Category Archives: Knowledge development

Work Process Knowledge, Developmental Competence and rhizomatic knowledge

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A number of years ago I did a couple of studies, funded by the European Commission on the use of technology for learning in Small and Medium Enterprises (SMEs). SMEs are defined by the European Commission as those employing less than 350 employees. My overall conclusions were that whilst few enterprises were using Virtual Learning Environments or indeed any other formal e-learning platforms or technologies for learning this did not mean that learning was not happening. Instead many employees used computers everyday for informal learning. Learning was motivated by the need to solve problems in the workplace or surprisingly often by curiosity and interest.

The technologies employed varied but they included Google, Bulletin Boards and email. Ask-a-friend was a common pedagogic strategy.

Now several years on, the European Commission’s Research Programme on information technologies has launched another call for projects designed to crack the perceived issue of the lack of use of Technology Enhanced Learning in SMEs.

And they still haven’t got it. They seem to have an assumption that there are hard to reach sectors or that the technology just isn’t good enough. Or, often is cited, the lack of access to hardware and connectivity.

Of course, since I did my orginal study, there has been considerable changes in technology. The biggest is probably the widespread use of mobiles, (handys, GSM, cells), many of them internet enabled.

But talking to employers this week I don’t see many changes in how the internet is being used for learning. There is one big change though. The employers I have spoken to are aware that computers can facilitate learning and knowledge exchange and support those processes. Back before few employers even knew their employees were involved in learning (mind, many of the employees also didn’t call it learning!).

but the learning processes remain informal. Human communication is most valued, albeit technology mediated. There remains little take up of formal e-learning programmes.

There does seem to be an increasing awareness of the need to link learning and information and knowledge management processes. There is also intense interest in the ability of new technologies to be utlisied at or near the work process and to support the development of what I call work process knowledge or developmental competence.

The concept of Work Process Knowledge emphasises the relevance of practice in the workplace and is related to concepts of competence and qualification that stress the idea that learning processes not only include cognitive, but also affective, personal and social factors. They include the relevance of such non-cognitive and affective-social factors for the acquisition and use of work process knowledge in practical action. Work often takes place, and is carried out, in different circumstances and contexts. Therefore, it is necessary for the individual to acquire and demonstrate a certain capacity to reflect and act on the task (system) and the wider work environment in order to adapt, act and shape it. Such competence is captured in the notion of “developmental competence” (Ellstroem PE, 1997) and includes ‘the idea of social shaping of work and technology as a principle of vocational education and training’ (Heidegger, G., Rauner F., 1997). Work process knowledge embraces ‘developmental competence’, the developmental perspective emphasising that individuals have the capacity to reflect and act upon the environment and thereby forming or shaping it. In using technologies to develop such work process knowledge, individuals are also shaping or appropriating technologies, often developed or designed for different purposes, for social learning.

it seems to me that if we really want to introduce Technology Enhanced Learning in the workplace (and especially in SMEs) we have to find ways of supporting the development of work process knowledge and developmental competence. The problem is that most formal elearning programmes are tied to very traditional notions of competences, which are often only loosely connected to practice. This is one of the reasons I like the idea of rhizomatic knowledge, as put forward by Dave Cormier and currently being discussed on the #Change11 MOOC. Rhizomatic knowledge in the sense of work process knowledge is  generated by practice in communities and technology can be used to scaffold the development of developmental competence through practice (incidentally I think this overcomes many of the objections to the idea of rhizomatic knowledge as discussed on Dave’s blog).

Has Open and Linked Data failed?

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How The Open Data Community Died – A Warning From The Future

I am intrigued by this presentation. Whilst I appreciate what Chris Taggart, who has been invo0lved in the development of the opencorporates and openlylocal data sites (and who undoubtedly has more experience and knowledge than me of the use of Open and Linked Data) I would be less pessimistic. I see the use of open and linked data as in very early days.

Firstly, although I appreciate that politicians and bureaucrats do not always want to release data – I think there is still a groundswell in favour of making data available – at least in Europe. Witness yesterdays unveiling of the Italian Open data store (sorry, I can’t find the url at the moment). And although Google search results do not help promote open data sites (and I am not a great fan of Google at the moment after they wiped out my account ten days again), they have contributed very useful tools such as Refine, Fusion Tables and Public Data Explorer.

I still think that as Chris Taggart says in one of his first slides the biggest challenge is relevance. And here I wonder if one of the problems is that Open and Linked Data specialists are just that – specialist developers in their own field. Many of the applications released so far on the UK Data store, whilst admiral examples of the art of development – would seem to have little practical use.

Maybe it is only when the tools and knowledge of how to work with Open and Linked data are adopted by developers and others in wonder social and subject areas that the true benefits will begin to show. Open data applications may work best, not through dedicated apps or sites, but when incorporated in other web sites which provide them with context and relevance. Thus we have been working with the use of open and linked data for careers guidance (see our new web site, www.careerstalk.org which includes working demonstrations).

