The Myth of the Digital Native?

In 2006 Anoush Margaryan , Kathryn Trinder and I led a project funded by the UK Higher Education Academy exploring the notion of learners as 'Digital Natives': Learning from Digital Natives . The final report was released earlier this year (2008).

Anoush has been reanalysing the data to find out the nature and extent of students’ use of digital technologies for formal and informal learning and socialisation. We have also been focusing on lecturers’ perceptions of the educational value of these tools and their views on the barriers and enablers for using technologies to support learning.

Our findings suggest that, compared with older students (so called Digital Immigrants) younger students do, indeed, make more recreational use of social technologies such as media sharing tools and social networking sites. However, their use of and familiarity of collaborative knowledge creation tools, virtual worlds, personal web publishing, and other emergent social technologies for learning is fairly limited.

The study has not found evidence to support the claims in relation to students adopting radically different patterns of knowledge creation and sharing. In fact students’ attitudes to learning may be influenced by the teaching approaches adopted by their lecturers.

Far from demanding lecturers change their practice, students appear to conform to fairly traditional pedagogies, albeit with minor uses of technology tools that deliver content. These outcomes suggest that although the calls for radical transformations in educational approaches may be legitimate it would be misleading to ground the arguments for such change solely in students’ shifting expectations and patterns of learning and technology use.

Some results are summarised in a presentation and a draft paper Are digital natives a myth or reality?: Students’ use of technologies for learning

Goals and self-regulation again

In discussing self-regulated learning with colleagues – focusing on Boekaert’s 2002 paper - I incautiously remarked that the teacher needed somehow to bring the students’ goals in line with academic goals – and was immediately pounced upon for being old-fashioned and teacher-centric in my views. This incident highlights for me one of the fundamental problems with self-regulated learning and the concomitant idea that by developing students as self-regulated learners we improve their employability. The problem is that one can take a very student-centred approach to learning, and be entirely symmetrical in ones view of student-teacher interactions (indeed, this is my preference), and may have highly self-regulated students. However, the definition of “learning” is still asymmetrically in the hands of the institution, as interpreted by the teacher or assessor, just as the definition of “employable” is ultimately in the hands of the employers. Even if student-teacher interactions are symmetric, the contextual definition of learning is not. Highly self-regulated students may have goals that are very different from those the institution or employer would wish them to have - in this case they will not be recognised as self-regulated learners and may appear totally unemployable. Equally, they may adopt the goals of an HE institution and count as very competent self-regulated learners, but never adopt the goals of an employer and remain unemployable (or vice versa). Because of this contextual asymmetry, if the hallmark of a successful teacher is that their students become self-regulated learners, then it still seems to me that this is probably due to something the teacher has done to encourage (somehow) the student to adopt the institution’s or teacher’s goals. A fundamental issue, then, in developing self-regulated learners or employable graduates is the study of how or why students adopt an institution or employer’s goals as their own.

CalShell Partnership Event

Yesterday we hosted a short event here at the Caledonian Academy centred around our action research partnership with Shell International. Mark Batho, Chief Executive of SFC spoke on the need for universities to supply graduates with appropriate skills, and Dr Sebastian Graeb-Konneker of Shell provided some personal thoughts on making the transition from Academia to the eneterprise. For our presentation, Allison, Anoush and I provided an overview of our work with Shell centred on the ideas of collective learning and charting which have been developed and explored as part of the project.

Our slides from the event are available on slideshare and embedded below:

Cal Shell Partnership Event 131108

View SlideShare presentation or Upload your own. (tags: create connect)

Further details about our work with Shell can be found at: http://www.academy.gcal.ac.uk/calshell/

We are hiring: A PhD Fellowship

PhD FELLOWSHIP (Full-time)

Learning from incidents: A social approach to reducing health and safety incidents in the workplace

Caledonian Academy, Glasgow Caledonian University www.academy.gcal.ac.uk

Purpose of fellowship

The Caledonian Academy, in collaboration with the UK Energy Institute (EI) and Shell International BV, is offering a 3-year fellowship to carry out research leading to a PhD investigating and developing new approaches to enhancing learning from health and safety incidents in the industrial workplace. This PhD fellowship is funded by the EI and will be jointly supervised by Caledonian Academy, EI and Shell. The research will be conducted in 3 real-life testbeds in Shell, BP and ConocoPhillips. The fellowship offers a unique opportunity to work with three leading, global corporations as well as an internationally-renowned research team.

