Tag Archives: e-learning

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.

eLearning@ Edinburgh

I’m attending the eLearning@Ed 2015 conference and will be attempting to live blog throughout the day.

Melissa Highton, Director of Learning Teaching and Web Services here at Edinburgh is starting the conference and the theme of Designing for 21st Century Learning. Wanted to ask what 21st century learning might be and how it might be different from 20th century. Many aspects of learning and education have stayed the same, but differences around scale, technology, teachers and teaching and, in particular, “its not ok to not understand the internet anymore”.

Highlighting some trends in the sector from the New Media Consortium with trends around maker spaces, changes spaces for learning, BYOD, personalised learning and the wicked problems of recognition and reward for teaching.

Now moving on to a panel of Chairs in Digital Education on views of 21st century learning.

First up is Judy Hardy, School of Physics and Astronomy with personal view and concerns. Looking to the student experience in 2020 and what will it be like. IN many ways, it will be very similar to now: lectures, workshops and tutorials and self-study. But there will be much more extensive use of digital technologies. Uses an anecdote on research methods for honours students that includes a self-reflective assignment and many used cloud based tools and Facebook groups and these sorts of tools and working methods will be mobilised. Also cited research on active engagement in classroom teaching against more traditional (didactic) learning design that shows active engagement has massive benefits to learning achievement.

But why is there lecturer resistance. Cited a survey showing lecturers want to teach and take pride in their teaching competences. So what are the challenges: time – which is a proxy for many things; and pedagogical context, where innovations abandoned early or perceive too much choices. So there are challenges of awareness; ‘how-to’ knowledge and why innovations in learning are important – ‘principles’ knowledge – and understanding these three forms of knowledge are crucial to implementing improving teaching.

Next is Sian Bayne based in the School of Education and Prof of Digital Education. Sian’s talking about Dave Cournier’s Rhizo Mooc, that included Tweets on one of Sian’s papers that was a set reading. The paper was about striated and smooth space in online learning: striated spaces is formal, goal-orientated and ordered while smooth space is nomadic, open and wandering-orientated and these two metaphorical spaces do merge and their boundaries blur. We can map learning spaces on to striated and smooth spaces: striated spaces as VLEs/ LMS and smooth spaces as hypertext, linkages, multimodal assessments, wikis and blogs.How do these metaphors work in 2015 and we continue to have striated spaces in VLEs, progression, e-portfolios, personalisation, adaptive learning, learning analytics, gamification. But also increased smooth(er) spaces such as Twitter, YikYak, augmented realities, flipped classrooms, maker spaces, crowd-based learning. The bigger point is that this field is predominately future orientated with lots of trends forecasts which generates a change acceleration to adapt practices to the ‘next big thing’. But trends are contingent on the situated context (the University of Edinburgh) leading to questions of what sort of institute we want to be and what is the purpose of higher education.

Judy Robertson, Chair in Digital Learning talking about current work and using technology to support learner goal setting. A lot of her work involves user centred design for mainly school pupils related to behavioural change in education and in public health.  Typically games set goals for users but the interest here is user goal setting and setting appropriate goals. Currently developing a game to encourage behavioural change to increase activity levels. Can also be extended to realistic goal setting for students in their study skills. So the question is on designing technology to be helpful but not intrusive.

Critter Jam (FitQuest) is an exercise game for a mobile phone to encourage children to run around. The game includes being chased by a virtual wolf, or to pick up virtual coins. Children can select different goals such as topping the leader board, beating your PB, setting points targets (but how to select an appropriate points goal?). Her research is on self-efficacy and in patterns of goal setting related to increased performance. Also links to resilience in context of goal failure and adjusting goals accordingly – and this could be adapted to, for example, undergraduates.

David Reay from Geosciences and talking on distance education and the development of the MSc in Carbon Management involving the Schools of Business, GeoSciences and Economics. There was a clear demand from students for applied experience and so developed online learning as a response. Initially, developed a role play simulation with face-to-face learning and developed this for online learning that was delivered as part of the MSc in Global Challenges. So now there is a full online MSc in Carbon Management launching in September. He is also developing an online course in sustainability for campus based students linked to graduate attributes around understanding sustainability. Each student will look at sustainability in their subject area to understand what sustainability means and have an excellent online learning experience. His research is on climate change including online teaching and conferencing in terms of its environmental impacts including measuring the total carbon emissions for the online programmes. The intention is to off-set carbon emissions generated by the programme – to be the greenest masters ever!

