lecture reducible to the Powerpoint and book chapter.
Prussia C19 lacked a generalised freedom of expression so was a precious thing for those entitled to free expression had a responsibility to study and understand things carefully before ‘daring to think’. Academic freedom was originally a guild right of freedom of expression and students train themselves to make judgements by attending different lectures and hearing different perspectives.
The Humboldtian university to act as an incubator of freedom and exploring what it means to be free. Freedom here meaning free for making informed judgements. Lecturing is an artform of the university and should be preserved as such. But the market of the networked learning pressure against such lecturing practices towards shallow learning and the transmission of established bodies of knowledge. Thus market pressures in HEIs act aganst the spirit of the enlightenment that makes the university a distinctive institution.
If HEIs seek to compete in the knowledge transmission market then universities will loose. Universities need to understand, identify and protect their core distinct identities. If concerned with knowledge transmission then you don’t need universities but rather you need a validating agency to certify that a student has attained “good knowledge”.
Moving on to the persona of the intellectual as someone who can improvise as an image of what it is like to think in public. Improvisation presupposes the existence of text – to improvise away from the text and exhibit their powers of thinking for themselves. A key challenge is that we’re able to record more and more of what we do often owned by someone else so we need to do something new each time to avoid infringing IPR. If you reliably deliver standardised lectures, you will be replaced!
The separation of research and teaching is a major challenge to this re-emergence of the enlightenment spirit. The idea of translating research into teaching is seen as a secondary task and this underpins a division of labour in HEIs. The outcome is an impoverishment of the lecture as a transmission vehicle and so it makes sense to get the content from an entertaining lecture online. But a lecture is like jazz and improvisation. Cites Liszt as a virtuoso adding new variations on traditional musical themes. For the 19C academic gained influence through enacting on and embellishing on their written texts as improvisation.
Lectures were a key part of university’s brand, the great universities had the great lectures engaging in public thinking and motivating students to critically read ‘the texts’. [In effect, the book and the lecture were a combined package].
So the uniqueness of a university is to take thinking and improvisation of conveying information as someone thinking for themselves. If all your interested in is cutting edge research or imparting vocational knowledge then there are much more effective ways of doing this than universities.

Q. Why is the lecture the best way of supporting students to think for themselves rather than, eg, direct dialogue?
A. but students still need to learn to think for themselves. A lecture has a argumentative form with an expectation that people will object. The key issue here is enactment and role-modelling of a public disputation (as well as in seminars, tutorials etc….). The public performance of thinking for yourself is the unique brand of the university.

Q. can we not model thinking for yourself beyond the oral tradition?
A. an important aspect is taking responsibility and multi-modality includes a danger that you can avoid taking responsibility by blaming the text, the slides etc… It is important to show the process of weighing and measuring alternatives perspectives.

Q. how can academic freedom be rearticulated in a networked world?
A. everyone is an information provider and universities should be more adventurous in entering these spaces, eg, in promotion of the strong lecturers. Links this to recruitment processes as academics should be performers – that HE should be dramatic! but this also requirs higher production values – Hollywood productions and Hollywood budgets!

Perspectives on identity within network learning

Well my notes on Neil Selwyn’s keynote got lost but am back for as session on identity issues in network learning with @janedavis13, @catherinecronin and @catspyjamasanz collaborating together on identity research. See #nlcID

Jane Davis on the conceptualisation of identity linked to roles in networked learning. Identities as Jane as me/ myself; as a student; researcher and practitioner. As a student, her roles included as practitioner, mother, student and partner but these roles changed over time especially over salience (as most prominent) at any given point in time.

So roles and identities merge over time and impact on what students do/ how they act.

So participants now to create diagram of own roles as students. As so individual to each student so we can suggest each student identity is unique.

In considering student identity, role identity depend on expectations in a wider social context. Shaped by family experience, or someone elses experiences, marketing of HE etc.

Again, these expectations are different to the individual.

Dimensions of student role identity as (i) academic responsibility; (ii) sociable; (iii) intellectually curious – scanner out seeking new knowledge; (iv) personal assertive – want to win awards, prixes etc. Each student has some of each dminension alongide expectations and roles but we try to aggregate all students as just ‘students’. And these change over time according to most salient role and porosity of roles.

