Characteristics of Informal Learning

Changes in the world economy are forcing corporations to rethink how workers learn and to perform effectively. How do people learn? Why? What accounts for the upswing in interest in less formal learning? Does it work?

In the corporate context, learning is about mastering technical and social skills, and product knowledge. The focus is on attaining the skills. knowledge, and expertise required to meet the promise made to the customer.

In an interview in 2005, the estimable Jay Cross articulated a concept that many (including myself) felt was an emerging trend in corporate learning and development:

Well, I had to redefine all learning …because the world is changing so fast. The concepts we had when knowledge was fixed in place, like something you could put in a library, don’t work anymore. So I look at all learning as adaptation to the communities that matter to you, to your ecosystems, if you will. Informal Learning is simply that, which is not directed by an organization or somebody in a control position.

(Interview with Jay Cross: Informal Learning)

The year 2005 heralded the recovery from the Dot-Com Crash in 2001, a year Kevin Kruse has described as one that

...brought the harsh, steep slope of unfulfilled promises. Several high-profile [e-learning] providers shut their doors while many more announced large-scale layoffs in the face of missed revenue targets and crashing stock prices. E-learning advocates retreated to the more defensible ground of "blended learning. This year [went] down as the Trough of Despair.

As a result of this turn-of-the-century disillusionment, a key document on lifelong learning published by the European Commission in the same year went unnoticed by many training professionals. In their 2001 document Communication on Lifelong Learning, the authors Holford, Patulny & Sturgis defined the terms formal, non-formal and informal learning (p.9):

Table 1 Definition of learning types

Learning Type	Description
Formal Learning	Learning typically provided by an education or training institution, structured (in terms of learning objectives, learning time or learning support) and leading to certification. Formal learning is intentional from the learner’s perspective [my italics].
Non-formal Learning	Learning that is not provided by an education or training institution and typically does not lead to formalized certification. It is, however, structured (in terms of learning objectives, learning time or learning support). Non-formal learning is intentional from the learner’s perspective [my italics].
Informal Learning	Learning resulting from daily life activities related to work, family or leisure. It is not structured (in terms of learning objectives, learning time or learning support) and typically does not lead to certification. Informal learning may be intentional but in most cases it is non-intentional (or “incidental”/ random) [my italics].

More next time...

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References:

Cross, J. (2004) An informal history of eLearning. On the Horizon [Internet] 12(3). pp.103-110. Available from: http://www.emeraldinsight.com/Insight/viewPDF.jsp?Filename=html/Output/Published/EmeraldFullTextArticle/Pdf/2740120301.pdf (Subscription required) Accessed 20th February, 2007

Holford, J. Patulny, R. & Sturgis, P. (2005) Indicators of Non-formal & Informal Educational Contributions to Active Citizenship. A Paper Prepared for the European Commission by the University of Surrey. [Internet]. Available from: http://farmweb.jrc.cec.eu.int/CRELL/active_citizenship.htm Accessed 25th October, 2006

Kruse, K. (2002) The State of e-Learning: Looking at History with the Technology Hype Cycle. [Internet] Available from: http://www.e-learningguru.com/articles/hype1_1.htm [Accessed 12th February 2008]

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The Stark Difference between Skills-based and Knowledge Workers

I'm a big believer in attics. No, not in the spiritual sense of the word "belief;' I don't have faith in attics, but I like what attics represent: a place to store and save the accumulated bits of your life that you don't need right now, but may again need at some point in the future.

So I have a folder of my back-up HDD called Attic - you may have a similar - Archive, or My Stuff, or Guilty Secrets, for all I know. I make a point of occasionally going in to my Attic directory to have a root around among what's stored there and having a look through old folders and zip files with deliciously obscure names like toiltrouble.pdf, avalon.doc, or BladesDemo.exe that once meant something, and that I have now completely forgotten what they represent.

Opening one such document yesterday, I re-discovered a table that clearly illustrated the differences between the 20th Century and New Economies, and here it is.

Table 1 The Emergence of a New Economy

Old Economy	New Economy
A Skill	Lifelong Learning
Labor vs. Management	Teams
Business vs. Environment	Encourage Growth
Security	Risk Taking
Monopolies	Competition
Job Preservation	Job Creation
Wages	Ownership, Options
Plant, Equipment	Intellectual Property
National	Global
Status Quo	Speed, Change
Standardization	Custom, Choice
Top-down	Distributed
Hierarchical	Networked
Regulation	Public/Private Partnerships
Zero Sum	Win-Win
Sues	Invests
Standing Still	Moving Ahead

Source: John Doerr, Kleiner Perkins, Caufield & Byers

In my view John Doerr's chart should be printed, laminated and posted beside every learning & development professional's desk, so that they are constantly reminded of the value of the work they undertake, and the potential lifelong and work-based learning helps to realize in the development of individuals, and society-at-large.

That's all for today. Now, for your homework, reflect on the chart.

___________

References:

Doerr, J. The Emergence of a New Economy. Kleiner Perkins, Caufield & Byers.

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Knowledge Worker Information Processing - an Overview

The goal behind this series of posts about knowledge working and knowledge workers is to understand something of the audience that most of the efforts of organizational learning and development professionals are targeted at; the knowledge workers (KWs) themselves. Today, I'm will wrap up the series by concluding my analysis of the William P. Sheridan's How to Think like a Knowledge Worker (2008).

I believe that knowledge working is intimately bound within the organizational context: knowledge workers use their skills and experience to innovate solutions to real-world problems. One of the primary conditions of knowledge working is the social aspect – knowledge workers typically collaborate with their peers, whether they are individuals with similar skill assets, such as application development teams working in an agile software development environment, or in project teams which require knowledge workers from different disciplines (technical architects, business analysts, and product consultants, for example) to cooperate in the implementation of the solutions on a customer site.

Figure 1. Human Knowledge Mindmap (after Sheridan)

In this context, Sheridan uses the Human Knowledge MindMap (see Figure 1. to converge the skills and knowledge of domain experts to look at the internal processes a knowledge worker uses to codify and utilize information in a fashion to what Donald Schon calls reflection-in-action.

We can say that the purpose of the mindmap is to enable KWs to "think effectively" (p.13). Most peoples’ thinking, is not clear, focused, or systematic enough to perform knowledge work competently. The purpose of the Human Knowledge MindMap is one approach that enables users to do this. Whether during learning, or on a job, effective thinking consists of a set of components as characterized in the mindmap.

Table 1 Knowledge worker thought processes

Sheridan suggests that to carry out this activity, the worker should do the following:

• Pick a situation, problem, challenge, decision or choice of interest or concern (on whatever basis you regard as appropriate).