Research project

Learning from incidents is embedded in the culture of organisations. The premise of this study is that incidents will be reduced by embedding learners into a culture where continuous learning is promoted (a generative organisation). A strong mechanism to achieve a generative organisation can be found from social constructivism. Social constructivism stresses dialogue in learning, with this taking place via an active process of constructing meaning. By following a participatory Change Laboratory methodology, workers, in collaboration with the researcher, will develop a deep understanding of why incidents have occurred and how they can be prevented in the future. Applying deep learning into practice will help develop a safer workplace environment and create a generative organisation.

Remuneration

There is a stipend of £13,900 per annum in the first year, rising to £14,746 in year 3. Each year’s stipend shall be payable to the fellow in four equal quarterly payments on 1 October, 1 January, 1 April and 1 July respectively of each year. In addition, the funding organisation will cover fellow’s PhD fees. Travel and subsistence expenses for carrying out data collection, progress and evaluation meetings in the testbeds will be covered by the funder/sponsoring organisation. The fellowship will also cover a conference visit, as well as residence permit costs for international student and training in workshop facilitation/Change Lab method. Glasgow Caledonian University will provide desk space and amenities.

Duration of fellowship

The fellowship will begin in the first quarter of 2009 (negotiable) and will last for 36 months.

Education/Experience sought:

The fellowship is open to candidates from any country. Applicants must be graduates (Masters or Bachelors Degree plus relevant Masters) with a background (and interests) in Educational Science & Training and its sub-disciplines. Candidates with a background in Social or Behavioural Sciences are also eligible to apply, but a strong interest in Education and Training is essential.

· Experience (or strong interest) in socio-cultural approaches to learning and participatory research methods is necessary. Experience in using Change Laboratory method is not compulsory but would be an advantage. Familiarity with case study methodology will be highly valued.

· Experience (or strong interest) in technology-enhanced learning is desirable. In particular this involves application of emergent social technologies, games and simulation and virtual worlds for learning.

· Familiarity with relevant research on workplace learning, organisational learning, health and safety, motivation, sociology, ergonomics, and/or organisational psychology is a plus.

· Practical understanding of corporate learning context is desirable.

Skills:
We are looking for a smart, dynamic, curious and motivated person who has the following skills:

· experience, or interest in, conducting original qualitative research

· strong writing and oral presentation abilities

· ability to work to strict deadlines

· ability to communicate research findings efficiently to both academic and corporate audiences

· skills in workshop facilitation are desirable

Application Materials and Deadline:

Applicants should submit the following documentation by e-mail to Ms. Fiona McBeth Fiona.mcBeth@gcal.ac.uk

*Letter of interest
*CV/Resume

*A writing sample (500-1000 words)
*Names and contact information of two references (professional and/or academic).

Deadline for applications is November 28, 17:00 GMT. Interviews with shortlisted candidates will be conducted in December 2008.

Additional information

The PhD fellowship will be supervised by Professor Allison Littlejohn, Director of the Caledonian Academy and Dr Anoush Margaryan, Lecturer in Learning Technology at Glasgow Caledonian University (www.academy.gcal.ac.uk/people), along with two corporate supervisors.

Contact

Those seeking further information should contact Prof. Allison Littlejohn, tel: +44-141-331-8409, email: allison.littlejohn@gcal.ac.uk

EU Marie Curie proposal submitted

A group of us at the Caledonian Academy submitted a proposal for a Marie Curie European Initial Training Network (ITN). The proposal is to establish a research and training programme in the area of self-regulated learning and adaptive social technologies.

The proposal is led by Glasgow Caledonian University, in collaboration with eleven leading academic and industry partners in six countries (UK, Netherlands, Austria, Germany, Estonia, Australia). This interdisciplinary network integrates 11 research projects with a comprehensive training programme.

Full title: Learn to Work(L2W): Enhancing self-regulated learning in transition from education to the workplace.

Call: FP7-PEOPLE-ITN-2008
Coordinator: Caledonian Academy, Glasgow Caledonian University

Partners: Eindhoven University of Technology (NL); University of Karlsruhe (Germany); Technical University of Graz (Austria); Tallinn University (Estonia); University of Canberra (Australia); Innovation Services Network (Austria); Shell Learning (NL); National Centre for Research Methods (UK); Know-Center (Austria); PROLEARN/EATEL (EU).

Environment and self organisation

As you’ll have gathered, I’ve been pre-occupied recently with self organisation, self regulation and learning. Thus two phrases leapt out at me when my Planet project colleague, Yishay Mor, blogged about Europlop 2008.
“Funny thing, how social scientists will stand before a hall full of neatly packed passive listeners and preach about collaborative constructivist learning, while the computer scientists just do it.”