Bu even more important may be finding ways of combining Open and Linked data with other forms of (human) knowledge and intelligence. It is just this form of knowledge – for instance the experiences and informal knowledge of careers guidance professionals, which brings relevance and context to the data from official data sets. And that provides a new design challenge.

Knowledge development and Personal Learning Environments

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I am in Innsbruck for four days for a meeting of the EU funded research project, Mature-IP. Over the next few days I will try to report on what theproject is doing.

The Mature project has always interseted me in its approach to Personal Learning Environments. Whilst most projects based on PLEs have looked at learning within schools and univeristies, Mature looks at knowledge maturing processes in work.

And the project has adopted a user based approach working with a number of different user groups, in the UK from the Careers services, in developing and iterating a PLE based on knowledge development services. The project has also developed a series of knowledge indicators, based on these services.

Is it working? It is a little early to tell. But the project acknowledges the importance of different forms of learning leading to knowledge development and sharing in the workplace and also takes account of differences in context. The services developed have been based on the idea of represneting, modellinga nd reseeding knowledge delopment or maturing processes as seen in the diagramme above. Twenty seven services have been developed to date and can be combined in what are being called insubstatiations to take account of such contexts. I realise these may seem somewhat abstract but they have served in bridging between social and educational researchers working on the project and software develers. These services are:

Representation Services:

Content

  • Content metric service: Provides a wrapper for encapsulating various content metric implementations
  • Classification service: Classifies resources to a given set of categories based on their content. Classification can be improved by the help of user feedback
  • Clustering Service: Groups items regarding a special feature

Structure

  • Task Similarity Service: Computes the similarity between tasks
  • Tag Mortality Analysis Service: analyses tags / concepts and their activity to predict their death
  • Concept Relationship Analysis Service: Analyzes concept hierarchy and usage of concept for annotations to derive recommendations for adding broader/narrower relationships
  • oSKOS Analysis Service: analyzes a SKOS ontology for potential redundant or missing information

Usage

  • Usage Logging Service: collects usage data from the user’s interaction with the MATURE systems
  • Process Tracking Service: logs process and task execution

Model Services

User

  • User Modeling Service: Detects a user’s knowledge from his or her usage data
  • Topical User Modeling Service: Provides an aggregated topical profile of a person

Task

  • Process Monitoring Service: Provides the means to query and browse log data provided by the Process Tracking Service in aggregated form
  • Process Model Refinement Service: Compares the modelled process with the actual process executions and suggests improvements on the process model based on it

Resource

  • Resource Model Service: Describes resources based on usage data
  • Document Similarity Service: Derives the textual similarity between two documents
  • Resource Quality Profile: Creates a qualitative profile for each resource

Reseeding Services

Reseeding of Knowledge about contents

  • Quality Based Resource Recommendation: Provides a set of ranked resources based on the qualitative status of the resource and quality requirements of the user
  • Context Aware Notification Service: Provides information about activities related to artefacts
  • Reseeding of Knowledge about SemanticsTag Recommendation Service: Provides tag recommendations to achieve a consistent personal and organisational tag vocabulary
  • Keyword Recommendation Service: Provides a list of synonyms and hyponyms for tags
  • Ontology Gardening Recommendation Service: provides recommendation for improving a SKOS ontology based on the ontology itself and information on its application

Reseeding of Knowledge about Processes

  • Case-based Resource Recommendation Service: suggests resources based on resource-use in historical process executions.
  • Historical Case Service: searches for historical cases based on a given input

Reseeding of Knowledge about People

  • Expertise Analytics Service: Provides an aggregated overview and comparison of available and requested expertise based on tag assignments and search query analysis within a certain timeframe
  • People Ranking Service: Provides a ranked list of people that are relevant for a given topic
  • Expert Ranking Service: Based on past tag assignments (user-document-tag triple marked with a timestamp), this service recommends knowledgeable colleagues working on a specific topic
  • People Awareness Service: Based on a user/person’s profile, this service recommends other persons with a similar profile

Innovation, education and thinking outside the skills matching box

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The second verse of the great Pete Seeger song ‘Little Boxes‘, written by Malvina Reynolds goes:

And the people in the houses
All went to the university,
Where they were put in boxes
And they came out all the same,
And there’s doctors and lawyers,
And business executives,
And they’re all made out of ticky tacky
And they all look just the same.

And of course it is true. More than that, it is the policy on which most of our careers guidance practice is based. Find what skills industry and commerce needs, goes the policy, set up training places to meet those needs, put people into those boxes and we will turn out a neat match between skills and the needs of the economy.The strategy is called ‘skills matching’ and forms the basis for the European New Skills, New Jobs policy as well as that of many national governments.

Universities traditionally stood aloof from such a policy which they saw only as applicable to those in vocational education and training. Univeristy was about the development fo minds and about research.

But with the increasing commodification of universities, they too are embracing such a strategy, in the name of value for money and employability. Students are reluctant to part with large sums of money unless they can see a job progression route for their expenditure on a degree course; governments regard vocational relevance as the key criteria in providing fiances for higher education.