Then proceed with the following steps:

• Identify which aspects are of most interest or concern to you.
• Prioritize (rank) your interests or concerns.
• Using the Human Knowledge MindMap as a visual guide, apply the relevant concepts to the most important (prioritized) aspects of your interest or concern (limit it to the top three aspects on your list to begin with).
• If you don’t recall whether or nor a particular concept is relevant, refresh your memory by re-reading the one-page outline.
• From this point apply the methodology as outlined above (this may, in addition to other things, require reading more materials to acquire the necessary depth of understanding in the issues you are trying to deal with).

________________

References:

Sheridan, W.P. How to Think like a Knowledge Worker:A guide to the mindset needed to perform competent knowledge work. United Nations Public Administration Network, New York. [Internet] Available from: http://unpan1.un.org/intradoc/groups/public/documents/unpan/unpan031277.pdf [Accessed 24 August 2008]

Thinking like a Knowledge Worker

Return again to a topic I looked at recently, here's some insights to thinking like a knowledge worker I discovered while undertaking my research on the subject. The concepts explored here are investigated in much more depth in a paper called How to Think like a Knowledge Worker by William P. Sheridan. I'd love to go into the level of detail that the author does, but to invoke the spirit of Star Trek's Dr. McCoy "For God's sake Jim, - I'm a blog, not a research paper."

"I'm a Doctor, not a blog..."

Moving on...

In his paper, Sheridan asserts that

Knowledge consists of concepts available to process information and guide action. Knowledge Management refers to "smart use of know-how." In a knowledge economy more and more tasks involved "think work."Thinking involves the separation of relevant information from irrelevant information. Therefore, "think work" is a component of "knowledge work," specifically the information processing part - the other part is just the "informed action" part.

(2008 p.5)

The author asserts that by assembling a "Human Knowledge Mindmap" (see Figure 1) we can develop a method to ensure the quality of knowledge worker outputs. He cites the example of W. Edwards Deming's methodology for quality control in industrial economies being "shunned" in the US, but being a key component in the growth of the Japanese automobile industry in the middle- to late 20th century as an example of how ignoring such approaches is done at organization's peril.

The central ideas of Sheridan's approach are Conceptual Pragmatism and Cognitive Economy.

If your question is "How do I know?" then [your answer] will involve some combination of empiricism, rationalism and constructivism. Such cognitive amalgamations do what makes "knowing" possible.

(p.9)

Figure 1. Human Knowledge Mindmap (after Sheridan)

We can say that there are three factors that characterize knowledge:

1. Empiricism (observable facts)
2. Rationalism (thinking things through)
3. Constructivism (formulating new ideas)

While we all undertake all three of these approaches, most people emphasize one of the trio; these "habits of emphasis" lead to partial or at best inadequate learning and knowing.

More...

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References:

Sheridan, W.P. How to Think like a Knowledge Worker:A guide to the mindset needed to perform competent knowledge work. United Nations Public Administration Network, New York. [Internet] Available from: http://unpan1.un.org/intradoc/groups/public/documents/unpan/unpan031277.pdf [Accessed 24 August 2008]

Rapid E-learning: using the 80/20 rule to prioritize learning needs

Today's post concludes my short review of Kineo's 80/20 approach to rapid learning content prioritization and development.
Previously, I considered how the 80/20 Rule could be applied to e-learning, and suggested that Juran's Axiom of "the vital few and the trivial many" meant that we could say 80 percent of learning results originate from 20 percent of inputs for any activity or process. For example, 80 percent of an organization sales come from 20 percent of customers, or 80 percent of performance in an organisation is attributable to 20 percent of workers.

In the learning domain, this rule can be applied to the process of training prioritization. In organizations the purpose of learning and development is to improve worker performance. There are many ways and opportunities for employees to improve their performance:

• reducing procedural mistakes
• identifying new customers
• influencing the behavior of others
• reducing error in products

Effective training should focus on providing what’s necessary to enable people to improve performance. However, the 80/20 rule suggests that not all performance improvement opportunities merit the same focus. Rather it suggests that 20% of opportunities, if addressed 80% of the total potential value of a training solution (assuming the ‘perfect’ solution will address 100% of opportunities completely. Focusing training efforts on that top 20% is a far more efficient model than attempting to cover the remaining 80%. For rapid e-learning with a relatively short duration, having this focus is critical.

In this context, Kineo recommend a value-driven model for identifying and prioritising opportunities for rapid e-learning to influence performance that will contribute the most to organizational performance.

According to Stephen Walsh from Kineo, this process has a number of key activities:

• Ensure that you have identified prioritized needs that rapid e-learning is best placed to address
• Use the 80/20 rule to guide your analysis of the prioritization of training
• Use the three-step approach (see Figure 1) to conduct rapid training needs analysis

1. Identify the full range of performance improvement opportunities
2. Establish criteria and rank accordingly with experts – concentrating your efforts on top 20%
3. Translate to objectives and seek approval

• Use rapid tools (check-lists) and rapid methods (phone, workshops, virtual classroom, surveys) to gather your data.

Figure 1. Value-driven model for rapid training needs prioritisation (courtesy Kineo)

For a more detailed look at this approach, go to Kineo's website, or download the Rapid Guide on How to Rapidly Identify Training Needs.

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Rapid E-Learning and the 80/20 Rule

You'll know if you're a regular reader of The E-Learning Curve Blog that I have discussed the usage of the Pareto Principle (also known as the 80/20 Rule) in previous blog posts. Elsewhere in the e-learning blogosphere, Tony Karrer at the eLearning Technology blog has also discussed what he calls the "Corporate Learning Long Tail" in some depth.

Over the weekend, I encountered a very useful paper describing a practical application of the 80/20 rule (though not, as we'll see, the Pareto Principle).

Now read on...

My experience of the e-learning industry is that the best and most effective practitioners are always looking for even more efficient content development methodologies, media production technologies, and approaches to content distribution to enable them to design, develop and deliver content to learners. In this regard, British e-learning development house Kineo always seem to have something interesting to say about the potential uses - and value - of Rapid E-learning, and one particular piece published in this month's Newsletter struck me as being particularly useful. In the article How to Rapidly Identify Training Needs Stephen Walsh discusses a strategy to pinpoint and prioritize training needs - "rapidly of course."

The value of any learning intervention is the change it achieves. If you know where the business challenge is, and you can pinpoint how learning can change behaviour, correct costly errors, and improve performance at the right time, you're setting yourself up for laser-accurate learning.