Impact on student participation in networked learning:
relational nature of affordance of the learning place; nature of engagement/ practice with technology for learning reflecting practices of visitor, tourist, tenant or resident). The more intellectually curious student more likely to adopt resident behaviours while the responsible student will adopt tourist behaviour using the technologies suggested / required by the tutor.

Catherine Cronin. Quotes Joi Ito on education as about becoming a node in a broad network of distributed creativity. Jenny Mackness: “space prepares to receive or respond”.

Networked individual (Castells) – based on social networks emerged with easier travel, use of telephone etc. while the internet brought in notions of openess while space and time redefined by mobile tech
Danah boyd defined networked publics as created through technologies and networks and communication now public by default.
Alec Couras came up with the concept of the networked teacher. That a teacher is a networked individual – is multimodal, networked and immediate.
Students are also networked individuals. So the question is where do networked students adn teacher encounter one another: physical spaces; bounded online spaces and open online spaces. Much teaching uses all three spaces depending on pedagogical and other choices.
Physical classrooms do not require lectures but that involves fighting against the architecture of the lecture hall. Bounded online spaces also have architectures that are more flexible and less temporally bounded and a bit freerer in how identities are defined and instructors are privileged. In open online identities allow reconstruction of identities as multiple, culturally contingent and contextual. This is true of all identities but more explicit and messy in open online spaces.
Instructors can join networks with students and share networks with students within consistent or multiple/ ‘play’ identities. Instructors can be seen modelling themselves as learners.
Her research is exploring the idea of a third space where student and teacher scripts – the formal and informal – intersect creating the potential for authentic interaction. Involves using formal and informal communication to enhance the learning experience. So the third space links formal and informal learning and link communities and networks. Using skills and confidence development in learning and community spaces to spread out to networks. ref Wenger “negotiation of productive identities”. The third space offer opportunities for teacher and student identity development.
Joyce Seitzinger on exploring online identity through social curation. How do we currently discuss curation in terms of online information resources with earlier academic literature is vague discussions of information resources and information flow, sharing and acquiring. Van der Klink talks about curation as learning.
On google can see an increase in searching on the term ‘curation’. Curation can be categorised as digital curation (digital repositories); content curation involves SEO and driving web traffic; social curation where the intent is to do something social. Defines social curation as:
“The discover selection collection and sharing of digital artefacts for social purposes”
Involves collecting in a cluster of resources eg, on Pinterest, Scoop It etc..
But users need to find the resources. For a student this may be through the LMS but as learners become more independept so using social cites like Flipboard, Facebook etc… and then select resources of interest which can be collected privately or openly and then shared. Sharing can happen simultaneoulsly to collecting, eg on Scoop-It.

Online identity through exhibition, ref Goffman’s presentation of self through social curation of ‘this is what I like”. Enacting an identity by sharing resources of a third party.
boyd, discusses online identity in SNS as involving connections while social curation does not involve connecting directly to an individual as a follower etc. Also, such curation identities does not involve a lot of self-disclosure online. Also avoids some of the difficulties of collapsed contexts between teachers and learners. Also community curation can present identities through supporting online communities.

Participant activities on mapping our curated collections and whether their are in bounded or spaces and therefore how transferable these are, eg, if moving jobs/ employer.

Point made on distinguishing between private and professional identities but also the academics tend to identify with their discipline communities rather than specific institutions.

A question on the quality of curation, eg. including a comment on a Scoop. But value is not just added by commenting but also by the act of curation – that adding a resource to a collection already adds value and is a comment in its own right.

Q. that links third space with liminality as a between spaces. But using third space as a description of a transformative space between formal and informal learning spaces.

Q. on data identity such as through netflix of spotify data that curates an identity.
A. yes, this is an area of interest. Also looking at how links/ networks form around the curated collections.

Working and learning in networks

I’m currently pulling together various thoughts on issues surrounding organisational design, networks and workplace or occupational learning. Initially, I’m drawing on:

the notion of learning networks, defined by Sloep (2008) as: “online, social network that is designed to support non-formal learning in a particular domain” to frame a discussion of the use of social technologies for workplace learning and the management of knowledge. In particular, the affordances of social technologies in enabling learning outcomes traditionally seen as vicarious by-products of work activities to be captured and made explicit as micro-learning objects (Peschl 2006; Schmidt 2005), will be explored in the context of professional learning that focuses on responding to complex and ‘wicked’ problems (Margaryan et al, 2013).

