I have just read an interesting blog post on mobile learning (via the useful ADL mobile learning email list). Donald H Clark says:

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.

And yet of course we use smart devices for learning all the time.

Every time we Google something, check a map for our location, quiz friends and colleagues for the answer to a question we are operating exactly in the sweet spot of L&D: we are learning something, or using a performance aid.

Of course we don’t call it that.

We call it ‘finding something out’, or ‘doing our job’. The learning is almost invisible because it is embedded in our daily lives; it didn’t require us to go somewhere special, to do anything special. It happened at the best possible time – when we had a need for it, and were attuned to be receptive to new information.

I agree. And in the Learning Layers project we are focusing on the everyday learning that take place with mobile devices. Our focus is on Small and Medium Enterprises. Donald Taylor goes on to say:

Rather than concentrating on writing courses, we should be establishing good practice in our organisations for finding information and experts and for sharing information. Where necessary we should be setting up the systems and then letting people get on with using them. We need to use this opportunity to move from being the gatekeepers of knowledge to the facilitators of conversations and learning.

Once more I agree – to an extent. I think the real potential of mobile learning is 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 even greater is the possibility to link what we used to call learning (or training) to developing and using knowledge for work. In the past we have called this work process knowledge. In development term this means we need applications which can ;recognise the different contexts (and purposes) for which the mobile device is being used. Whilst there has been considerable academic research on mobile work based learning, there is only limited accounts of practice.

One barrier is the attitude of employers. 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.

Much of the work we do in Pontydysgu is project based. And a lot of that work is funded by the European Union, inv0olving multi national consortia of partners working together over a period of two to four years. The two year projects are a bit tight for time, especially if this includes technology development. But the big problem is what happens after the project funding ends. In the best cases, the ideas and products get taken up, further developed and embedded in practice. For instance  work we undertook through the MOSEP project has led to the introduction of e-portfolios in German schools. And work piloted in the Mature IP project has led to the development of an open portal and database for labour market information to improve career choices and decision making in the UK.

But all too sadly, many projects just fade away at the end of the funding. Of course sometimes this is because the work turned out to be less impressive than we had initially hoped. But there are also two big problems more relater to the structuring and fincaci9ng of European projects. The major one is the scaling up of projects and innovations. If products and processes are to be used after a project ceases funding, whatever the outcome, substantial numbers of users are needed. This is true for software, for processes or for more traditional products such as handbooks. Of course it is difficult to scale up to substantial numbers of users with two years. But regardless of the length of a project it requires a strategy. And most projects do not have such a goal, let alone a strategic approach.

The EU funded Learning layers project has as a major objective, scaling the use of technology to substantial numbers of small and medium enterprises in the construction and health sectors. To do this we are looking at developing engagement with clusters of small and medium-sized enterprises.

Between 2002 and 2010, nearly 85% of new jobs in Europe were created by small and medium-sized enterprises (SMEs), which are currently employing 67% of the total workforce (De Krok et al., 2011). Notably, it is the smallest and youngest SMEs that drive this trend, while more established and larger firms are shedding jobs on a net basis. Many of the new jobs created by these SMEs are knowledge intensive and demand specialised skills. According to a European Commission study, the number of low skilled jobs is expected to fall from 21% of total jobs in 2012 to 18% by 2020, while jobs that require higher skills levels are expected to rise by 20%. (European Commission, 2012).

Highly specialised and high-skill growth SMEs increasingly organise in regional clusters as competitive pressures and the difficulties in some sectors of finding skilled workers make collaboration even among competitors an attractive value proposition. At the same time, clusters have a unique negotiation advantage in the region compared to smaller actors, and have the power to influence educational institutions and policy makers. In theory, by joining clusters together with other firms and regional players, SMEs have  a means to influence educational and business development policy in their region and the bargaining power to lean on local colleges and universities to produce the skills and talents needed for economic advancement. Cluster organisations can drive innovation in learning at the workplace by helping SMEs and other cluster members in developing joint technology-enabled training and skills services, which in turn provide an additional funding source for the cluster organisation.