In his seminal article Rapid E-learning: Disintermediate or die! Ted Cocheu asserts that:

Learning is rapidly changing from today’s hierarchically-driven, curriculum-based training process where instructional designers and trainers intervene to transform subject matter knowledge into courseware, into a “flattened” world where experts transfer their knowledge more directly to those who need it. In this brave new flattened learning world, training professionals will focus more time on capturing and transferring expert knowledge than developing formal courses.

To support these changes in the design, development, and delivery of content, a number of factors need to be considered:

• Speed is king.
• Knowledge is exploding.
• Budgets are shrinking
• Classrooms are not scalable.
• Workplace learning is informal.
• People forget.
• Key knowledge is proprietary.

Rapid E-learning "changes the development model, leverages new tools, and dramatically changes the economics of content development" (p.2). By focusing on specific learning needs, e-learning developers can generate a much higher return on investment in training when compared to content designed using a more traditional ISD-based approach.

The methodology suggested by Kineo is designed to assist learning professionals identify and prioritize learning needs that are appropriate for rapid e-learning in organizations using a "value-based analysis."

This will get you to the outcome that a more detailed training needs would, but in a fraction of the time, by focusing specifically on the greatest points of pain and potential to add value. Identifying those key points means taking an 80/20 approach to needs analysis.

The Kineo interpretation of the Pareto Principle is based upon Dr. Joseph M. Juran's pioneering work in Quality Management in the 1930s and '40s. He "reduced to writing" his generally applicable observation (which I suggest that we should really call Juran's Axiom) of the relative importance of the "vital few and trivial many." Juran observed that in any activity or set of tasks, a few (20 percent) of the functions are vital, and many (80 percent) are trivial. However, as he stated in his 1975 article The Non-Pareto Principle; Mea Culpa he "...mistakenly applied the wrong name to the principle." In Pareto's case it meant one-fifth of the people owned four-fifth's of the wealth. In Juran's research for the US Government, he identified 20% of defects in a production process causing 80% of the quality issues. Project Managers know that 20 percent of the work (the first 10 percent and the last 10 percent) consume 80 percent of time and resources. Extending from this, Juran asserted that the 80/20 Rule could be generalized, from the science of management to the physical world, and indeed to learning and development processes.

In this context, 20 percent of learning interventions, if properly identified, should address 80 percent of the learning needs of an organization, and 80 percent total potential value of a training solution (assuming the ‘perfect’ solution will address 100% of learning.

Focusing training efforts on that top 20% is a far more efficient model than attempting to cover the remaining 80%. For rapid e-learning with a relatively short duration, having this focus is critical.

(How to Rapidly Identify Training Needs p.2)

As such, implementing a value-driven model based on the 80/20 Rule for identifying and prioritizing learning interventions can be a highly effective means to enhance worker performance in an organization.

More..

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References:

Cocheau, T. (2005) Rapid eLearning: Disintermediate or Die! [Internet] Available from: http://ww.elearningforum.com/downloads/rapid_elearning.doc [Accessed 15th May 2006]

Juran, J.M. (1975) The Non-Pareto Principle; Mea Culpa [Internet] Available from: http://www.projectsmart.co.uk/docs/the-non-pareto-principle.pdf [Accessed 30 August 2008]

Walsh, S. (2008) How to Rapidly Identify Training Needs [Internet] Available from: http://www.kineo.com/documents/Kineo_Rapid_Guide_Identify_Needs.pdf [Accessed 30 August 2008]

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The Characteristics of the Knowledge Economy, Part 4

In concluding this part of the E-Learning Curve Blog's series on Knowledge Work, I will describe the final characteristics that define a knowledge economy.

Systems of creation, production and distribution

The commonly-held notion that a knowledge economy is a services economy is misleading. As information and knowledge add value to basic products manufacturing and services are becoming increasingly integrated into complex chains of creation, production and distribution. At the core of the economy are goods producing industries, linked into value chains which see inputs coming from knowledge-based business services and goods related construction and energy industries, and outputs going to goods related distribution service industries[1].

Convergence or divergence

One feature of the emerging knowledge economy is increasing evidence that the nations of the world are polarizing, rather than converging, in economic terms. Standard growth theories suggest that economies subject to market forces should converge in terms of per capita GDP levels, either absolutely or relatively. But the reality is quite different.

Countries appear to be moving towards two peaks or nodes, one at high incomes and one at relatively low incomes. This polarisation of countries into different strata of economic activity and of living standards is becoming both pronounced and persistent – what is often referred to as “twin-peaks dynamics[2].” What the future will show as the knowledge economy unfolds remains to be seen, but there is little in the recent historical record to assure policy makers that market forces will deliver a continuing process of convergence to US levels. In such a world the consequences of policy failure or inaction can be dramatic.

Divergence and concentration

These same dynamics may cause changes in the industrial structure of knowledge economics. Many contend that increasing inequality can be observed at the international, national, regional, household and personal levels – that the rich are getting rich, while the poor are getting poorer. Some economists suggest that increasing returns from network economies and learning economies characteristic of knowledge economies will lead to industrial concentration – a world of winner takes all[3]. Others contend that the expansion of the knowledge driven economy will create a proliferation of material, firms and activities at all points and at all levels, suggesting that no one can expect to enjoy continued control of markets.

There may be temporary monopolies but they cannot last. And it is misconceived to think that the key lies in being at the point of delivery of the product: the low cost and ease of access to the delivery mechanism mean that the rents are driven down at the delivery level and instead migrate back up the value chain to those with genuinely scarce factors and competitive advantages[4].

Whichever proves true, the knowledge economy will see the development of new business models.

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Footnotes:

[1] Sheehan, P. Tegart, G. (Eds.) (1998) Working for the Future: Technology and Employment in the Global Knowledge Economy. Victoria University Press.

[2] Sheehan, P. and Tegart, G. (Eds.) (1998) Working for the Future: Technology and Employment in the Global Knowledge Economy, Victoria University Press, p100. See also Quah, D. (1996) ‘Convergence Empirics Across Economies with (Some) Capital Mobility,’ Journal of Economic Growth, 1(1) pp. 95-125 [Internet] Available form: http://www.jstor.org/pss/2235377 [Accessed 20 August 2008]

[3] Arthur, W.B. (1996) ‘Increasing Returns and the New World of Business’, Harvard Business Review, July-August 1996, pp. 100-109

[4] Kay, J. In: DTI (1999) Economics of the Knowledge Driven Economy, Conference Proceedings, Department of Trade and Industry, London.

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The Characteristics of the Knowledge Economy, Part 3

In yesterday's post, I began to describe in some detail the characteristics of the knowledge economy in the 21st century; in today's post I will continue to investigate some of the defining factors that identify the emergence of this economic paradigm.