“EuroPLoP 2008 also leaves ample space and time for the real work of conferencing, the stuff that can’t be captured in predefined structure, because it emerges out of the discussions at the time and place.”

For Yishay, then, working in a research context, the really valuable process is self organisation rather than regulation (whether by self or others). I note, though, that for the outcomes of self organisation to be useful research ideas the environment has to be structured in an appropriate way – which implies a fair degree of control or regulation of the environment and an understanding of the types of environment that encourage effective emergent behaviours - or, in memetic terms, a knowledge of the types of environment that will select useful behaviours. So, for the conference to be a success, the environment is controlled although the entities within it are not. Perhaps, though, even here the environment is less controlled than at a conventional conference? Is deliberate absence of control, in itself, a form of control?

I’m not entirely convinced by the memetic, selection, interpretation. It is not clear to me why a relatively uncontrolled environment should select useful research behaviours. It might select all sorts of other things (eg. a lot of alcohol addiction, if Yishay’s emphasis on beer is to be believed). There is evidently a much more complex relationship between environment, interactions between conference delegates, and attributes of the delegates than a simple selection model would suggest. Perhaps, an uncontrolled environment, a community of research practitioners (ie. the interactions) and delegates with “academic” attributes are all necessary conditions. If these conditions are independent, then one would say that selection of the right sort of delegates, and community of practice, had happened before the conference started: only those who meet the necessary conditions are in jobs that will pay for their attendance – they have been ruthlessly selected through educational and career structures. However, it also seems entirely likely that the conditions are not totally independent - that the environment, community and delegates help bootstrap each other up to the useful research behaviours. This, after all, is presumably why we encourage research students to attend conferences.

In a previous post, I suggested that for effective learners, the attractors, or stable states, are educationally desirable behaviours. It seems to me that there might be two ways we could ensure this. The first is by the environment ruthlessly selecting those who have these behaviours – this approach might be said to characterise HE prior to the mid 1960s and the beginning of a widening participation agenda. The second is by helping learners to develop strategies for finding these states, and for avoiding other, equally stable but educationally undesirable, states (for example by turning them into repellers). If my analysis of Yishay’s conference experience is near the mark, then a self organisation model of learning needs to understand, not only the necessary environments and communities for learning, but also the dependencies of environment, community and student attributes that will help students become learners.

Thinking about transitions between self organisation and self regulation

In a previous post, I noted that Carver suggests that self regulated learning and self organised learning are two different processes, and that different parts of the brain may be responsible – although this is, he says, a speculative proposal. If it is true, though, we cannot have a linear transition from one to the other – the process cannot reside in some intermediate part of the brain. We have the question then, of whether the change from one to the other is a discontinuous flip – perhaps once the self organised learner has found an attractor and reached a stable state, this triggers the self regulated process and switches off the self organising process. Gestalt psychology, and experience of "Ah ha" moments might suggest that this is the case. Alternatively, the change may look continuous – as the learner homes in on an attractor the self organising process may gradually tail off, with the self regulated process gradually increasing, and the overall learning process represented by the convolution of the two.

Under what conditions could self regulated learning take over from self organised learning. It seems to me that the essential condition for self regulated learning is to be able to conceive of the goal and a process for reaching that goal (?charting). Feedback then comes into play in monitoring the process and progress towards the goal. To be able to conceive the goal and process one must have some experience of it already; this is why I do not see how cutting edge research can be self regulated. But the experience may be vicarious, and it is this, I think, that makes self regulated learning in an educational context possible.

We also have an issue of goal definition. Does the process of reaching a goal help to define the goal? Or is a goal that we do not know how to reach, necessarily one we consider ill-defined? Or has this more to do with whether the measure of achievement is an internal subjective or external objective measure?

Consider the goal, “I want to get a 1st class degree classification”. This, looks like a pretty well defined and objectively measured goal. If I am the child of upper middle class, university-educated and employed parents, and am at a university surrounded by similar peers, with a close academic relationship with tutors and a well scaffolded course, then I have a pretty good conception both of what that goal means in terms of performance, and of what I have to do to achieve it. My parents, and many of my friends, and tutors have all done it previously and provide a model, or pass on tacit knowledge through practice, in Harry Collins’ terms.