Dragan Gasevic, Professor of Learning Analytics at the Schools of Education and of Informatics. Why learning analytics is important: especially in provision of personalised feedback loops for students that acknowledges their diverse needs. We use VLEs/ LMS but also rely on many other digital technologies for learning including on the web, using social learning, reflective learning through annotation technologies and blogs. In using digital technologies we are leaving a digital footprint. We have been collecting some of this data since the start of universities. We want to leverage this data to assist teaching, learning, policy-making etc. and this is the point of learning analytics. Learning analytics is about learning and this must not be forgotten – not just data crunching for its own sake but is purposive. Learners are not black boxes but are individuals with many different and not permanent traits, knowledge and understanding, The black box needs to be opened up to deliver the benefits of learning analytics. Looks to CLAS – collaborative lecture annotation system – but the key is to encourage learners to use beneficial technologies. So we have a duty to inform students on the benefits of a technology and to scaffold support for the students to use that technology. Found that students were more engaged with technologies in graded courses and came to internalise the use of the tool in either graded or ungraded courses. So if we teach our student to use a tool they will continue to use that tool even if that use is not required. Learning analytics support and validate pedagogy.

“Counts don’t count much is decontextualised”! We need to account for pedagogical context in learning analytics. Also, visualisations can be harmful especially in showing visualisations to learners/ students so we need to develop analytics literacy for students. We also need to scale up qualitative analysis to improve understanding of learners and to develop institutional policies to support the use of analytics. But the use of learning analytics is contingent for each institutional context – one size does not fit all!

Jonathan Silvertown, Biological Sciences, is talking about the project ‘virtual edinburgh’. The project will turn the city in to a pervasive learning environment for formal and informal education. The future is already here – such as WiFi on buses but also apps such as Walking through Time, LitLong (Palimset), Mesh, iSpot etc.. but virtual edinburgh will also allow interaction between users. Also look to the ‘nearby’ function on Wikipedia. These apps and functions will be linked together through virtual Edinburgh and draws on the teaching and learning strategy priorities on giving learners agency and providing technology to do that. Modes of interaction will involve existing and new apps, peer interaction, game play, new data layers, mashups etc. that can be used in courses or as part of self-directed (informal) learning. The ultimate objective is to create Edinburgh as the City of Learning.


Question: One of the themes is on student digital literacy and what baseline of literacy should we expect students and staff to have?

Judy R: That’s a really interesting question as we cannot assume that students will know how to use it for learning.

Judy Harding: we need to think about how institutional and personal technologies are used with, perhaps students preferencing their personal technologies.

Dragan: the focus should be on study and learning skills and these will not change but that abilities may decline in these due to the affordances of new technologies.

Dave Reay: confession on start of online course assumed students would know about and be able to use particular technologies. Preparation with students is key.

Sian: the research busting the idea of the digital native. The evidence is that what students come to the university with is less important than what we expect them to do. As many of the talks have suggested, the context is key.

Question: on engaged learning[??]

Judy H: the flipped classroom is important in using the technology to engage with larger cohorts of student as the large lecturer will not disappear.

Question: teach honours and postgraduate students and trying to get students to use newer technologies and if not introduced to these technologies earlier, then it may be too late in learning to use these technologies for learning.

Judy H: do we need to be more explicit in encouraging students to develop relevant technology skills in students.

Dave Reay: this will improve in patches and should be a question for programme convenors to develop online learning experiences in degree programmes.

Dragan: we have academic autonomy and so top-down solutions will not work. We need to consider what technologies academics are aware of and can use and so what incentives are provided to encourage the use of technologies. Suggests greater emphasis and recognition of teaching.

Question: what learning technologies are we developing taking account accessibility and the ethical responsibilities of the university.

Dave Reay: the technologies and online courses increase the accessibility to the programmes to new and different students. Avoids some of the challenges of cost, visas, personal circumstances.

Sian: need to differentiate between learning and education – wanting to learn is different from seeking qualifications via formal education.

Dragan: accreditation is an important factor. Also students don’t just come to edinburgh for the content but also for the experience and networks. Online learning also needs higher development abilities at self-regulated learning. We also tend to think in terms of credit hour rather than outcomes and this can be seen in shifts towards competence based education including graduate attributes.