The only problem is that the ‘Little Boxes’ approach doesn’t work. Firstly employers often don’t know what skills they want. take the fiasco at the end of the last century when the European Industry Group for Information and Communication Technologies was predicting huge skills gaps in computing and computer programming. These gaps never materialized despite little growth in the supply to computer programmers. Secondly we simply do not have sufficiently well developed central planning infrastructures to plan for skills and employment in such a way.

This is not to deny the needs for close community links between employers and education providers, at least on a local level. However this should not be to the detriment of other community interests in education and community well being. And rather than focus on skills matching, it would be far better to focus attention on creativity and innovation. If we look at regional innovation centres in Europe such as the manufacturing clusters in Emilia Romana or the media cluster in Cardiff it could be argued that such growth happened due to innovation around the skills and creativity of the workforce, rather than because of matching of skills to existing industry (indeed in Cardiff’s case the economy was traditionally based on heavy industry and manufacturing).

In any case is it possible to ‘predict’ the skills needed int he economy in a period of fast technological change? The Institut Technik und Bildung at Bremen University, with whom I have worked for many years used to talk of the ‘shaping’ principle. They saw education as playing a key role in shaping work organisation and skills development as enabling social innovation in production and economic development. The word ‘shaping’ is a translation of the German ‘Gestaltung’, also commonly translated as ‘design’. And once more this would suggest we can design our futures, that technology and production are not mechanistically determined but rather can be shaped or changed.

But for such an approach we need people who can think out of the box, who can consider the social implications of technology development. And that will not happen through a skills matching policy!

Barriers to elearning in Small and Medium Enterprises

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I have been doing some thinking recently on the use of technology for learning in Small and Medium Enterprises (SMEs). Or rather the lack of it. Some six or seven years ago we did a project on this finding that although there was much use of technology for informal learning, there was very little awareness, take up or implementation of elearning systems in SMEs (the book of the project is available on our publications page).
Since then there has been considerable public expenditure in Europe encouraging the enhanced use of technology for learning. Small and Medium Enterprises are seen as a key sector for creating employment and for innovation. Training and Continuing Professional Development are critical to innovation and the growth of SMEs. SMEs do not provide sufficient training because they cannot spare the time for staff to attend external training programmes and because internal training is too expensive. Therefore use elearning – so goes the logic. But the logic is clearly flawed. SMEs have not rushed to embrace the possibilities of elearning, despite pubic subventions. So what are the barriers and constraints. The following list is based on a series of meetings and consultation albeit in the somewhat specialist field of careers guidance, which, in England, is organised through private careers companies under contracts with local and national government. Indeed, one of the problems, I think, is that we have tended to treat SMEs as a homogeneous entity, whilst, in reality, the possibilities and approach in different sectors varies greatly and there is also big differences between an SME of 250 workers (the EU says an SME is any organisation employing less than 300 staff) and small enterprises with say 8 or ten staff.

  1. Lack of resources. Lack of formal based learning courses or resources. Most training programmes and Continuing Professional Development opportunities are face to face. This may reflect culture, lack of awareness of potential of e-learning and lack of technically proficient specialists to develop e-learning resources, plus of course the cost of producing high quality learning materials.
  2. Poor infrastructure. Many careers companies have a poor network infrastructure and are using out of date computers with even more out of date web browsers etc. Furthermore many of companies have set up heavy firewalls preventing access to social networking sites.
  3. Lack of competence or confidence in use of computers by some careers advisers. May be some reluctance by staff to become involved in elearning.
  4. Lack of awareness by senior managers and staff development officers of potential of elearning. Lack of local champions for change
  5. Despite all these problems and barriers, most careers advisers use computers as part of their everyday job. There are requirements to use networked systems for record keeping. In addition many use the computers for informal learning and especially for browsing for resources, also using the computer in direct work with clients. However such activity is not viewed by managers as ‘learning’ neither is it accredited.
  6. Lack of time. It is difficult to persuade managers to provide time for informal (or formal) online learning, especially given present financial climate. Many do appear to use computer for work purposes at home and in their own time.
  7. Cost. Many online resources are expensive and at present careers services are under heavy financial pressure. Is also worth noting that practices of companies in paying for online access by say mobile phone varies greatly. Staff may be unwilling to use mobile devices if are expected to pay themselves.
  8. Confidentiality. Much of the work is confidential. This may mitigate against the use of open social software networks.
  9. Organisational structures. Careers companies have to bid for contracts and may be unwilling to share learning opportunities or resources with other companies who may be perceived as competitors.
  10. Lack of functionality to share informal learning. Are only limited networks and community applications for sharing learning. there are some signs this may be changing but most learning is hared and disseminated face to face or by email.
  11. Much of the work of careers advisers take place outside the office. Access to resources including internet may be limited.

These barriers could be categorised as social, pedagogical, organsiational and technological. In reality the different categories probably reinforce each other and overlap. But each area needs to be addressed if progress is to be made.

I would be interested in other opinions as to barriers in developing elearning in SMEs – in this or other sectors