If, though, I come from a disadvantaged background, with no parental experience of university education, and go to a university with a high number of other widening participation students, then the goal seems less well defined, despite the objective measure, since I am likely to have far greater difficulty of conceiving what it feels like in terms of the my performance, and even less of how I go about achieving it, however good the tutor and scaffolding on the course may be. Monitoring of both the process and the performance becomes difficult. I have to trial or sample different behaviours to find one that seems to be working, and my learning initially looks more like self organisation than self regulation. Even when I have found one, I don’t know whether it is a tried and tested behaviour that leads to the goal, or a potential dead end, so I am less likely to stabilise on that behaviour.

In the latter case, I am much more akin to someone who has what seems an ill-defined goal, eg. “I want to be happy”. I can conceive of being happy, but have no objective measures of happiness. I know a number of happy people, but they all seem to have achieved it in different ways, and there seems no fixed route to happiness. The best I can do is work on a day to day basis, making decisions that I hope will promote my happiness, and hope that the emergent state will, indeed, be happiness.

We can, I think, conceive of these issues in complex system terms by saying that self-regulation is only possible within the basin of attraction of an attractor. Social links with, and vicarious experience of people who have already achieved the goal and are already in the attractor, are a strong (?necessary) condition of being located within the basin. Thus, in social terms, the difference between one’s ability to self organise and to self regulate lies in one’s distance from others who have already achieved the goal: the widening participation student is likely to be using the same self organising processes as the Nobel Prize winning researcher – neither knows exactly what they are doing – both are self organising.

The requirement for proximity to someone who has already achieved the goal, ties in well with activity theory and the zone of proximal development. It also provides a role for the teacher, even in learner centred learning design and participatory, socially constructed learning – the teacher is someone who has already achieved the goal. If they expose their process of achieving the goal they can help attract learners into that behaviour ?an apprenticeship model of learning.

Key Reference:
Carver, C. S. (2004) “Self-Regulation of Action and Affect” in Baumeister, R and Vohs, K (eds) Handbook of Self-Regulation, New York: Guildford Press, pp13-39

Memetics & Self Organisation

When Anoush alerted us to Susan Blackmore’s talk on memetics it sparked a flurry of debate. Like the rest of the CA I have a number of issues with Blackmore’s argument. However, what I was struck by was the relation between Universal Darwinism, and the idea of self organisation discussed in my last post.

In my snowflake example of self organisation, we have, essentially, two factors at work: the interactions between the water molecules, and the interactions between the water molecules and the environment (largely defined by temperature and pressure)

It seems to me that Universal Darwinism provides three factors as a basis for self organisation:
Mimicry/replication/heredity – ie, the interactions between entities
Selection – ie. the interaction between an entity and its environment
Variation – ie. an autonomous characteristic of the entities

If the entities are genes, we get the whole panoply of living species that we know, as emergent states – from amoeba to armadillos.

If the entities are practices, we get memes.

And, according to Blackmore, if the entities are information, we get temes.

If one takes this self organisation view, it becomes clear how, as Blackmore claims, living species, memes and temes can emerge bottom up and without any top down purpose or direction.

It also seems that the Universal Darwinism example captures the three fundamental types of factor we have to take into account when thinking about any self organising system: the characteristics of the entities; interactions between the entities; and interactions of the entities with the environment

Self Organisation versus Self Direction and Self Regulation, and Learner Autonomy

I (Isobel) have been reading some of the psychology literature on self regulation recently, and also following up on the (rather underdeveloped) psychology ideas about self organisation - leading to this over-long blog post. Sorry folks.

Self Regulation has its foundations in cybernetic control theory. There are a large number of variants on the idea, but core features are that:
• Processes are purposive
• Self-corrective adjustments are made to adhere to the purpose
• The corrective adjustments originate within the person
The basic metaphor is of feedback control with four elements:
• Input function
• Reference standard (defined by the purpose)
• Comparator
• Output function
Behaviour is a process of moving towards goals, or away from anti-goals, via feedback control.

Self Direction. So far I have come across no definitions in the psychology literature (although of course there are definitions in other literature). For linguistic reasons, though, I would take it as differing from self regulation in two fundamental ways:
• The purposes or goals are set by the self (in self regulation they may, but need not necessarily, be set by others)
• No specific mechanism for processing towards the purpose is proposed
I take it as similar to self regulation in
• The primacy of goal setting (both in importance and chronologically)

The cybernetic control metaphor underlying self regulation and (perhaps) self direction is well defined and has clear experimental implications when considering one goal, or factor, at a time. On this view a successful autonomous learner would have the ability to plan an efficient route to their goals, and have effective feedback mechanisms to keep them on the route. The focus of research would be on planning competencies and feedback mechanisms.