From this, I’m looking to explore


… how technology enabled learning networks act as mechanisms for personal professional competence development. How might or how do professionals combine and use self-selected digital tools to support the integration of work and learning as Personal Learning Environments (PLEs) (Pata 2009; Ralagopal, et al 2012) and approaches to Personal Knowledge Management (PKM) (Redecker 2009)?

So I *think* the argument I’m developing is that increasingly for *some* occupations, workplace learning is in practice operationalised as a ‘web of relations’ (Fenwick 2008) within and across organisational and professional boundaries and so the long-standing practices of L&D functions are increasingly redundant in this context. By extension, I’d suggest that there are various implications arising form this for much higher education provision: for example, is the privileging of knowledge content really justified, can the assumptions that students are effective learners in such a context justified, where or what may indicate knowledgeable authority in such a context?

IT Futures Conference – Disruption

Here’s my attempt at live blogging the IT Futures conference at the University of Edinburgh IT Futures conference on the theme of Disruption. The hashtag for the conference is #itfutures

The conference is starting with an address from the Principal, Sir Tim O’Shea on disruptions, predictions and surprises and the need for systematic thinking especially on what really is surprising in teaching, learning and research activities. He is largely to talk about the student experience but points to the importance of IT for research activities is also important, and pointed to the use of computational modelling in the recent chemistry Nobel prizes.

Disruptions described as ‘the pretentious bit’ and lists as disruptions: nouns and verbs; tilling and fire; writing and printing; machines; engines and electricity; telegraph/ phone/ vision and then computers. Notes that the telegraph was hugely disruptive to diplomacy and the role of the ambassador by allowing leader to ‘talk’ direct to leader.

Describes a computer as an amplifier of cognitive abilities. The question is whether MOOCs are disrupters of HE? Reflects that the printing press and the OU did not fundamentally disrupt the lecture-led HE model. So large changes can still be non-disruptive.

The major predictions of:

  • Moore’s law that the power of computers will double every 18 months and will stay true for another 8 years;
  • Metcalf’s law predicted that the internet will ‘fall over’ early 2000’s due to volume of traffic proved not to be true
  • Bayes’ law on probability
  • Semantic networks predicted from 1960s so Google should not be described as surprising
  • Cloud – first described in 1960s as software as a service
  • Intelligent Tutors – look to 1962 for first description of an intelligent tutor.

Minor predictions such as the iPad as a personal portable device along with ICT integration (iPhone); robots; videophone; personalised instruction; cybernetics; and speech recognition predicted decades ago.

So what are the big surprises?

  • that Moore’s law is true and Metcale’s law is still false (due to redundancy in the system)
  • Facebook and Twitter
  • Google Translate using Bayes’ Law
  • Very personal computers
  • Netscape business model – give the product away for free and work out monetisation later.

Smaller surprises include the World Wide Web; Third World take-up; face recognition now; mouse and take-up; reliability; MOOCS.

ICT characteristics: as a memory prosthetic; ubiquitous; revered time travel; disrupted highly redundant; very cheap; garage start-ups (HP) – which is mainly the point of massively reduced costs of entry now.

The educational opportunities:

  • OERs especially software
  • natural languages – points to the translation of MOOCs by volunteers including in minority languages
  • visualisation of models and data
  • wisdom of crowds – see the astromoly MOOC with volunteers discovering new stars/ planets
  • Big data – in health, social data, physics
  • Fast feedback
  • Universal access – “to the blessings of knowledge”

The challenges are in: reliability; security; platform sustainability – most platforms we use now will probably not be here in ten years so need to design for platform independence); planned obsolescence; enquirer to alumnus (a single integrated student IT model); internal IS silos and appropriate assessment. Appropriate assessment is one of the larger challenges and innovation is needed here as traditional assessments are often inappropriate.

Implications for HE are varied: a squeezed middle model where MIT, Stanford will be OK as will Manchester Met as a local vocational HEI will also be OK. The top 100 will be OK. Student mobility, pick & mix and credit accumulation will be (finally) realised as a workable model. This has some interesting implications as Edinburgh perceived as the best University in the world for literature.