Question: what practical measures could be taken to keep academic staff up to date with what is happening with learning technologies at schools level

Judy R: CoE does include technology in primary such as using Microsoft office but also extreme paranoia about anything social online and allowing pupils outside the walled garden of eg, GLOW

Judy H: not all out students come through the Scottish education system and we need to encourage self-regulated learning for students coming from a vast range of education systems.

Jonathon S: that would be a goo topic for the conference next year.


We’re back from a break with Dash Sekhar, VPAA and Tanya Lubicz-Nawrock from Edinburgh University Students Association on “Co-Creation: Student Ownership of Curriculum”. Starts with the many forms of student engagement such as Kuh’s focus on time and effort aligned to institutional desired outcomes and Bovill emphasises respect, reciprocity and shared responsibility between students and academics.

Co-creation operates on a continuum  from student feedback/ evaluation to students as experts of their own learning experiences expressed through student representations to Co-Creation of the Curriculum. So Co-Creation is a mutuality between students and academics and so shifts power relations between staff and student.

Putting the ideas of co-creation in to action through student-led content where students create their own projects to meet learning outcomes and assessment criteria. Technology allows for more flexible and remote learning.

Student partnerships in assessment: where students select and negotiate the assessment components and weighting to create sense of joint ownership of the assessments. Involved a democratic process for selecting the final assessment process.

Social bookmarking: in a statistics course where as a part of the course, the students had to tag sites and posts related to the course content. These posts were used in a running ‘live feed’. While fairly surface, this involved a shift in how students relate to course content.

We’re now moving to small group discussion so I’ll stop here and be back later. 

Group work over and we’re on to Prof. Ian Pirie, Asst Principal Learning Developments on the use of portfolios and e-portfolios in art & design. Simon Riley (CMVM) will talk about portfolios in medicine. Portfolios are used to demonstrate research, process, methods, outcomes etc. and curate a portfolio for submission for assessment. Portfolios a central to the method of art & design education in the context of sustained practice including art, design, architecture, medicine, engineering, healthcare etc. linked to demonstration of competence.

In the case of art, design & architecture, the portfolio is used from recruitment to almost all assessments. Portfolios include all forms of media and is crucial in entry to the next stages of education and in professional careers.

Simon Riley, on portfolios in medicine. Medical education governed by the GMC as a competency-based curriculum with an interest in allowing student choice.  To enable the student choice element of the curriculum, portfolios were adopted since 1990s.

The university curriculum is closely mapped to the GMC requirements. The different themes of the curriculum is pulled together through the portfolio. Portfolios include case reports, essays, project reports, reflective analysis of professional skills, reflective analysis of experiences, assessment (by viva) and project organisation. The reflective analysis components continue to have room for further development.

There is also a professional development portfolio including capturing the graduate attributes using Pebble+ in parallel to the programme portfolios.

Gives the example of a Group Project that uses an open WordPress site. This involves the collection and synthesis of information and knowledge.

The portfolios are being used for the demonstration of competence and reflection. Portfolios also train students for progression to postgraduate study and professional development. There is a huge amount of commonality between how medicine and art & design use portfolios.

Back to Prof. Ian Pirie on the share pedagogy based on Kolb’s model of experiential learning. In the remaining time, the range of eportfolios being used at Edinburgh are shown. A key issue is transferring the ePortfolio so students can use them outside and after their University forum.


Melissa Highton is in the last slot before lunch to talk about Open Educational Resources: new media for learning, and recent developments on OER at Edinburgh.

Openess is seen as a bold and positive move for the University. Initially, the University set up a task group on the development of an OER strategy. OER underpins a lot of the themes of this conference. The task group involved a range of academic and support services stakeholders. Cites the Capetown declaration of 2007 as a fit with stated intentions around sharing and developing knowledge. This sharing of knowledge and learning resources is enabled by technology. But resources need amending to the local context and we’re not sure if this is possible/ legal. There are also strong opinions that publicly funded resources should be open.