However, it seems clear that the complexity of the cybernetic control metaphor increases rapidly (?exponentially) as the number of interacting goals increases, and rapidly becomes unmanageable, especially if the algorithm connecting the goals is undefined.

Self Organisation has its origins in dynamical systems theory. One aspect of dynamical systems theory is the mathematical theory of complex systems of interacting factors. Key ideas are:
• Emergent states: the form and properties of the whole cannot be predicted from the component parts but arises from the interactions of those parts and without top-down purpose eg. snowflakes – each has a different form, and they cannot be predicted from looking at an individual water molecule – they arise from the interactions between water molecules without anyone/thing/top molecule organising all the rest. They are self-organised.
• Phase transitions: states are stable against small perturbations, but a slightly larger perturbation in one factor may trigger a change to a completely different (emergent) state of the system. For example a snowflake at -5C is stable against changes in temperature of up to 5, but as soon as the temperature rises even slightly more than this, the flake suddenly melts into water. For some systems an infinite number of phase transitions or states is possible.
• Attractors and repellers: Some configurations of the system are stable against small perturbations – these are attractors. If it is near such a configuration, the system will self organise into such a stable state. Similarly, some configurations will never be adopted and the system will not spend any time here – these are repellers. If it is near such a repeller, the system will self organise so as to move away from this state. In between are configurations that are not stable, but that the system may move through. For example, a pencil lying on its side is in an attractor. A sharp pencil will not stand on its point (repeller), but it will move through a number of leaning positions as it falls on to its side.

Such ideas have been applied to subjects from maths, physics, chemistry, to the stock exchange, social systems and psychology. From a psychology/learning viewpoint, self organisation seems a candidate metaphor for systems where there are:
• Multiple interacting factors
• Changing situations
• Emergent states
• Lack of purpose
• Lack of predictability

Carver (2004) views attractors and repellers as analogous to the goals and anti-goals of self regulation. To be successful as a self organised learner, it seems to me crucial that the attractors are educationally desirable outcomes, while the repellers are undesirable outcomes. In practice most learners are surrounded by undesirable as well as desirable stable states (truancy, addictions, low level computer games, etc). Hence, perhaps one thing that characterises successful learners is their ability to convert undesirable attractors into repellers. Another characteristic would be their ability rapidly to find and configure themselves around desirable attractors: the learner will move into a state where they can “do this”. We could, for example, model this by thinking about an individual moving through different configurations defined by cognitive, affective and social parameters. It seems to me that, assuming that at first they try different configuration solutions by sampling, there might be several ways in which they might locate and move towards the attractor more rapidly than another learner. They might sample more rapidly – eg. switch attention rapidly from one possible outcome to another. They might sample at a greater distance from their current configuration – eg. by greater cognitive leaps. They might have a greater number of sampling points – eg. by a bigger social network (although note that they might also have to switch attention more rapidly to take advantage of this). They might have a stronger pull toward the attractor once found – eg. by greater interest, recognition or reward. There is likely to be an element of randomness in all these processes.

Putting it another way, one might posit, for example, that successful learners can synthesise a large number of information/skill sources, keep a broad overview of multiple possible outcomes, are sensitive to the proximity of a stable state, and able to strengthen the connections that will move them into that state if it seems a desirable one.

Carver suggests that individuals perform both self regulation and self organisation, and that different parts of the brain may be responsible. He suggests that self organisation is the appropriate process in new and undefined situations, but that as a pattern of behaviour emerges and is recreated, it becomes familiar and defined and self regulation takes over. He cites evidence that different parts of the brain are involved in learning a new skill from repeating an established one.

On a larger scale, human systems are capable of both self organised, and regulated behaviours. Liu et al (2005) draw an analogy to patterns of traffic on a motorway composed of all the cars which are more or less autonomous within the broad constraints set by the environment. These represent a self organised system. They differ, for instance, from the very rehearsed and regulated patterns of an american football team

It seems to me that in the CA we are studying two different scales, and it is worth distinguishing between the two:
• Organisational scale. Here the organisation (HE institution or commercial company) is the system, and the people within it are the entities of which the system is comprised.
• Individual scale. Here the individual is the system, and its cognitive, affective, social predispositions are the entities of which the system is comprised

In the self organisation/complex systems approach, the description “autonomy” is applied to the entities of which the system is comprised. At individual scale, then, it does not make sense to talk of an “autonomous learner” because “learner” refers to the macroscopic behaviour of the system (the individual), while “autonomy” refers to the microscopic entities (cognitive predispositions etc) of which the individual is composed. It would make sense though, to describe the behaviour of a company, as a system, comprised of autonomous learners as entities. For example the emergent, self organised, state of a company comprised of autonomous learners might be a learning organisation (if the company was lucky:-))

It would, though, make sense to talk of an individual as a self organised learner. In this case the entities of which the individual is composed, have organised themselves into a behaviour which we would describe as “learner”.