The assets of the University of Edinburgh: Informatics and high Performance Computing are key strengths; the University has won Two Queen’s Prizes both for e-learning (in teaching Vets and in teaching surgery both at a distance); Edina; Institute of Academic Development and the Global Academies; Information Services and leading in European provision of MOOCs.

Trends of changes:

  • e-journals and e-books massive growth in both availability and use
  • but also the number of library visits has increased (doubled in ten years)
  • students now increasingly own a computer (99% now have their own).

Which suggests: more MOOCs; more online postgraduate programmes; more hybrid undergraduate programmes (eg, drawing on online resources including from MOOCs); advanced ICT partners; radical experiments; learning analytics is key along with innovation in assessment. Describes stupid schools as those that have not developed online programmes and/ or MOOCs. In terms of partnerships, the University needs to be selective and ask what is in it for us in terms of learning from partners. New Chairs in Learning Analytics and in Digital Education were confirmed.


Q: why use the term ‘disruption’

A: that conference organisers used contemporary business school jargon and prefers challenge and opportunities

Q: You’ve discussed how you cannot assume that the ICT incumbent is immune to these global changes so why apply that to universities?

A: in pre-MOOC world innovations were led by smaller niche universities but now what has changed is the scale and impact of MOOCs led by leading world universities. But no institution is safe and it is still the case that smaller institutions can generate ‘disruptive’ innovations. This is a reason for the need for radical experimentations.

We’re now moving to the keynote talk from Aleks Krotoski of a 30 minutes recoded presentation then she’ll join us for Q&A and a response from Chris Speed.

Asks why online information is rarely subjected to the critical thinking that other sources are subject to (journalism, politicians, teachers etc.). Technology is a cultural artefact created by people with particular interests, tools, at a specific place etc. so technology is also art.

So what is in the frame – taking from cinema – to create compelling story-telling but also leads to the question of what is outside the frame. The same is true of software but we lack a recognition of this or also how to question them.

Context is key: your perspective on the ideas about world depends on the context of when you receive the idea and so context cannot be taken account of by machines. Are we being manipulated by men behind the curtain

Tech is being developed on a wider societal and cultural context – see how computers replicate the office environment. Features of technology define what can and cannot be done with that technology.

Digital identity: how define being human. Many aspects of sense of self, names, user names and can this be translated into software. Digital identities are assigned to any ‘thing’ – a person, group etc.. and assumed to be either true or false. But identity changes in context and over time and this is difficult to capture in software. But defines the human online but also reflects biases of engineers in presenting us as us. Bie, google’s predictions based on algorithms depends on biases of the engineers and the results appear to be relevant but not necessarily so and presents outputs based on observed behaviours. It also assumes all sources of data are equal and that quantitative judgement are superior.

Facebook: social networks as platforms for self-expression and create online identities but how and what you can express is constrained, eg, by skills in photography and writing; categories of FB profile choices which are really based on FB needs for data for advertisers; you must use your real name so is an identity authenticator so cannot experiment with anonymous identities.

Life recognised by common ‘beats’: graduations/ coming of age etc. but can be very personal such as personal crises or fantastic experiences that fundamental changes  – a life change. You’re not deleting your past but reconsidering it and re-visit those experience. But these artefacts of your past can be used against you? While people will recognise that people change, the web does not forget and treat each ‘beat’ as occurring now. Online does not allow or consider how we might change and develop as a person or even have died.

But this is a human not technological problem to be resolved by people when we assess online information – information should be assessed by people. We don’e acknowledge that online information is partial and limited.

Educators at the frontline of digital technology use: don’t assume students have the skills to use technology; don’t use systems you don’t understand; encourage the use of multiple personalities for social development; be critical of technology and the information from technology. Engineers/ developers may not have your best interests; demand software works to meet your needs not the other way round; avoid being constrained by technologies; consider the concerns and biases of the developers when using software.

Highlights how we’ve developed effective media literacy over 200+ years but seeing biases in software and platforms is harder for us to understand including within the algorithms. So what is valued by software may not be what we, the user, values. Discomforting experience of being online is often that software assumes an immutable, singular and quantifiable identity.

Now we’re moving to Chris’ response:

Chris describes self as a fine artist working in digital spaces but finds doing the ‘self stuff’ difficult. Presents a model showing four interpretations of one living room by different people so things like the sofa and TV changes in prominence and importance. There is no consensual space.