A recent study conducted by the Cluster Excellence Initiative (Meier zu Köcker et al., 2012) of over 300 European cluster organisations shows that the depth and breadth of services offered to their members is the most important contributor to generating impact on the business of SMEs. In terms of the type of service offered by the cluster organisation, our research indicates that currently, services focusing on training and skills development have the greatest potential in terms of generating revenues. This supports the Learning Layers project strategy of targeting cluster organisations as scaling partners and the focus on training and skills development services for SMEs in and across regional clusters. Inter-cluster collaborations in developing learning services makes economic sense since clusters in a given region share common actors, including regional policy makers in education and business development, universities, VET and general upper secondary schools, research institutions, and financial institutions and investors. (more to follow).

Last week I wrote about projections of future demand for Science, Technology, Engineering and Maths (STEM – or in Germany – MINT) occupations. I suggested that predictions of skills shortages were overstated.

The same applies to computer programmers. According to the European Commission, “many vacancies for ICT practitioners cannot be filled, despite the high level of unemployment in Europe. While demand for employees with ICT skills is growing by around 3% a year, the number of graduates from computing sciences fell by 10% between 2006 and 2010.

If this trend continues, there could be up to 900 000 unfilled ICT practitioners’ vacancies in the EU by 2015.”

This is not the first time the European Commission has predicted skills shortages for ICT practitioners. Prior to the Millennium bug, there were once more predictions of a massive shortage of programmers. And I suspect, with a little internet searching, it would be possible to find annual predictions of skills shortages and unfilled vacancies, especially from industry lobby bodies.

One reason for this, I suggested in my previous article, is that the ICT industry has an interest in keeping wages down by ensuring an over supply of qualified workers. In this respect, a report last week on the size and value of the apps industry in Europe is interesting. The  report published by industry trade body ACT, claimed that there are currently 529,000 people in full-time employment directly linked to the app economy across Europe, including 330,000 app developers with another 265,000 jobs n created indirectly in sectors like healthcare, education and media, where apps are increasingly prominent.

At first glance then, this is a rosy area for young people with a good future. But digging deeper into the data suggests something different. According to the Guardian newspaper, “In the UK specifically, the report claims that 40% of organisations involved in developing apps are one-man operations, while 58% employ up to five people. It also points out that 35% of UK app developers are earning less than $1,000 a month from their work.”

1000 dollars a month is hardly a living wage, let alone a sufficient level of remuneration to justify the expense of a degree course. However this does not discourage the industry group who amongst other measures are lobbying the European Commission to strengthen the single market and develop “a flexible and supportive business environment for startups and entrepreneurs.” In other words, more deregulation.

There are a number of problems in looking at skills shortages in this area. My suspicion would be that although the numbers graduating from computer science have fallen, graduates in computer and ICT related courses has risen. And demand for ICT practitioners covers a wide range of occupations. Rather than increasing the number of computer science graduates, more useful would be to ensure that ll graduates are skilled in designing and using new technologies. Of course developing such skills and competences should start at a much younger range. It is encouraging the ICT has been included in the primary school curriculum in England from next year.

The EU policy on future employment is based on the idea of job matching – of trying to match skills, qualifications and vacancies. Of course this does not work. What they should be doing is looking at prospective competences and skills – at giving young people the educations and skills to shape the future of workplace3s and employment. That could include the ability to use technology creatively in a socio-technical sense. But of course that would not suit the various industry lobby groups who are more concerned with protecting there profits than shaping the future of our society.

The debate over skills shortages is looming again. For some years national governments and the European Commission have been warning over shortages of qualified workers in Science, Engineering, Technology and Maths (STEM) . Yet a number of studies refute these claims.

A blog post on SmartPlanet quotes Robert Charette who, writing in IEEE Spectrum,  says that despite the hand wringing, “there are more STEM workers than suitable jobs.” He points to a study by the Economic Policy Institute that found that wages for U.S. IT and mathematics-related professionals have not grown appreciably over the past decade, and that they, too, have had difficulty finding jobs in the past five years. He lists a number of studies that refute the presence of a global STEM skills shortage. The U.S. Bureau of Labor Statistics, for one, estimates that there was a net loss of  370 000 science and engineering jobs in the U.S. in 2011.