At individual scale, then, one might look as self organised learners, their abilities and behaviours. Alternatively, at organisational scale one might look at the types of institutional emergent state that arises from different behaviours and interactions of individuals.

Summary of differences between self regulation and self organisation

Self regulated	Self organised
Purpose	No purpose (maybe
Top down control	Bottom up organisation
Autonomy characterises the unit	Autonomy characterises the constituent entities
Clearly defined goals	No goals or poorly defined goals
Best when dealing with a single goal	Can accommodate multiple interacting factors
Constant environments	Changing environments (maybe)
Predictable outcomes	Unpredictable outcomes (maybe)

Key references:
Carver, C. S. (2004) “Self-Regulation of Action and Affect” in Baumeister, R and Vohs, K (eds) Handbook of Self-Regulation, New York: Guildford Press, pp13-39

Carver, C.S. and Scheier, M.F. (2002) “Control processes and self-organization as complementary principles underlying behaviour” Personality and Social Psychology Review, 6, 304-315

Liu, J., Jin, X. & Tsui, K.C., 2005. Autonomy-Oriented Computing (AOC): Formulating Computational Systems with Autonomous Components. IEEE Transactions on systems, man, and cybernetics - part A: systems and humans, 35(6), 879-903.

Hooker, C. & Skewes, J., 2007. Abstract of “Complex Systems Dynamics: Implications for Sustainability, conception and policy.” To appear in Gabbay, D., Thagard, P., and Woods, J. (eds) Handbook of the Philosophy of Science. Elsevier. Available at: http://www.johnwoods.ca/HPS/Hooker_Skewes_abstract_v2B%20F.pdf [Accessed August 1, 2008].

Transformational change through Ideagoras

I (Allison) have been thinking about processes and environments that might support transformational change in approaches to learning and teaching. Recently I had a discussion with Anoush and Koos about the notion that Ideagoras could be potential incubators for ideas on learning innovation.

Ideagoras are online environments (usually wiki-based) where people (researchers and developers) can collaboratively develop ideas (Tapscott and Williams, 2007). Companies seeking solutions to difficult problems can post questions that are answered by experts tapping into the network. These experts are rewarded – often through cash incentives. Alternatively companies can post their Intellectual Property as a solution in search of a problem. This can lead to innovative applications and development of new products. An example of an ideagora is InnoCentive: an open innovation network aiming to ‘provide solutions to tough problems in business, science, product development’ (www.innocentive.com)

Transformational change in higher education is often talked (and written) about yet seldom achieved. I was inspired by the paper by on ICT-Enhanced Teacher Innovation by Lina Markauskaite and Peter Reimann at this year’s EdMedia. Lina and Peter examined areas of innovation outside the educational sphere (for example engineering) to identify characteristics of effective innovation systems. In general innovations are:
1. grounded in basic research
2. horizontally oriented (for example user-doer networks)
3. modular (in terms of processes and products)
4. involve ICT
5. incremental (not disruptive)

Most of these characteristics align with our thinking on transformational change within the Caledonian Academy at Glasgow Caledonian University (UK):
1. All our initiatives are through action research, using principles and theories generated through basic research.
2. Our action research is horizontally oriented through joint ventures with colleagues in our academic schools as well as our industry partnerships.
3. The modularity of our approach to innovation is illustrated through our clustering of projects around the key themes of our learning, teaching and assessment strategy. These themes include learner autonomy/progression, work related learning and scholarship of learning and teaching.
4. Most of these initiatives have a strong ICT focus.
5. Interventions are incremental, based on an understanding of current approaches and behaviours.

Yet we are finding transformational change difficult to achieve. This brings into question the readiness of the organisation for change. We have invested considerable time and resource following Carol Twigg’s (2000) eight-step process, instilling a culture of readiness for change This includes establishing a sense of urgency, assemble a team to lead the change, creating a compelling vision of change, communicate the new vision, removing obstacles to change by encouraging risk., recognising and rewarding success, identifying people who can implement change and making changes part of the institutional culture for long-term transformation. Part of the problem is that the speed of change is so slow that it is difficult to detect.