As part of an internet of things project various sensors have been placed in Chris’s house including in the toilet. Also disrupts the domestic setting due to reinterpreting spaces in terms of collecting data.

Aleks positions this work as reflecting on ourselves through data and quantified self. But why have you chosen to do this?

Chris: its part of an ESRC project on digital economy and looking at the thing as part of an experience. The artefact can be part of the ‘beats’ of life. If ‘things’ are contextual we should look at correlated data from multiple ‘things’ that better captures the interactions.

Aleks: can’t see the point of much of internet of things except on data capture on eg, resource use. What is the politics of these technologies

C: interested in the disruption of this experiment. Recognises some of the concerns but also wants his children to be lead-users

A: focus on children makes mistakes and should be allowed to make mistakes but what does making a mistake online mean if the web doesn’t forget?


Q: ppl have always left snapshots but now leaving many more and are searchable but we’ve always understood the limitations of interpretations and so could transfer that understanding that the artefact is not the person to the digital age.

A: the key point is that it is now searchable and so raises that question of techofundamentalism  is that we don’t appear to recognise that technology is not neutral and don’t query where and how the information comes from.

Q: Zuckerberg has stated that privacy is dead but this is a normative statement, but is this possible?

A: no and Zuckerberg has created privacy around himself. To chnge attitudes and norms, there needs to be a lot more people saying the same thing – that privacy is dead – to change attitudes and behaviours of people.

Q: distinction between online and psychological identity – but both involve picking out from everyone else, in the former, by the etch and in the latter by the brain

A: people playing more with playing with sense of self online – could AI develop to the point that it could fool us in to thinking we were conversing with a person. But this is enormously complex and difficult. But people are getting closer, eg, sentiment analysis is slowly improving – combine AI and social science in a nexus that replicates an identity. But we don’t understand the brain and so difficult to reverse engineer. Also highlights that online identity is still some form of authentication of self.

Q: technology only cares about efficiency and that people are being taken over by a dictatorship of efficiency but the beats of life are not efficiency. Is it efficiency that disrupts our lives?

A: Great question! But social rituals can be a form of social efficiency. If we know someone is married that that signals that person has moved to a particular point in their life – interpretive efficiency – and so context specific. Although this is different from the quantitative basis of efficiency in software but how can software account for these softer notions of human efficiency.


…. just back from break.

Now up is Tim Fawns, e-learning coordinator for Clinical Psychology and is speaking on opportunities for deep reflection on collected data – and challenge the assertion that we don’t need to remember anything anymore.

Works on the notion of blended memory and that the external context and internal memory are co-dependent.

His research is on digital photography and memory as the practices and conventions on behaviours around photography are changing rapidly. Is talking today specifically on reflection in terms of linking with what we already know. Reflection takes time, energy and sustained attention.

Changes in photography have been rapid since 1990s and change to digital photography. By 2011 more photos were taken on mobile phones than stand-alone cameras.

We depend on photographs for our memory. Taking a photograph of an object impairs your memory of that object with looking at the photo. Does this matter? Well yes, if we don’t remember and reflect on events than we learn less  from experiences.

From his research noted that people took a lot of photos of significant events and that people are not very selective as few photos were deleted even if very poor images. People take so many photos that it may detract from the experience as well as saturated with images. People rarely did anything with the photos unless being used for something specific – forming a slide show or sending to others.

Flickr was used for broadcast purpose and little concern with you was viewing these images. On FB people tended to sanitise their discourses around the photos as may be not certain who would and could view the images and discussion of them.

So we’ve ended up with more information than we can process. Photography has shifted from preserving the past for future remembering to recording the present and moving on.

Some similarities to other technologies, ie, broadcasting to Twitter and a compulsion to be aware of everything going on in a network and the fear of missing something. Also has 322 articles stored on Mendeley and collecting articles that will never be led. Suggests that the more PDFs collected leads to fewer being actually read.

Discusses different image projects and memory maps as ways of reflecting. In an educational perspective, he points to multimodal assessments and how different components interact to be greater than the sum of their parts.

Again, emphasis that the issues/ concerns with surface reflection from technology is not a result of the technology itself but is rather a cultural context towards the surface and individual choices.

Q: confused by the changes in the talk between describing what we’re doing and what we should be doing. Which were you describing?