A problem with the word ‘open’ is that it means different things: available, available online, accessible. There is a definition of open: “open data and content can be freely used, modified and shared by anyone for any purpose”. There is a need for rigour in the definition in apart to manage the reputational risks of stating that the university is using open resources and that staff understand licensing and sharing and publishing of material. Licensing tends to be on Creative Commons licenses which fits nicely with the notion of teaching as a creative act – and this is a growing phenomena with 882million items on CC license in 2014 from 50m in 2006.

Fourteen countries have made a national commitments to open education including Scotland. CC licensed material is available from all over the world – which would help in internationalising and diversifying the curriculum.

Edinburgh has launched open.ed as open content resources. Also CC licenses allow us to renew and amend any resources so as technologies change, resources can be updated and so are sustainable.

…. and now its time for lunch….and I’ll have to finish here as I’ve run out of power and that plug points don’t work… 

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.

Personal learning environments

Network ALL2_BC
I’m currently writing up some ideas on open online professional learning that includes considering  personal learning networks. I came across this interesting post from Martin Weller on the apparent decline in interest or discussion of personal learning networks. The reasons suggested include the mainstreaming of the practices associated with PLEs, a consolidation of the tools used in to a fairly generic set of software used but also that the (research) agenda has shifted from personal learning to institutionally provided personalised learning partly driven by learning analytics.


MOOCs automation, artificial intelligence and educational agents

Geoge Veletsianos is speaking at a seminar hosted by DiCE research group at University of Edinburgh. The hastag for the event is #edindice and the subject is MOOCs, automation and artificial intelligence.

[These notes were taken live and I’ve retained the typos, poor syntax and grammer etc… some may call that ‘authentic’!]
George began by stating that this is an opportune time for the discussion as MOOCs in the media, the developments on the Turing Test and MIT media lab story telling bots used for second language skills in early years or google’s self-driving cars. Bringing together notion of AI, intelligent being ets.
Three main topics: (1) MOOCs as sociocultural phenomenon; (2) autonomation of teaching and (3) pedagogical agents and the automation of teaching.

MOOCs: first experienced these in 2011 and Change11 as a facilitator and uses them as object of study for his PG teaching and in research. Mainly participated as observor/ drop out.

MOOCs may be a understood as courses of learning but also sociocultural phenomena in response to the perceived failure of higher education. In particular, MOOCs can be seen as a response to the rising costs of higher education in North America and as a symptom of the vocationalisation of higher education. Worplace training drives much of the discussion on MOOCs as illustrated by Udacity changing from higher ed to training provider and introducing the notion of the nano-degree linked to employability. Also changes in the political landscape and cuts to state funding of HEIs in the USA and the discourse of public sector ineffieciencies and solutions based on competition and diversity of provision being prefered. MOOCs also represent the idea of technology as a solution to issues in education such as cost, student engagaement  and MOOCs as indicative of scholarly failure. Disciplines and knowledge of education such as learning sciences not available many as knowledge locked-in to costly journals, couched in obscure language. MOOCs also represent the idea that education can be packaged and automated at scale. Technologies seen as solutions ot providing education at scale, including TV, radio and recording lectures etc. so education is seen as content delivery. 
Also highlighted that xMOOCs came out of comp sci rather than education schools and driven by rubics of efficiency and autonomation. 
Pressey 1933 called for an industrial revoluation of education through the use of teaching machines that provide information, allow the learner to respond and provide feedback on that learner response. B.F. Skinner also created a teaching machine in 1935 based on stimulous/ response of lights indicating whether a response is correct or not. 
Similarly MOOCs adopt similar discourses on machine learning around liberating teachers from administration and grading to be able to spend more time teaching. So these arguments are part of a developed narrative of efficiency in education.But others have warned against the trend towards commodification of education (Noble 1988) but this commodification can be seen in the adoption of LMS and “shovelware” (information masquarading as a course).
Automation is increasing encrouching in to academia via eg, reference management software, Google scholar alerts, TOC alerts from journals, social media automation, RSS feeds, content aggregators (Feedly, Netvibes) and programming of the web through, for example, If This Then That (IFTTT). 
As a case, looks at the Mechanical MOOC that are based on assumptions that high quality open learning resources can be assembled, that learners can automatically come together to learn and can be assessed without human involvement and so the MOOC can be automated. An email schedular coordinates the learning, OpenStudy is used for peer support and interactive coding is automatically assessed through CodeAcademy. So attracts strongly and self-directed and capable learners. But research incates the place and visibility of teachers remains important (Ross & Bayne 2014). 
Moving on to educational agents as avatars that present and possibly respond to learners. These tend to be similar to virtual assistants. Such agents assist in learning, motivation, engagement, play and fun but the evidence to support these claims is ambiguous and often “strange”. In the research, gender, race, design and functions all interact and learners respond often based on the stereotypes used in human interactions. The most appealing agent tending to have a more positive effect on learning. Also context mediates perceptions and so how pedagogical agents are perceived and understood. 
The relationship between the agents and learners and their interactions is the subject of a number of studies on topics of discussion and social practices. Found that students and agents engage in small-talk and playfulness even though they are aware they are interacting with an arteficial agent. Also saw aggressive interactions from the learners, especially if the expert-agent is unable to answer a query. Students also shared personal information with the agents. Agents were positioned in to different roles as a learner companion, as a mediator between academic staff and learner, as a partner.
So social and psychological issues are as important as technology design issues. So do we need a Turing test for MOOC instruction? How we design technologies reflect as well as shape our cultures. 
//Ends with Q&A discussion