I doubt that figures in Europe would be much different. One of the issues is how to define a ‘STEM” job. In the UK jobs are classified through a system called Standard Occupational Classification. This itself has its problems. Given the desire for comparability, SOC is only updated every ten years (the last was in 2010). In a time of fast changing occupations, it is inevitably out of date. Furthermore jobs are classified to four digits. This is simply not deep enough to deal with many real occupations. Even if a more detailed classification system was to be developed, present sample sizes on surveys – primarily the Labour Force Survey (LFS) would produce too few results for many occupations. And it is unlikely in the present political and financial environment that statistical agencies will be able to increase sample sizes.

But a bigger problem is linking subjects and courses to jobs. UK universities code courses according to the Joint Academic Coding System (JACS). It is pretty hard to equate JACS to SOC or even to map between them.

The bigger problem is how we relate knowledge and skills to employment. At one time a degree was seen as an academic preparation for employment. Now it is increasingly seen as a vocational course for employment in a particular field and we are attempting to map skills and competences to particular occupational profiles. That won’t really work. I doubt there is really a dire shortage of employees for STEM occupations as such. Predictions of such shortages come from industry representatives who may have a vested interest in ensuring over supply in order to keep wage rates down (more on this tomorrow). For some time now, national governments and the European Union, have had an obsession with STEM and particularly the computer industry as sources of economic competitiveness and growth and providers of employment (more to come about that, too).

However, more important may be the number of occupations which require use of mathematics or programming as part of the job. One of the problems with the present way of surveying occupational employment is that there is an assumption we all do one job. I would be pretty pushed to define what my occupation is – researcher, developer, write, journalist, project manager, company director? According to the statistics agency I can only be one. And then how the one, whichever it is, be matched to a university course. Computer programmers increasingly need advanced project management skills.  I suspect that one factor driving participation in MOOCs is that people require new skills and knowledge not acquired through their initial degrees for work purposes.

My conclusions – a) Don’t believe everything you read about skills shortages, and b) We need to ensure academic courses provide students with a wide range of skills and knowledge drawn from different disciplines, and c) We need to think in more depth about the link between education and work.

Mind the Gap, says Geoff Stead referring to the gap between theory and practice in mobile learning. And it is this gap which is perplexing me as we attempt to develop an App (code named Rapid Turbine) for use by German construction apprentices.

Writing in a blog for last year’s MobiMOOC Geoff says:

There are a few academic frameworks that can be useful in evaluating, and reflecting on m-learning:

1. Laurillard’s Conversational framework (2002) – showing the different roles that technology can play in the process
2. Park’s Pedagogical Framework for Mobile Learning (2011) – offering a simple matrix to map the transactional and/or social closeness of a learning intervention
3. Koole’s Model for Framing Mobile Learning (FRAME) – 2009 – showing how the mobile learning is an interaction between the technology, the learner and the context.

FRAME model

The one that most connects with my own thinking is FRAME, because it is quite clear that you any theory about m-learning needs to engage with the technology itself (the device), AND the learner (who they are, what they want), AND their social context.

The reason the definition works for me is exactly the reason why I suspect m-learning has proved so problematic to define precisely. It just isn’t one thing. There may well be one core idea in the middle, but this is heavily influenced by factors that are different in different contexts.

Here are some examples, and contrasting ideas:

• while m-learning at work might be about performance support tools, and access to small nuggets of information; m-learning in the classroom might be more about exploring ideas together, and collaborating on a project
• while m-learning on a field trip might be exploring your environment (GPS / augmented reality / mapping / camera), m-learning in a lecture theatre might be about taking notes, and looking up references.
• while BYOD m-learning might be about sharing critical information via any device; a specific iPad activity will be rely on a specific app on a specific, named device

Folks, these are ALL m-learning, but because the circles in the Venn Diagram are filled with different questions, the resulting answer is different.

The core idea behind Rapid Turbine is that it brings teogther learning in different contexts – in the vocational school, in the industry training centre and in the workplace

Thus the pedagogic design of the App needs to be ‘mutable; to reflect these different designs. In the vocational school learning may be more formal and the app needs to scaffold and support apprentices in linking that formal knowledge to the work based learning gained in practice.

In the training centre the use of the App is focused on gaining practical work based knowledge and the presentation of learning materials and learning support needs to reflect that use. In the workplace, the App may be more needed to provide information and knowledge based on the other settings.