A: Both – we can see evidence of better behaviours of more reflective use and discussion of artefacts but also can see many examples of surface and unreflective use of technologies.

Q:  Reflecting on the quantified self trends and the creation of online data about ourselves and so wondered what the opportunities of technologies to support reflection?

A: as the tools approve, eg, facial recognition, tagging, you can start generating algorithmic analysis of your behaviours but the individual episodes remain the main point of interest.

Q: what might be the implications of technologies like blip-photo and snap-chat

A: these are interesting. Blip-photo is about recording one photo a day which is a strange way of recording a day. Snap chat as a response to privacy concerns but can promote  more negative behaviours, ie, sexting.


Now moving on to James Fleck on innovation and IT Futures.

Passion has been on innovation and technology development and has recently retired form the OU Business School.

Is interested here in notions of innovation and disruption.

Innovation as how ideas become real- for practical purposes and having impact. Innovation has been a field of serious study for 40+ years but has been on the margins of academic departments but is now centre stage and everyone is piling in. But while new ideas are emerging but also the rigour may be being diluted, especially in the use of the term disruption as meaning any level of change. So would like to look at what is innovation and disruption.

Innovation involves many components including individual characteristics such as creativity and problem solving but does extend to national systems. Risk-taking seen as important but innovators tend not to be risk-takers but rather know that their idea is good and requires persistence and resilience. Not failures but trials.

Context is important and systematic understanding of the industrial and policy context linking to innovation.

What are the key ideas in applying innovation to ICT:

  • incremental innovation: a linear model from invention to diffusion either as innovation push or market-led pull innovations. Used in consumer goods, car production, pharmaceuticals but not ICT
  • In ICT innovations tend to be in configuration and innovation is bringing different components together in a new way, also practices around the technology
  • mobile and platform technologies are a new categories. Points to the growth in mobile phone use across the world.
  • disruptive innovation – from Schumpeter’s radical innovation and creative destruction. Also a sense of discontinuity combining new technologies and how these are received (in terms of configuration with culture and society) – Christensen – some technology innovations bring in new markets and user and push out the older technologies. So the real issue is how the technology interacts with the users, eg, from mainframes to PCs; HE and the OU?


– the electronic newspaper changed interaction with news journalism which has now been realised through citizen journalism

– discussed a contraceptive aid based on measuring hormones in urine was a failure but a success when marketed as an aid to fertility

– the OU has very good student experience feedback despite low number of full-time staff. But courses are designed collectively and tested with students and relies on tutor support as learning content is a commodity and easily accessible. OUBS also able to develop a practice route by delivering work-based learning offer. But OU is not disrupting the HE system but rather sustains the system. The key component here is the pedagogy rather than the technology.

Looking at MOOCs, the numbers of students are comparable to 19 century correspondence courses or the downloads from iTunesU. What is different is the involvement of prestigious institutions. The key question is where is the tutor interaction, eg, the pedagogy and the content is secondary.

The system of HE with pedagogy at the core, interacting with practice, technology, policy, students, staff etc… is relatively stable over time.

In conclusion, technology alone is not disruptive but the wider context. HE has a very stable ecology of stakeholders and so is more resistant to disruption. Asks the question of what HE is for and places the learning lower down – priorities are for social networking, moving to becoming an independent adult, finding a mate, etc.

Technology capacity for capturing and storing data is increasingly growing and allows increasing access to material – Galileo’s note books as high resolution images available to all. We are all potentially innovators.


Now time for lunch …


Back from lunch and the closing key note from Cory Doctorow 

To start with a proposition that computers are everywhere and all things are computers. For example, the informatics building depends on computers and would not function as a building without computers, the same could be said for cars or a plane. And we increasingly put computers in our bodies, ie, cochlea implants but also personal music players … defribrilator implants also a computer.

Also, almost everything depends on computers for its productions.

We hear a lot about computer crime and failure. In part it is novelty, so of an interest in the way that clothes that criminals wear to commit their crimes are not interesting, So we hear a lot about regulating computers to fix their flaws and politicians use some heuristcs of where to apply regulations: (a) general technologies, eg, a wheel, are best not regulated; (b) if specific technologies can be subject to regulation so if we ban car drivers using mobile phones, the car continues to function as a car.

Computers are both general and specific and complex and have general properties that make them difficult to regulate.