Learning organizations and innovation systems

In a knowledge economy, organizations search for linkages to promote inter-organizational learning, and for outside partners and networks to provide complementary assets. These relationships help organizations

1. spread the costs and risks associated with innovation
2. gain access to new research results, acquire key technological components
3. share assets in manufacturing, marketing and distribution.

As they develop new products and processes, organizations determine which activities they will undertake individually, in collaboration with other organizations, in collaboration with universities or research institutions, and with the support of government[1]. We can say that, as such, innovation is the result of numerous interactions between actors and institutions, which together form an "innovation system."

These innovation systems consist of the information flows and relationships which exist among industry, government and academic and other institutions in the development of science and technology. The interactions within these systems influences the innovative performance of organizations - and ultimately of the economy. The ‘knowledge distribution power’ of the system, or its capability to ensure timely access by innovators to relevant stocks of knowledge, is can be seen as a major determinant of economic growth.

Strategy and location

One of the consequences of globalization combined with advances in communications technologies has been a strengthening of world competition, and the emergence of a new form of ‘global competition’. Most organizations in a dominant market position are, by necessity, multinational or transnational organizations. To compete successfully with their rivals, organizations must compete head-to-head in all markets (including their home market), and they must rapidly attain a global scale in production and/or rapidly roll out products and services into multiple markets in order to do so. In this environment, competitiveness depends increasingly on the coordination of, and alignment of a broad range of specialized industrial, financial, technological, commercial, administrative and cultural skills which can be located in many locations around the world[2].

Production is being rationalized globally, with organizations combining the factors, features and skills of various locations in the process of competing in global markets. There are three major dimensions of change involved:

• increasing national (locational) specialization
• increased international ‘fracturing’ of value chains or chains of production – witnessed in increased intra-industry and intra-firm trade
• greater line-item by line-item trade imbalances

An increasingly apparent consequence of this development in industrial ertia is substantial structural dislocation in local, regional and even national economies, and a consequent need for substantial structural adjustment.

Clustering in the Knowledge Economy

Networks and geographical clusters of firms are a particularly important feature of the knowledge economy. Organizations find it increasingly necessary to work with other firms and institutions in technology-based alliances, because of the rising cost, increasing complexity and widening scope of technology. Many organizations are becoming multi-technology corporations locating around centers of excellence in different countries. Despite improved capability for global communication, firms increasingly co-locate because it is the only effective way to share understanding[3]. Consequently, skills and life-style are becoming increasingly important locational factors.

As we enter the age of human capital, where organizations merely lease knowledge-assets, organizations’ location decisions are increasingly based upon quality-of-life factors that are important to attracting and retaining this economic asset. In high-tech services, strict business-cost measures are becoming less important to growing and sustaining technology clusters … Locations that are attractive to knowledge assets will play a vital role in determining the economic success of regions[4].

Economics of knowledge

In the knowledge economy there are new ground rules. Knowledge has fundamentally different characteristics from ordinary commodities and these differences have crucial implications for the way a knowledge economy must be organised[5]. The whole nature of economic activity, and our understanding of it, is changing.

Unlike physical goods information is non-rival – not destroyed in consumption. Its value in consumption can be enjoyed again and again. Hence, social return on investment in its generation can be multiplied through its diffusion. Ideas and information exhibit very different characteristics from the goods and services of the industrial economy. For example, much more than is the case with a frozen dinner or a haircut, the social value of ideas and information increases to the degree they can be shared with and used by others. More important, the costs associated with their production are distributed very differently over time. While up front costs associated with the production of traditional goods such as a car or house may not necessarily be high, each item is still costly to produce. The more of these one produces, the more likely one will eventually encounter scarcities that drive up production costs and reduce the size of social returns. In the case of innovation, ideas and information, however, the opposite would seem largely to be the case. While up front development costs can be very high, the reproduction and transmission costs are low. The more such items are (re)produced, the greater the social return on investment[6].

Traditional economics is founded on a system which seeks to optimise the efficient allocation of scarce resources, but because of the unique characteristics of information and knowledge the very meaning of scarcity is changing. Indeed, the scarcity defying expansiveness of knowledge is the root of one of its most important defining features. Once knowledge is discovered and made public, there is essentially zero marginal cost to adding more users[7].

More...

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References:

Sheehan, P. Tegart, G. (Eds.) (1998) Working for the Future: Technology and Employment in the Global Knowledge Economy. Victoria University Press.

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Footnotes:

[1] OECD. (1996) The Knowledge-Based Economy, OECD Paris, p. 16. [Internet] Available from: http://www.oecd.org/dataoecd/51/8/1913021.pdf [Accessed 20 August 2008]

[2] Hatzichronoglou, T.(1996) Globalisation and Competitiveness: Relevant Indicators, STI

Working Paper 1996/5, OECD, Paris, p. 7.

[3] Cantwell, J. In: DTI (1999) Economics of the Knowledge Driven Economy, Conference Proceedings, Department of Trade and Industry, London.

[4] DeVol, R.C. (1999) America’s High-Tech Economy: Growth, Development and Risks for Metropolitan Areas, Milken Institute, Santa Monica

[5] DTI (1999) Economics of the Knowledge Driven Economy, Conference Proceedings, Department of Trade and Industry, London, p.5

[6] Industry Canada (1997) Towards a Society Built on Knowledge [Internet} Available from: http://strategis.ic.gc.ca/SSG/ih01644e.html [Accessed 20p August 2008]

[7] DTI (1999) Economics of the Knowledge Driven Economy, Conference Proceedings, Department of Trade and Industry, London, p. 6.

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Characteristics of the Knowledge Economy, continued

In the 21st century, comparative advantage will become much less a function of natural resource endowments and capital-labour ratios and much more a function of technology and skills. Mother nature and history will play a much smaller role, while human ingenuity will play a much bigger role.

(New Tools, New Rules: Playing to win in the new economic game. p.101)

As I discussed in much finer detail (and in the context of e-learning rather than the economy) in this post, in my view we as a society are on the cusp of a knowledge revolution akin to the explosion of information made possible after the general availability of printed texts following the invention of movable type and the printing press in 1440.

As this century unfolds, the skills used by people will increasingly be those that are complementary with information and communication technology; not those that are substitutes.

Now read on...