The different dimensions of the App should adapt to these different contexts of use. Collaboration, communication and data sharing will vary in each context of use. Thus a use case based on a single scenario or context will only provide us limited help.

Perhaps a dimension or scale lacking in these frameworks is that of depth and breadth, which can be seen as key in linking both the different kinds of knowledge and learning and the different resources which support scaffolded learning.

If we take a particular work task as the basis for an application (as Rapid Turbine does which is why it is high in authenticity and situatedness) then at some points apprentices will want to progress in more depth which perhaps brings in more theoretical learning and in other cases with more breadth which provides more contextual links to other work tasks (and arguably to more holistic work tasks).

The App needs to overcome not just a gap between theory and practice in mobile learning design but the gap between theory and practice in skilled construction work and the gap between informal and formal learning. And that is not easy

by Graham Attwell, Owen Gray and Martina Luebbing

We wrote in an earlier post about the Rapid Turbine app which we are developing through the Learning Layers project. Rapid Turbine is a prototype demonstrator, designed to show the potential of mobile devices to support learning by apprentices in the north German construction industry training centre, Bau ABC. Apprentices at Bau ABC learn through undertaking a series of practical projects, detailed in a paper based White Folder.

The task sheets are used both outlining the tasks to be undertaken, the tools required, materials and health and safety concerns etc and for recording learning. Through developing a mobile app it is intended to make updating 0of tasks easier but most importantly to allow closer links between the learning apprentices undertake in the training centre, with their courses in vocational schools and with their work undertaken on construction sites.

The task we are developing for the prototype is called Rohrleitungsbau (pipe and sewer laying). Our main aims are to test the pedagogic approach and design of the app and to develop a work flow so that trainers can themselves produce mobile learning materials.

One of the key aims for the Learning Layers project is to encourage the development of peer produced learning materials. Peers might be apprentices themselves or trainers in the training centres. We are aware that a major barrier to the take up of technology for learning in Small and Medium Enterprises is the high cost of buying or commissioning the production of learning materials. Furthermore we are aware of the need for vocational expertise in the development of these learning materials, expertise we do not have as researchers and developers.

Although it is beginning to change, most traditional e-learning has been very heavily text dependent. This is not really suited to practical and wok based learning, especially using the mobile devices which can allow apprentices to access learning materials directly in the training centre or workplace.

Therefore we are keen to videos into the app related to the different tasks being undertaken. Once more, fairly obviously the trainers are the best people to make these videos. Originally we had thought of going to Bau ABC and filming these videos ourselves. But this would have been very time consuming and is not really sustainable. Our next thought was to use wearable video devices and we experimented with prototype smart glasses with video capacity. However, the quality was not great and the controls were difficult to use.

So our latest solution is to use an Go Pro camera, attached to a construction site safety helmet. The cameras are reasonably easy to use and importantly, having originally been designed for recording extreme sports,  are extremely rugged, and with the cover fitted, water proof and dust proof. They can also be controlled through a Wireless based phone app. We need more work to find out what makes a good short learning video to be accessed on a mobile device. We’re starting out trying to make a series of handy tips, based one each task, but will review this as we go. And we are encouraged that some of the trainers have already been making their own videos using an ipad. I suspect they will have more ideas than us.

The helmet mounted camera will be delivered to the training centre tomorrow and as soon as we have some videos we will shared them on this site.

I guess many of you are enjoying your holidays now. Here at Pontydysgu we’re ploughing ahead with our summer project, codenamed Rapid Turbine. Rapid Turbine is a spin out from the Learning layers project design group called Sharing Turbine.

The design idea has followed extensive discussion with Bau ABC, a large training organisation for the building industry in Lower Saxony and Bremen in north Germany. The apprenticeship system in Germany is based on a Dual System, with apprentices learning both within companies and within vocational schools. However in the construction trade there are three venues for learning, the company, the vocational school and the training centres.

Training in the training centre is organised around practical tasks which may take from one to three or four days to complete. The tasks are documented in something called the White Folder which is also used for reporting on work. This has a number fo problems – it takes time to update content and despite the use of colour photocopying has limitations in terms of media. Perhaps the biggest drawback is teh lack of portability, thus limiting the use of learning materials or of apprentices/ past learning in the company or the vocational school.