Many papers on transformational change point to incremental change as being important. Yet when organisations try to achieve incremental change in learning there is often very little change at all. This may be because change within formal education tends to focus on content, packaging or delivery rather than approaches to learning. Markauskaite and Reimann suggest integrating epistemic approaches of practitioners and researchers as a potential solution. How might this integration be achieved?

Effective research-development partnerships are difficult to achieve, partly due to the different goals, values and discourse used by these research and development groups. How can we overcome the difficulties in bringing together different cultures and values of researchers and developers? One way forward could be through Ideagoras.

How could ideagoras support research-development partnerships? In particular how might they identify and expand ‘disruptive’ factors that bring about real change? Tapscott and Williams (2006) abstracted six general principles for success which provide a framework to think through how we could move towards integrating epistemic approaches of practitioners and researchers:

1. Move from ‘closed’ to ‘open’ innovation. In industry this usually involves moving from a closed, hierarchical workplace to an open self-organised, distributed and collaborative environment. Networks are an important component, since communities are too bounded and slow to bring about rapid, flexible change. Success requires open communication through loosely coupled, peer collaboration networks that involve innovation leaders, other experts (eg researchers) and resources that the innovators turn to for advice and support. Tapscott and Williams cite examples where these sorts of networks have radically changed product design and development in companies such as BMW and Boeing. Some universities have introduced distributive leadership networks, where the sort of expertise required for change (eg contributory and practice based expertise) is distributed throughout the organisation. These networks could focus on open, collaborative development of ideas where practitioners post questions on Ideagoras, seeking information on ideas, trends, framework or methods. Researchers could post their latest ideas, seeking out contexts and application areas for further research where they could work in partnership with practitioners. It will be difficult to integrate the different epistemic approaches of practitioners and bridge the gaps in understanding the terms and language of each group.

2. Use research-development partnerships to shake up product roadmaps. In the corporate sector there is a trend towards outsourcing research. The reason is simple – if the research is too closely tied to the existing product, real innovation is unlikely to happen. We can see this in education where many ‘action research’ initiatives are embedded within existing forms of teaching, reducing the possibility of rethinking approaches. There is an inherent dilemma: if incremental change is likely to be most successful , tying it closely to existing approaches may inhibit innovation. At the same time innovation that is removed from existing practices (in the absence of a disruptive force, such as loss of a ‘home’ student market necessitating distance learning approaches) is unlikely to be adopted. It seems that the most likely way to ‘shake up product roadmaps’ is to have sufficient separation between research and development to allow new ideas to emerge, while, at the same time, fostering understanding across the research-development interface. This would inevitably create a ‘tension’ which could incubate innovation. Ideagoras could potentially provide an environment that provides sufficient separation while, at the same time, allows individuals to network. Of course a range of different technologies and environments could achieve this. The key idea here is to use the environment to challenge the thinking of practitioner and researcher group on their ‘product’ roadmaps.

3. Aim for win–win collaboration . For a ‘win-win’ both sides have to understand each others perspectives, values and motivators. This level of understanding can be achieved by working together on a common goal (eg through action research that aims to solve a learning problem by identifying the issues causing the problem, then finding, implementing and testing solutions). Tapscott and Williams cite a number of examples where ‘knowledge tasks’ have been used to bring about learning across enterprise boundaries (see also ‘The Only Sustainable Edge’ by John Hagel and John Seely Brown). Research-development teams working together on learning innovation often find the initial stages of collaboration to be difficult. In the beginning the two groups may not understand each other’s values and goals. If the ideagora environment could be used as mechanism to bridge cultures, focussing on a win-win for all groups is more likely to bring about success.

4. Deepen and broaden collaboration across enterprise boundaries One way of bringing about understanding could be to circulate ideas through ‘reverse innovation transfer’, where an idea from practice is moved ‘upstream’ to research. A number of organisations have used ‘reverse innovation transfer’ to deepen collaboration. This may be best achieved by focussing on ‘high value’ activities for collaboration (ie activities values by researchers and developers). In an open, networked ideagora environment ideas could be scored, indicating their value and enabling selection of ideas that should be researched and developed. This already happens in networking environments such as Linkedin (Koos Winnips just told me he recently posted a question on technology enhanced to Linkedin and had 12 answers within 24 hours from a variety of people from the education and corporate sectors).