Learning Insights ….

Kineo, the e-learning company, have issued a new report on e-learning insights based on interviews with “learning leaders” to identify key emerging trends. I’m not going to repeat the report but will look at a few of their ten key insights:

1. Learning is pervasive. Learning is continuous, collaborative and connected and most learning lives outside a learning management system. This has implications for the learning architecture and intervention models adopted by Learning and Development departments.

ZypadI see this as a key insight. Not as some new trend in learning but rather as something that L&D is (finally) waking up to. Most learning at and for work occurs through working: by solving problems; collaborating with others; being challenged and being observant. Much of this learning occurs vicariously and by serendipity and well outside much of the activities and service offers of L&D functions. The weaknesses were always that organisations were failing to understand that all this learning was going on and that staff weren’t being recognis

ed for making this learning happen. In addition, learning and knowledge was being lost because no attempt was made to capture it, staff were not always making best use of it as learning wasn’t either intentional or the main goal and also that employees had under-developed capabilities in “learning to learn“. What *has* changed is that digital technologies, especially digital working, has made such learning and knowledge more visible and these informal learning processes more transparent.

4. Design higher empathy learning. …It is not so much about meeting learning objectives as about empathy with the learner, their position, their challenges and personalising their experience.

Which I take to mean L&D should seek to get the right knowledge to the right people at the time they need to use it … No argument here and this may well prove to be a crucial focus for future developments around predictive learning analytics; knowledge management and knowledge resource development and work/ learning integration.

7. Informal learning must not become chaotic. There is a danger with the pervasive nature of learning and the wide range of informal opportunities that learning can become chaotic.

Is an interesting pronouncement but I’d argue not a key issue as most workers will be seeking to get the job done to the best of their abilities. L&D should be concerned with developing an enabling infrastructure, establish baseline (learning to learn) competence in employees but then largely get out of the way.

10. Where web technology goes, learning will follow. It is difficult to overstate the degree of change in web technology.

This seems to me to point to a shift from LMS  to Personal Learning Environments/ Networks that span the boundaries of any organisation and where significant components are owned by the employee – see Jane Hart’s post here

Its an interesting a useful report.


[Image of the ZYPAD, rugged wrist wearable computer from Arcom Control Systems licensed under the Creative Commons Attribution-Share Alike 3.0 Unported]

LinkPool [16012014]

I’ve been back to work for four days now but today was the first day of feeling inspired and quite happy to be back (possibly due to ‘home improvement’ hassles earlier in the week). Anyway, this is not an extensive post but I found a couple of useful reads this week:

An e-learning strategy framework caught my eye mainly for the statement that:

I realized that this manager was under the impression that her learning management system (LMS) was her e-learning strategy. Several years ago, Brandon Hall said that an “LMS is the lynch-pin of an e-learning strategy,” but technology alone is not a strategy.

Which is a nice illustration of the common problem of technological determinism. But the framework presented discussed organisational goals, MarComms, administration, audiences and finance yet nothing on pedagogy. Can an e-learning strategy framework that doesn’t address questions of how users learn be adequate?

The Vulnerability of Learning from @gsiemens via @mhawksey caught my eye as something rarely stated but very true:

Learning is vulnerability. When we learn, we make ourselves vulnerable. When we engage in learning, we communicate that we want to grow, to become better, to improve ourselves.