Thus the idea of Sharing Turbine is to produce a mobile app which can provide interactivity whilst undertaking workplace learning tasks. But the more we have looked at developing such an app – the more daunting it seems. Wireframes and diagrams have multiplied, with multiple use cases and endless meetings.

So Rapid Turbine has been designed as a rapid application project to get something out. And my thinking is until we have produced something, we will not really understand what we are doing. So we have taken just one task – Trench digging and pipe installation- and are trying to produce an app.

So far we have hit two big issues. The first is the pedagogic approach. We want to go further than just producing information on how to do the task – even with nice video. The mobile app should stimulate not just interactivity  but activity in the work process. And of course there are many real life artefacts which are used in that activity.

The second issue is establishing a workflow. Ultimately our aim is that our colleagues from Bau ABC will be able to produce the learning materials themselves. So far our workflow is fourfold. Firstly we are producing wireframes. Although we have used Balsamic in teh past, at the moment our designers, Owen Gray and Martina Luebbing are preferring to work on flipchart paper. then we need to generate the HTML, CSS, Javascrtipt etc. for the app. This we plan to do using Twitter Bootstrap and an html editor. And then we will use the Tribal m-Learning program to produce the App.

So far so good. We are still at the wireframe stage. I will update you on how it all goes.

A new nationwide Open Badges initiative has been launched by DigitalMe in the UK. Badge the UK has been developed to help organisations and businesses recognise young people’s skills and achievements online.

Supported by the Nominet Trust, the Badge the UK initiative is designed to support young people in successfully making the transition between schools and employment using Mozilla Open Badges as a new way to capture and share skills across the web.

At the recent launch event at Mozilla’s London HQ Lord Knight emphasised the “disruptive potential” of Open Badges within the current Education system. At a time of record levels of skills shortages and unemployment amongst young people all speakers stressed need for a new way to encourage and recognise learning which lead to further training and ultimately employment opportunities. Badge the UK is designed to help organisations and businesses see the value in using Mozilla Open Badges as a new way to recognise skills and achievement and and connect them to real world training and employment opportunities.

You can find more information on the DigitalMe web site.

We have been running a series of workshops for the RadioActive project on developing internet radio stations. Part of this is about content and part around the technical side of streaming internet radio.

In theory the technical side should be easy – we take a series of feeds – from microphones, MP3 players, from a computer and mix them through a 8 track mixing deck before returning the signal to the computer, streaming it to a streaming server in London and hence to the internet. Indeed, so easy we thought it, that we designed the technical training as a breakout session from the main workshops.

We were wrong. The struggle with the technocracy has proved to be the main problem with the RadioActive project. And we came to realize the problem. We had showed people how to set the computer and deck up. But we had not explained the underpinning theories and ideas behind the audio set up. Fine if it all worked our of the box. But if it didn’t then without an understanding of what different components are doing, it is mighty hard to diagnose where the problem is.

Secondly we paid insufficient attention to the issue of leveling. Fairly obviously different inputs will have different levels (just like people – I am make an incredibly loud input). And one of the skills of the technician is leveling those inputs, both using presets during a sound check and adjusting the faders (and if necessary, the gain) during the broadcast. Also, post processing on pre-recorded items can help in getting a common level.
I could sort of operate the deck and system myself. But I had just picked it up as I went along and had no real knowledge of what the different buttons did.

And one of the issues was that people kept asking for us to tell them the ‘right’ why to do it, when , in truth there are many different ways to set the system up. But, once more, to understand the different possible set ups, which is useful when you discover you have left a key connecting cable behind, means having a more theoretical understanding of what we are doing than just following a diagram.
So we have revamped our technical training for internet radio. We have turned it into a two-day module and are experimenting with outcomes based accreditation. Dirk delivered the first workshop for the London partners two weeks ago. And I followed the same programme in Bucharest with our partners from Romania.

One of the critical aspects is we go far further into the theory, explaining what each part of the equipment does before even trying to connect it all up.
And it seems to work. Our Romanian partners broadcast a wonderfully smooth programme last Friday lunchtime. We still have some things to learn – we had forgotten to teach them how to use remote recorders. But the programme is getting set on the right course. Next step I think – is to try to produce some open educational resources and multimedia to supplement the face to face training

In the past, I spent a lot of time researching different kinds of knowledge and how they could be supported by vocational education and training. In particular, I was trying to counter the reductionist approach, as embodied in the then National Vocational Qualifications in the UK, which came from a narrow understanding of competence. Lately I have been returning to that research to try to understand how technologies can support the development of vocational competence and knowledge in a workplace setting.