Regulate the use of a computer by installing security software, DRM etc… but will allow a back door to  over-ride such software (but assume that only the ‘good’ guys will use the back door) .

Describes the notion of Turing Completeness that designs a computer or language to be able to run any programme computer.

Need to recognise that where no demand, that regulations in computers then this will be worked around/ subverted by people, eg, DRM, mobile phone lock-in etc.. But is illegal to show how this is done but people will find ways to subvert these constraints.

Is currently discussing basics of cryptography  and decrypting protected software as an illegal act. Cryptography used to force onto customers things that customers don’t want, eg, inability of DVDs to play in different regions, unskippable adverts (as the last place for unskippable adverts left). So these restrictions are key to business models. But also these restrictions constrain innovation – points to Open Software and Ubuntu as example of what innovations can happen when restrictions on adding feature and changes are removed.

Also, these constraints can be delivered as hidden software on computers that, eg, stop you ripping DVDs. But these are vulnerabilities to hackers and allow introduction of viruses.

Also, using laptop recovery  software used in law enforcement to monitor people eg, suspects, school pupils etc…used by law enforcement but also by criminals.

So the idea of installing the back door in PCs is the wrong response to the problems with computers as such back doors/ hidden software encourages new crimes to be committed. So that computers are vulnerable and this represents a crucial threat to individual freedom.

What to do?

Learn how to encrypt your email and hard drives but you’re only as secure as the people you interact with.

But also we should insist that digital infrastructure and regulations are robust and effective in protecting us – by joining the Open Rights Group; Free Software Foundation; Electronic Frontier Foundation.

MOOCs & flipping higher education

A quick few comments on a post from Donald Clark (via Scoop it):

Donald Clark has given ten reasons why MOOCs flip higher education. While he makes some valid points, the post itself is overly influenced by the hype surrounding MOOCs and does not really provide a justification for how MOOCs address the problems he identifies in HE (deficiencies in pedagogy, some poor teaching and high costs). I particular: flip 2 suggests almost that MOOCs have been imposed on HE from outside rather than developed by HE; flip 4 from teaching to learning has been going on for a long time and certainly is embedded in the higher quality online (and face-to-face) programmes; flip 5 on assessments is pure conjecture as there are no actual MOOCs I’m aware of that provide for recognised credits (as in part of a national qualifications framework); flip 8 on criticism, yes some criticism is ridiculous but the credibility of MOOCs as learning has yet to be established, but the main criticism of monetisation is important (at least for the platform providers and VCs) and its hard to see how ROI can be established. Its the same for HEs but HEs may be involved for reasons other than as money-making opportunities (reputation enhancement, experimentation and innovation)
Fundamentally, the assumption that MOOCs have succeeded (and succeeded in what?) is not clear to me. Having said that, there are lots of good points here on online learning being as good or better than face-to-face, on the potential to drive greater responsiveness to demand for HE; being more learner-centric (and that’s before looking at a feudal timetable of HE and the balance of teaching vs research in reward and recognition in the sector. All good and interesting stuff but lets engage with what we know about MOOCs rather than what we’d which about them.

Satisfaction with digital education

I came across this survey from Gallup on student satisfaction with digital higher education. The findings make interesting reading from a number of perspectives. While the value-for-money and breadth of curriculum of online learning is clearly acknowledged as key strengths by students. More important are the perceived weaknesses in terms of the quality of teaching, rigour of assessment and credibility with employers.

Also worth noting is that while both four-year degree universities and community colleges are seen to provide good or excellent education:

Americans’ overall assessment of Internet-based college programs is tepid at best. One-third of Americans, 34%, rate such online programs as “excellent” or “good.” The majority calls them “only fair” or “poor.” In contrast, two-thirds of Americans (68%) rate four-year colleges and universities as excellent or good, and nearly as many (64%) rate community colleges this highly.

Also interesting in terms of MOOCs and badging of skills and learning was the finding that…:

half of Americans currently believe that obtaining the knowledge and skills needed to perform a specific job are more important for young people today than earning a college degree from a well-respected university. This broadly suggests that online programs offering more targeted curriculum — distinct from a traditional bachelor’s degree — or even certification in specific skills, could ultimately transform how students approach postsecondary education.

The survey indicates that from a market perspective, online learning has a way to go to have the authority to disrupt higher education but perhaps has more potential for professional learning and development.