And the same can be said of other valuable learning processes of creativity and innovation – there is a link between making oneself vulnerable and doing what is valuable. As George suggests, the logic of efficiency may well end up destroying what makes learning valuable personally and socially.

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.

Learning innovations and digital education

An interesting report on Technology Enhanced Learning (TEL) from Open University based academics. The report discusses:
1. what is TEL but in terms of technologies “add value to” (enhancing) teaching and learning rather than being indivisible from or enmeshed in teaching and learning. Can you imagine teaching and learning without any technologies (digital of otherwise)? This section does include some useful references to the European and UK policy frameworks including networks such as STELLAR. The framing of education in terms of being a service, as media production and broadcasting (xMOOC?) or as a conversation is useful. The discussion of the education system as being stable and acting as a ‘constraint’ on digital education innovations is also useful – that the education system is the more powerful network and slower to transform which affects what is possible in terms of digital-led innovations in education. So analysis of innovations in digital education should be framed by an understanding that:
New technologies follow complex trajectories often supported or thwarted by other technologies, infrastructural issues, competing standards, social systems, political decisions, and customer demands. [p17].
The report goes on to note that the web was started at CERN as a tool for learning through information sharing. The emphasis here is on innovation occurring within contexts of communities, practices as well as technologies. The discussion of success stories includes mobile learning pointing to the MOBilearn project supported by the European Commission as well as the BBC’s Janala language learning service but doesn’t really discuss the growth of smart phones and tablets as means of going online. In effect, learning technology design needs to be responsive to the requirements of these devices. Other success stories cited include Scratch and xDelia.
In examining the situation for research and innovation in digital education, the report points to certain disadvantages compared to other ‘scientific’ areas in terms of the coherence of the research agenda and the lack of a single focal point for innovation such as a single technological solution. The report notes the difficulties of creating a compelling narrative around how technologies are used to enhance learning. The report notes that: there is a need to reassess the use of computer technology from an educational, rather than a technological, perspective; and develop a more sophisticated conceptual model of how ICT can facilitate teaching and learning in the classroom..[p23]. The recommendations on experimenting in how technologies can be used to enhance informal learning (in the corporate sector), in ensuring research findings are made available inside and outside HE and that research is increasingly undertaken as applied research (mode 2 knowledge production) are welcome.
The section on the innovation process in TEL positions innovations involving pedagogy and technology combining in to emergent practices supported by communities of practitioners operating within wider sectoral ecologies and contexts. Given the emphasis on practice and complexity, the report finds TEL innovations depend on innovators as bricoleurs as someone who makes do with whatever is at hand. However, successful innovations depend on bricolage that also takes the wider learning complex into account and where innovations can take decades to diffuse fully. The report goes on to promote a design based approach to research and evidence-based innovation.
While making a number of recommendations for researchers and [research] policy-makers, the report concludes The focus for future TEL research should be on effective transformation of educational practices, rather than small incremental improvements.

Mobile learning at work

An interesting post from Graham Attwell on mobile learning that quotes Donald Clark:

Training Magazine’s annual survey of US L&D professionals shows that just 1.5% of training was delivered via mobile devices. That’s right, after about 7 years of hype and discussion we’ve reached 1.5%. That’s not leaping. That’s trench warfare.

The issue here is partly framed in terms of the Learning and Development function that remains in a training course mentality rather than supporting workplace performance and situated knowledge development, generation and sharing. Graham makes the interesting point that the potential of mobile tech is in supporting an environment of learning and …

to link learning that takes place in different contexts. That mean linking formal learning to informal learning. And to link learning that take place in vocational schools, in training centres and in work.

But this potential is not realised, in part due to the attitude of employers or their failure to understand how such technologies are being used anyway by their workforce:

A recent survey we undertook on over 500 construction apprentices in Germany found that whilst over 50 per cent said they used their mobiles for finding information related to their work or training, only 20 per cent said their employers allowed them to do so. They said that they used the devices in their breaks and lunch time. And in construction I would argue that mobiles are a working tool anyway. So part of  “establishing good practice in our organisations for finding information and experts and for sharing information”, is a task of awareness raising and capacity building with companies for them to realise the potential of mobile technologies for their organisation.