This is an extract from a paper entitled  ‘Work process knowledge, Communities of Practice and the development and introduction of mobile learning applications in the workplace’, submitted by myself, Ludger Deitmer, Lars Heinemann and Pekka Kamarainen to the ECTEL 2013 conference. You can download the full paper in PDF format here.

When thinking about knowledge development in a richer way, it may be useful to distinguish between different types of knowledge. Lundvall and Johnson (1994) identify four different kinds of knowledge, each requiring different types of mastery: know-what, know-why, know-how, and know-who.

Know-what refers to knowledge about ‘facts’: it can be considered as equivalent to what is normally called information and related to the knowledge ‘corpus’ that each category of experts must possess. Know-why refers to scientific knowledge, influencing technological development and the pace and characteristics of its applications in industries of every kind. Also in this case, knowledge production and reproduction take place within organised processes, such as university teaching, scientific research, specialised personnel recruiting, and so on.

Know-how refers to skills – that is, the capabilities to do something in different contexts (e.g. judging the market prospects for a new product, operating a machine-tool, etc.). Of course know-how is typically a kind of knowledge developed at the individual level¹, but its importance is evident also if one considers the division of labour and degree of co-operation taking place within organisations and even at the inter-organisational level (for instance, the formation of industrial net-works is largely due to the need for firms to be able to share and combine elements of know-how). Know-who is another kind of knowledge which is becoming increasingly important, referring to a mix of different kinds of skills, in particular the social skills, allowing the access and use of knowledge possessed by someone else.

Rauner et al. (2013) modified these categories in order to bring it in line with the ideas of situated learning and communities of practice, emphasising the role of work processes and the corresponding work process knowledge. The categories of know-what and know-how still refer to ‘factual’ knowledge and the ways of ‘expressing’ it in a work process. The third category, know-why, refers to why to carry out a specific task in a certain way (or, if more appropriate, in another). This modification is due to the insight, that work tasks as well as work processes in post-Taylorist work organisations do not follow a logic of right/wrong. Instead, a solution to a problem can be more or less adequate. This adequacy depends on a number of partly conflicting factors, One may programme the control of a car’s motor giving different weight to factors like acceleration, fuel consumption, high speed, exhaust emissions, etc., according to the intended main use. An electrician may counsel his or her customer on the design of a lighting system regarding costs, efficiency, ecological aspects, sustainability, ease of maintenance, etc., according to the end-users’ ideas. This, then, has the consequence that vocational learning has to address all these three dimensions of knowledge as a whole. The ‘reflective practitioner’ (Schön 1983) is not someone reflecting on what he or she has done after work, using analogue or digital media. ‘Reflection’ is a category built in the expert solution of work tasks requiring a deep knowledge of the work process a given task is embedded in.

Each kind of knowledge is characterised by different channels through which learning takes place and can be supported in different ways using technologies. The easiest cases are those of know-what and know-why, that can be obtained through the typical channels of knowledge acquisition (watching videos, accessing data bases), while the other two categories are rooted primarily in practical experience and in terms of technology enhanced learning have been more problematic insofar as they require the availability of informal social channels. Apprenticeship is a fundamental channel for acquiring know-how knowledge: it represents the most important way for skilling newcomers in an organisation, but these protracted processes of learning by doing are also frequently the responsibility of those who are considered the experts in an organisation, capable of above-average performance. Technology can be used to bring together novices and experts Simulations can be used as shortcuts for reproducing the many aspects of the know-how acquisition available in real situations. Mobile technology can capture know-how in the application of knowledge within the workplace. Know-why can be facilitated by helping to make traceable the processes guiding expert workers’ decision making. In general, this points to a use of digital media going far beyond the transmission of information.

References

Lundvall. B.; Johnson, B. (1994) The learning economy, Journal of Industrial Studies, 1.

Rauner, F., Heinemann, L., Maurer, A., Haasler, B. (2013) Competence Development and Assessment in TVET (COMET), Dordrecht: Springer.