5. Learn from ‘proxy’ customers early and often Change can be sparked in industry by disruptive factors such as reducing number of customers, demand for different sorts of products or the need for rapid change. These factors are becoming increasingly influential in education, where ‘products’ can be viewed as graduates who have undergone personal transformation through learning. Customers can be viewed as employers (corporations, public sector organisations, SMEs) or even students themselves. Ideagora environments could potentially be used to link with proxy customers so that they might build ideas that are more likely to be adopted.

Ideagoras are not radical technologies. However, thinking through the ways they could be used and the processes they could support could help find a solution to integrating epistemic approaches of practitioners and researchers to support innovation in learning. It would be interesting to investigate if and how environments such as ideagoras could be used to surface ‘disruptive’ factors required to ring about real change in education.

References:
Collins and Evans (2007) Periodic Table of Expertise
Markauskaite and Reimann, ICT-Enhanced Teacher Innovation, EdMedia 2008
Tapscott and Williams (2006) Wikinomics
Tapscott and Williams (2007), Ideagora, a Marketplace for Minds, Business Week http://www.businessweek.com/innovate/content/feb2007/id20070215_251519.htm
Twigg (2000) Educause http://net.educause.edu/Elements/Attachments/nlii/nliifs03_nlii_paper.pdf

BNE workshops on blended learning

Last week the first of a series of 5 workshops (26 staff in total) were done with the School of the Built and Natural Environment (BNE) to help staff develop their modules for the blended learning Degree in Construction Management which is due to start in Semester A 2008.

BNE will offer blended learning modules on their Construction Management course to their learners who will be on campus only for a limited time, allowing them to better combine learning and working (typical attendance at year five part time is one day per month).

This is a huge task, that will get done, but it will need time to get 35 modules fully developed. We will make a start next year, then roll out this approach further next years.

During the workshops it was not the technical aspects of Blackboard that was discussed, but mainly work on the approach to learning to follow. Discussion was also held on how to make learners self-reliant, how to make the mix between online and face-to-face activities and most importantly, how much time and resource the staff will need to develop materials. Some very interesting topics were identified during the workshops including:

• How to present you courses so that they are personal, and inviting to learners?
  
• Using and integrating online testing
  
• Use of Wiki's to write collaboratively
  
• How to get support for developing materials?
  
• Who will develop materials? Staff? Support staff? Or do you just grab it from Merlot, Jorum, or Opencourseware?
  
• How to support site visits
  

Five more workshops will be carried out before Semester A 2008 and after that we will be ready to carry out and adapt the workshop approach within other academic schools.

Professorial vacancy at Caledonian Academy

We are recruiting again. Caledonian Academy is relatively new and we have established a dynamic group of colleagues working across research and development. We now have a new Chair post and would welcome applications from interested colleagues.

Professor of Learning innovation
Glasgow Caledonian University, UK
£51,276 to £64,125 per annum

The Caledonian Academy is a flagship initiative at Glasgow Caledonian University driving forward innovation in learning and teaching through the integration of research and practice. require an ambitious and creative Professor of Learning Innovation to lead the embedding of ideas and new approaches from research into the curriculum, ensuring that the Academy’s research and development initiatives are complementary and integrated.

You will lead academics within a dynamic Learning Development team, work closely with academic schools and will carry out research in an area of strategic importance to the university. You should have an excellent national or international profile in research. You should have a PhD and be prepared to lead a Doctoral degree programme and contribute to postgraduate level teaching and professional activities. For more information contact allison.littlejohn@gcal.ac.uk Application form Closing date June 30th 2008 .

Social media explained in plain english

New video out from Commoncraft about Social Media. Very good explanation. many more of these are available at Commoncraft: http://www.commoncraft.com/show

Googolopoly

The people from Box.net made a little game to play: Googolopoly. You can even download the full game from them. Nice to play when you get bored with the Microsoft monopoly.
Thanks to Kathy for sending this on.

EU proposal on SmartCharting submitted

The EU proposal that a number of people at the Academy worked on for the last number of months submitted yesterday! Big relief, and a lot of hard work got done on this. For a number of people at the Academy I think the question that springs to mind today is: ‘What to do with my life now?’ (the answer is not hard I guess; get some sleep, and then on the with the next ;)

We expect this project can give a further boost to innovation of learning at Glasgow Caledonian. The proposal is about charting, which will help learners make a better transition to the workplace, and help learners and workers set their long term learning paths. Tools for charting will use web 2.0 technologies to help learning on and in the job.

The above image describes charting. Now lets just hope we get this proposal funded. Competition is steep, but this was not supposed to be easy.