What makes the emergence of the knowledge economy important is that it is, in some significant respects, different from the industrial economy we have known for most of the last two hundred years. Some of the key differentiators include:

Information revolution

The IT revolution has intensified the move towards knowledge convergence, and increased the share the knowledge stock of advanced economies. All knowledge that can be distilled as information can be transmitted globally at relatively little cost. Knowledge per se has attained more of the properties of a commodity. [1]

Flexible organization

Flexible organizations reduce waste and increase the productivity of both labor and capital by integrating worker cognition and action at all levels of their operations.In doing so they eliminate many layers of middle management, which are dysfunctional in terms of information flow[2]. Flexible organizations also avoid excessive specialization and compartmentalization by defining multi-task job responsibilities (which calls for multi-skilled workers) and by using teamwork and job rotation.

Flexible organizations merge agility and high product quality with the speed and low unit costs of mass production. They do this by more fully utilising the human capabilities of their workers.

Knowledge, skills and learning

Information and communication technologies have reduced the cost and enhanced the capacity of organizations to converge knowledge, and process and communicate information. In doing so they have substantially altered the ‘balance’ between explicit and tacit knowledge in the overall quantum of knowledge. As access to information becomes easier and less expensive, the skills and competencies relating to the selection and efficient use of information become more crucial, and tacit knowledge in the form of the skills needed to handle explicit knowledge has become more important than ever.

Information and communication technology investments are complementary with investment in human resources and skills[3]. Whereas machines replaced labor in the industrial era, information technology will be the locus of explicit knowledge in the knowledge economy, and work in the knowledge economy will increasingly demand uniquely human (and tacit) skills – such as conceptual and inter-personal management and communication skills.

Innovation and knowledge networks

The knowledge economy increasingly relies on the creation, distribution and use of knowledge assets. The success of enterprises will become more reliant upon their effectiveness in creation, harvesting, absorption and utilization of knowledge.

A knowledge economy is driven by the acceleration of the rate of change and the rate of learning of the contributors to the economy, where the opportunity and capability to get access to and join knowledge-intensive and learning-intensive relations determines the socio-economic position of individuals and firms[4]. Companies must become learning organizations, continuously adapting management, organization and skills to accommodate new technologies and grasp new opportunities. They will be increasingly joined in networks, where interactive learning involving creators, producers and users in experimentation and exchange of information drives innovation.

More...

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References:

Sheehan, P. Tegart, G. (Eds.) (1998) Working for the Future: Technology and Employment in the Global Knowledge Economy. Victoria University Press.

Thurow, L. (1991) New Tools, New Rules: Playing to win in the new economic game. Prism.

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Footnotes:

[1] This post is primarily drawn from Sheehan, P. Tegart, G. (Eds.) (1998) Working for the Future: Technology and Employment in the Global Knowledge Economy. Victoria University Press.

[2] Oman C. (1996) The Policy Challenges of Globalisation and Regionalisation, Policy Brief No. 11, OECD Development Centre, OECD, Paris, p. 19. [Internet] Available from: http://www.oecd.org/dataoecd/51/8/1913021.pdf [Accessed 20 August 2008]

[3] Soete, L. (1997) Macroeconomic and Structural Policy in the Knowledge-based
Economy. In: Industrial Competitiveness in the Knowledge-based Economy: The New Role
of Governments, OECD, Paris, p. 136.

[4] David, P. Foray, D. (1995) ‘Accessing and Expanding the Science and Technology Knowledge Base,’ STI Review, No 16, OECD, Paris.

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Characteristics of the Knowledge Economy

In their paper Working for the Future: Technology and Employment in the Global Knowledge Economy, John Houghton and Peter Sheehan discuss the "impacts" (p.8) of globalization and as the foundation for the Knowledge Economy. They assert that

...firms are increasingly required to adopt global strategies to deal with the new realities. Global competition in all major markets between competitors from all major countries, the increasing multinational origin of the inputs to production of both goods and services, the growing intra-industry and indeed intra-product nature of world trade and the interdependent role of the various elements of globalisation are all contributing to a transformation of the global economy.

(1998, p.8)

The emergence of the knowledge economy can be characterized in terms of the "increasing role of knowledge" (p.9) as a factor of production and its impact on skills, learning, organization and innovation. These, then, are the key circumstances and characteristics in the development of Globalized Knowledge Economy:

• There is an enormous increase in the codification of knowledge, which together with networks and the digitalization of information, is leading to its increasing commodification.
• Increasing codification of knowledge is leading to a shift in the balance of the stock of knowledge – leading to a relative shortage of tacit knowledge.
• Codification is promoting a shift in the organization and structure of production.
• Information and communication technologies increasingly favour the diffusion of information over re-invention, reducing the investment required for a given quantum of knowledge.
• The increasing rate of accumulation of knowledge stocks is positive for economic growth (raising the speed limit to growth). Knowledge is not necessarily exhausted in consumption.
• Codification is producing a convergence, bridging different areas of competence, reducing knowledge dispersion, and increasing the speed of turnover of the stock of knowledge.
• The innovation system and its ‘knowledge distribution power’ are critically
  important.
• The increased rate of codification and collection of information are leading to a shift in focus towards tacit (‘handling’) skills.
• Learning is increasingly central for both people and organizations.
• Learning involves both education and learning-by-doing, learning-by-using and learning-by-interacting.
• Learning organizations are increasingly networked organizations.
• Initiative, creativity, problem solving and openness to change are increasingly important skills.
• The transition to a knowledge-based system may make market failure systemic.
• A knowledge-based economy is so fundamentally different from the resource-based system of the last century that conventional economic understanding must be re-examined.

More...

_________________

References:

Sheehan, P. Tegart, G. (Eds.) (1998) Working for the Future: Technology and Employment in the Global Knowledge Economy. Victoria University Press.

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The Half-Life of the Knowledge Worker

If you don’t like change, you’re going to like irrelevance even less.

Gen. Eric Shinseki

The US and EuroZone economies are in recession, China is ascendant, Russia is asserting it's regional dominance, all the knowledge jobs are going to India, and it hasn't stopped raining for two weeks.

As you know if you're a regular reader of The E-Learning Curve Blog, I occasionally reflect on e-learning, the economy, and the effect that the one has on the other.

This time I have decided to discuss the emergence and current role of knowledge workers, how this role is changing, and will come to propose a definition for a new type of worker that seems to emerging, particularly in the traditional home of knowledge work, North America and Europe.

Now read on...

In 1959 Peter Drucker coined the term “knowledge worker” to describe

one who works primarily with information or one who develops and uses knowledge in the workplace. It is performed by subject-matter specialists in all areas of an organisation;

(1973, p.839)

their tools are the knowledge assets they use in an organisation. Knowledge workers are characterised by a number of traits, among them the ability to extract and synthesize key information to enhance innovation and productivity.

It is “generally accepted” (Drucker, 2006, p.165) that the knowledge workers’ expertise in their role is the starting point for enhancing productivity, quality and performance. If knowledge workers are to continue contributing to an organisation and the economy at large, their knowledge must remain up-to-date. Ongoing training and continuous learning must accompany gains in performance; “the greatest benefit of training comes not from learning something new but from doing better what we already do well” (2006, p.165).

Three years later, Fritz Machlup published The Production and Distribution of Knowledge in the United States. In concert with Drucker's work, we can say that the early 1960's marked the beginning of the study of the post-industrial information society. Machlup coined the phrase "knowledge economy" to include everything from stationery and typewriters, advertising, and presidential addresses - in fact, anything that involved the activity of telling anyone anything - to evaluate the use of knowledge technologies to produce economic benefits.

The transformation to a knowledge economy continued throughout the rest of the 20th century, especially following the invention and growth of the Internet.

Especially in the wake of the invention and growth of the Internet, we can say that today's global economy is characterized as being in transition to a knowledge economy, and an extension of what we can call an information society. This transition requires that the rules and practices that determined success in the industrial economy need to be rewritten in an interconnected, globalized economy where knowledge resources such as know-how, expertise, and intellectual property are more critical than other economic resources such as land, natural resources, and even manpower. According to analysts of the knowledge economy, these rules need to be re-factored at the levels of companies, organizations, and industries in the context of managing knowledge and (possibly more imperatively) at the level of government- or public policy.

Due to the increasingly technological nature of industrial growth and the emergence of globalization as a influencing factor on the world economy of the last 60 years, there is an ongoing and increasing requirement for an academically capable workforce. As a result, knowledge workers are now estimated to outnumber all other workers in North America by at least four-to-one (Haag et al, 2006, pg. 4).

...and at this point I will conclude for today, as this is a blog post, not an essay and I'm sure, dear reader, that you have other things to be getting on with. In tomorrow's post, I will continue to develop the concept of the half-life of the knowledge worker and begin to look at how the Asian Tigers have superceded the advanced industrial nations of the 20th century.

In the meantime, as I started today's piece with a quote, I think that for the sake of symmetry I should conclude this article with another excerpt:

Turning and turning in the widening gyre
The falcon cannot hear the falconer;
Things fall apart; the centre cannot hold;

W.B. Yeats The Second Coming

___________

References:

Drucker, P. F. (1973) Management: Tasks, Responsibilities, Practices. New York, Harper & Row

Drucker, P. F. (2006) Classic Drucker. Boston, MA. Harvard Business School Publishing Corporation

Haag, S. Cummings, M. McCubbrey, D. Pinsonneault, A. & Donovan, R. (2006) Management Information Systems For the Information Age (3rd Ed.). London, McGraw-Hill Education

Machlup, F. (1962) The Production and Distribution of Knowledge in the United States. Princeton University Press

Yeats, W. B. (1920) The Second Coming. The Norton Anthology of English Literature, 8th Edition. W. W. Norton & Co.

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Approaches to evaluating learning

In yesterday's post I put forward some thoughts on terminal second-level examinations and the effect that faring poorly in these could have for young adults' future lives.

I received a comment on the topic from a correspondent who asserted:

...does success in exams equal education? Exams are an outmoded assessment tool - success in them means nothing more than a certificate and maybe entry into higher education - where you sit more exams until you finally move into the real world...where you realise your so called education did you a grave disservice.
Can you think? Can you create? Can you problem solve? Does an exam system fit into 21st century learning?

Now read on...

Do we have practical solutions (as opposed to high aspirations) about the best way to serve students in the 21st century?

Hard to say.

I would suggest that the best way to prepare people for the workplace is to evaluate learners as if they were in the workplace. So let's look briefly at the role of certification in this context.

Certification is the ability to prove through testing if an individual has achieved a mastery of skills, knowledge and attitude. Certification can also prove the ability of an individual to apply those skills and knowledge in specified areas and job functions.

(Certification: Corporate America’s Secret Weapon. Hilbink, P. 2004 p.2).

In 1959, Donald L. Kirkpatrick first published his four-level training evaluation model (see Table 1) in a series of articles for the US Training and Development Journal. “The reason for evaluating is to determine the effectiveness of a training program” (Evaluating Training Programs, 2006, p3). The reason for the four-level model then “was to clarify the elusive term evaluation” (2006, xv). In articulating evaluation through each of the four levels – reaction, learning, behaviour and results – the model aspires to

inspire us to look beyond our traditional classroom content delivery model and opens windows to the many way we can improve the performance of our organisations.

(2006, p.xi)

Table 1 Kirkpatrick’s Four-level Model

In the context of Kirkpatrick’s Four Level Model, second-level certification is typically interpreted at Levels Two. We can say that the most effective approach to understanding how well learners have acquired new knowledge, skills, and expertise is to ask them to demonstrate what they have learned: they sit a test. In the context of second-level education, certification assesses the learner at Level 2: Transfer of Learning. It is important to measure learning transfer because no change in behaviour can be expected unless one or more of these learning objectives have been accomplished. Measuring learning means determining one or more of the following metrics:

• What knowledge was learned?
• What skills were developed or improved?
• What attitudes were changed?
  

The benefits to conducting Level Two tests are that the learner must demonstrate that the learning transfer has occurred, and that the assessment provides verifiable and conclusive evidence that an improvement has occurred in knowledge, skills, or attitudes.

Assessment tests are a powerful tool for organisations, institutions and society-at-large, as they combine a hierarchical observation and a normalising judgement. Testing makes individuals visible (who has attained the qualification? who has not attained certification?) and enables them to be categorised (how well did they do?). Exams also normalize people by assessing them according to the same metric, and subsequently measures them in relation to one common standard.

Having established the value of Level Two assessments to understand how well knowledge has been transferred, what next? Does the education system as it currently exists meet the needs of students as they prepare for life in the Information Age, or is there a lag between national educational policies & strategies, and how students' skill need to be shaped?

Substantial resources (time, well-paid teacher, continuous training for educators etc) are required to undertake these types of evaluations, and the ministries and agencies with responsibility for managing these tasks don't seem to have the influencing powers to ensure these assets are in place.

A cynic might say that it's because such an initiative requires long-term planning. The results of such an approach mightn't be seen for five to ten years, and a politician who advocated such a spend on education might not be in a position, a decade or so later, to reap the rewards of such an innovation in national education policy.

_____________________

References:

Hilbink, P. (2004) Certification: Corporate America’s Secret Weapon [Internet] Available from: <http://www.digital-latitudes.com/docs/Cert_White_Paper.pdf> [Accessed 7 July, 2008]

Kirkpatrick, D. & Kirkpatrick, J. (2006) Evaluating Training Programs. 3rd ed. San Francisco, CA: Berrett-Koehler Publishers, Inc.

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It's not the end of the world, you know

Today's blog post is not so much about e-learning or learning and development but rather more about education in general. Whether it's the Leaving Certificate (the final course in the Irish secondary school system), SATs in the US, O- and A-Levels in the UK, or le bac in France, I'm sure you are familiar with the day of reckoning just-finished secondary-level students are facing about now as their results are published in advance of matriculation for third-level and university places, as well as those former students who intend to go straight into employment, or take a gap year to figure out what they want to do with their lives.

Now read on...

In Ireland, the examination results were published yesterday, and today they're released in the UK; tuning in to Irish and British radio and TV broadcasts over the last twenty-four hours you would be forgiven for thinking that we're on the edge of a natural catastrophe (well, apart from the monsoon-like rain we've been experiencing for the last week, but that's another story).

You may be familiar with the format:

• Images / sounds of students opening their results envelopes and shouting for joy / groaning with disappointment
• Vox-pop of said students as they discuss their plans now that they've achieved / failed to achieve the marks they needed
• Outro from reporter which goes along the lines of "... you might not have got what you wanted, but it's not the end of the world, you know" before an short excerpt of some successful local business person or politician describing how they left school at 15 with no qualifications and worked their way up from tea-boy to head of a transnational organisation (before giving out the number of the helpline worried parents can call for advice).

While I completely understand the need to sympathize with devastated young adults who see their hopes, dreams, and career options evaporating before their eyes, I believe that to glibly state that "it's not the end of everything" simultaneously devalues the emotional and psychological impact of performing poorly in such an important life event, and provides false hope that somehow it will be all right.

Sadly, the reality is that in the 21st Century knowledge economy, a less-than-average result in these examinations seriously affects most young peoples' ability to move forward with their lives - particularly in these increasingly straitened times. As the world transitions to an Information Age where the primary asset an individual possesses is their expertise, a misstep on this lowest rung of the ladder has the potential to damage an otherwise bright, intelligent individual's potential to both contribute to, and make their way in their society.

For every business leader who "did it the hard way" or "learned from the university of life," there are ten frustrated employees working in the wrong career, and maybe ten times that number pumping gas, or just about making enough to hang in there, not really living, just existing. Unless you're in a position where you have the financial resources, the family or social contacts, or just the pure luck to break into your chosen path, you have to pretty much generate your own career based upon your abilities and talents - hopefully enhanced by what you learned in school.

I never cease to be amazed by (for example) politicians who state that through hard work and perseverance they finally got elected and rose to the position they're in now... while omitting that their father held the seat before them and they're based in a traditional constituency where the electorate has voted for the 'name they know' for generations, or the business-person who was a millionaire by thirty, through their ceaseless efforts and dedication ...and the fact that they come from a wealthy family with the resources to set them up.

I heard one such person on the radio yesterday who asserted that "all you need to be successful in your chosen career is to be focused on your goal and to be passionate about what you want to do." Try this experiment - say for example you want to be a project manager - send your résumé to as many organisations as you like, outlining your passion, enthusiasm and lack of formal qualifications in the field. Then, wait for the employment offers to roll in.

But don't hold your breath.

Passion is great, but in many cases it's the last resort of the incompetent (look at all those candidates on The Apprentice who, when about to be fired protest that they're "passionate about what they do"). Enthusiasm is an admirable quality, but certainly no substitute for expertise, ability, and experience: organisations understand this, though professional competence is boring and makes for poor reality TV.

Which one of these would YOU hire?

One of the primary reasons I take such joy in my career (and it's not even a logical reason) is that it puts me in a position to see people reach their potential. Aristotle (Nicomachean Ethics) believed that education was fundamental to the human condition - the fulfilled person was an educated person.

Perhaps this week, more than at any other time of the year his assertion that

the roots of education are bitter, but the fruit is sweet

is at it's most evocative and apposite.

_____________

References:

Aristotle. Nicomachean Ethics

_____________

Images' source:

Radio Telefís Éireann image library

BBC. The Apprentice. [Internet] Available from: http://www.bbc.co.uk/apprentice/ Accessed 14 August 2008

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Web 2.0 technologies and learning professionals' opportunities and challenges: LCBBQ July 2008

This month’s Learning Circuit Blog Big Question is should learning professionals be leading the charge in the use of Web 2.0 technologies. More precisely:

• Should workplace learning professionals be leading the charge around these new work literacies?
• Shouldn't they be starting with themselves and helping to develop it throughout the organizations?
• And then shouldn't the learning organization become a driver for the organization?
• And like in the world of libraries don't we need to market ourselves in this capacity?

Should workplace learning professionals be leading the charge around these new work literacies?
The short answer is "Yes, with an if...". Long answer is "No, with a but...". Yes, learning professionals should be at the forefront of orienting and guiding knowledge workers in the use of read / write Web technologies. Knowledge work is, at it's heart, about problem-solving, and knowledge workers are employed to utilize their skills to find solutions to organizational challenges. We can say that knowledge workers are performing at their optimum when they:

• use their deepest skills
• work on many projects at the same time
• know how to allocate their time
• can multiply the results of their efforts through soft factors such as emotional intelligence and trust (Francis Fukuyama, Manuel Castells).

If Web 2.0 technologies enable knowledge workers to undertake these tasks, I believe that it is in the remit of the learning and development arm of knowledge organizations to support this.
However, given that any such learning interventions are undertaken within organizations, there is a corporate responsibility to ensure that any learning initiatives to support learning about Web 2.0 technologies be endorsed by board-level approval of the program with all that entails, which should include

1. recognition for the initiative
2. acknowledgement that it may be difficult to capture metrics on knowledge worker performance enhancement attained through these technologies by more traditional assessment techniques
3. that the learning programs themselves will probably be non- or informal in character, as these Web 2.0 technologies are by their very nature, non- and informal
4. implementing Web 2.0 technologies will probably require substantial investments of time, expertise and capital.

Finding solutions to these challenges is difficult, and many organizations may not understand that this domain is too new to be properly understood at this time.

Shouldn't they be starting with themselves and helping to develop it throughout the organizations?
In my experience, the "throw it over the wall and see where it lands" approach is a non-starter. While learning professionals are typically highly-motivated individuals who expend personal time and effort staying "ahead of the curve" in terms of their own skills and competencies, a "viral approach" to learning in this domain can only have success if the learning professional in question is highly influential within an organization (and probably a C-level executive).

For a "footsoldier" to attempt to modify work practices within a large organization would meet high levels of resistance, particularly from managers who have no desire to change production processes that probably work very well, given the potential disruptions entailed in transitioning to a more collaborative environment.

Shouldn't the learning organization become a driver for the organization?
Most learning professionals would say "Yes", most execs would (probably) say "No."

In my view, organizations function best when the organization's business goals are aligned with their learning goals; ideally the two should support and drive each other. If learning professionals can persuade the executive team that a Learning organization is an Earning organization, then they will usually receive the support to operationalize innovative learning initiatives.

Like in the world of libraries don't we need to market ourselves in this capacity?
Yes, yes, and yes again.

If you are familiar with the 1989 motion picture Field of Dreams, you'll know the mantra of one of the lead characters is "if you build it, they will come."

Yes, if you build it (the learning initiative) they will come.

...But only if they know it's there.

I believe that it is the responsibility of learning professionals both in an individual as well as in a departmental capacity to broadcast what they do and they services they offer at every opportunity. Without resorting to spin, lies, and weasel words, the only way your voice will be heard in the bustle of the marketplace (whether internally within an organization or externally facing) is to "say it loud, and say it proud" about your learning and development offerings and services.

Use what ever resources are at your disposal to do so, and don't forget that as a trainer, you're probably in a position to influence a wider range of individuals in your workplace than those in any other department, except perhaps for Human Resources and ICT.

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Corporate learning environments - a framework

As discussed in previous blog entries, the 21st century corporate learning environment is a patchwork of systems, tools, technologies, and processes that support (more or less) individual and team learning, performance, and development.

We can say with a degree of certainty that it's the case that these systems are in place for a range of tactical, operational, and strategic reasons. According to Klein and Eseryl (2005) this agglomeration of systems can be viewed within

a framework based on the premise that different methods are needed for different levels of knowledge and expertise.

(The Corporate Learning Environment, p.8)

Klein and Eseryl extend Dillon and Hallett's 2001 learning curve model; by making it the basis for a framework (see Figure 1) that applies the notion of the conventional learning curve to the context of the corporate learning environment, they assert that to supply an "apt" structure for understanding when and how different learning approaches and strategies are used.

Figure 1 Framework for corporate learning environments (After Klein & Eseryl 2006)

[click to enlarge]

Within this framework, the conceptualization of the learning environment consists of systems to manage and support:

1. cohesive team management
2. knowledge generation and sharing
3. performance support
4. document storage and retrieval
5. on-demand learning
6. traditional training

___________________

References:

Dillon, P. & Hallett, C. (2001). Powering the leap to maturity: The eLearning ecosystem. Cisco Systems white paper.

Klein, J. Eseryel, D. (2005) The Corporate Learning Environment. [Internet] Available from: http://www.igi-pub.com/downloads/excerpts/159140505XCh1.pdf
Accessed June 12 2008
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The E-learning Ecosystem in organizations

In the previous E-Learning Curve Blog entry on this topic 'adapting to knowledge workers learning needs in organizations,' I made a case for the benefits of e-learning as a means to providing workers with the appropriate and relevant learning interventions as they progress from neophyte to mastery of their particular skills, experience and expertise.

By adapting the well-known learning curve, I developed a conceptual model that maps Bloom's Taxonomy of Learning Objectives to learner requirements as they progress along the curve (see Figure 1).

Figure 1. Learning Curve model aligning Bloom's Taxonomy and components of the E-learning Ecosystem

In today's blog post, I'll look at preconditions for introducing learning modalities to this model.

Now read on.

There are two components involved in investigating this aspect of e-learning as a means to enhance knowledge worker performance:

1. E-learning tools and technologies
2. Applying effective learning modalities to learning requirements

E-learning tools and technologies

In their influential white paper Powering the leap to maturity: The eLearning ecosystem, Dillon & Hallet define the concept of the "E-learning EcoSystem." The authors assert that a "blended approach" where instructor-led resources are deployed at the earliest stages of a learner's development, and increasingly, e-learning solutions are implemented as the learner develops.

With Web-based training, as with its manual counterpart in the classroom, the zone of applicability is actually quite limited. The only time it makes sense to pull workers off their jobs for training is limited precisely to those times when no other alternative will suffice. Off the- job forms of training make good business sense only when workers are at the bottom of the learning curve and are not yet equipped to perform at any acceptable level of competence.

(p.19)

Through "pervasive connectivity" (p.19), characterized by the growth of deployment of corporate portals and intranets, as well as learning support technologies such as content management systems and knowledgebases, and is the foundation for their e-learning ecosystem. In my view, the choice of terminology that the authors use is interesting; by employing the term ecosystem -

a system whose members benefit from each other's participation via symbiotic relationships... It is a term that originated from biology, and refers to self-sustaining systems,

(LearnThat.com)

they imply that the nature (no pun intended) of organizations parallels complex natural systems. Similarly, a functioning learning ecosphere holistically supports a diverse range of learning modalities which enable the learner to thrive in the corporate environment.

As workers move up the e-learning curve, they quickly leave the relative isolation of pure asynchronous courseware. Initially, they enter the more richly supported environment of the online university, backed by an enterprise-level learning management system.

(p.20)

Progressing along the curve, the authors note the introduction of just-in-time forms of learning content delivery.

As we move even further up the e-learning curve we encounter yet another interesting revelation. Most of the learning technologies at this end of the curve are not generally recognized as “learning” technologies at all. Rather, such items as collaboration tools and intelligent search are more typically thought of as knowledge management technologies. Deploying and utilizing these types of tools are what differentiates an employee from a “performer.”

(pp. 20-21)

Having characterised the e-learning ecosystem, Dillon & Hallet define the components of it:

• Web-base training
• Online university
• Learning Objects
• Electronic Performance Support Systems
• Collaboration
• Intelligent Search

As they suggest, these components "put the 'system' in ecosystem" - a statement that I would suggest is doubly true: by describing the technologies (and to a lesser extent on technology and learning solutions vendors) in their white paper, they neglect to lend appropriate weight to how these systems are implemented.

More.

FÓGRA: Malinka Ivanova of the Technical University in Sofia has an interesting perspective on this topic. Click here to find out more.
_____________________

References:

Definition of "Ecosystem." Learnthat.com. [Internet] Available from: http://www.learnthat.com/define/view.asp?id=302 Accessed 30 May 2008.

Dillon, P. & Hallett, C. (2001, October). Powering the leap to maturity: The eLearning ecosystem. Cisco Systems white paper.

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