In a Learning 2.0 world, where learning and performance solutions take on a wider variety of forms and where churn happens at a much more rapid pace, what new skills and knowledge are required for learning professionals?

As Harold Jarche and Jay Cross have already addressed the “learning” part of the discussion with informative and illuminating posts on the topic I’m going to talk about the business aspect of the “performance” element highlighted in The Big Question.

Now read on…

I strongly believe that to survive and maybe even prosper in these leaner economic times, those of us involved in L&D need to understand that we are also business people. As in any enterprise, we are connected to our customers and clients through a variety of sophisticated and interconnecting partnerships: with organizations, with vendors, with the board of directors, with employees, and ultimately and most importantly with learners.

Our product is our special expertise in learning and development (and all that this entails), and our market is more competitive now than it has ever been. I would assert that if, as a trainer, you feel that you are somehow shielded from the realities of business in the early 21st century, you probably won’t have much of a career in five years time.

Enterprises need e-learning. The pace of organizational change in most companies requires a constant refreshing of skills and the continual development of new competencies. In many organizations, not choosing e-learning as a method to deliver key training initiatives usually means it will not be delivered at all. To remain competitive, enterprises need to:

• Provide continual, up-to-date training and professional development
• Distributable to knowledge workers across multiple delivery channels
• Implement scalable training solutions
• Ensure plan is developed and deployed within a matter of months, rather than quarters or years
• $$$ Demonstrate economic viability $$$

Learning professionals should heed their organizations’ strategic and business imperatives, align with them, and deliver appropriate solutions to support them. To make this happen, my view is that learning professionals need to have (or should develop) the skills and expertise to perform in the following domains:

Sadly none of this is sexy, but it’s what I believe you need to accomplish to be successful in this domain.

In meetings in my organization I have been known say that being a learning & development professional is a bit like running a truck company. It’s my job to get stuff to the people who need it, and to be honest my customers don’t really care how it gets there, once it arrives on time and it good shape. To extend the analogy, I could argue that Web 1.0 e-learning was like a sports car – it looked great and made a big impact wherever it arrived, but it was quite impractical, required a lot of TLC and maintenance, and while it may be high-performing on the (one-way) racetrack of the information superhighway, try maneuvering it around the multi-storey car park of most organizations’ networks.

Web 2.0 is without equal at delivering vast amounts of information. It is an accessible, multiplex environment, so data can move back, forth, left, right – wherever it needs to go. Learning 2.0 leverages this facility exceptionally well, because communication of knowledge, skills, and expertise, is at the heart of training and learning.

Learning professionals who have supplemented their educational expertise with broader business skills have positioned themselves to add value to their enterprise facilitating their organizations’ performance requirements, and their customers’ learning needs. And that is a win-win situation. 

–

• entry-level or new hire orientation and competency building
• internal transfers to a new discipline (i.e. the worker moves from Production to QA)
• retraining on a new production system (i.e. a new type of widget-making tool or a new software system)
• employee career advancement (i.e. from individual contributor to manager)

Psychology tells us that the learning curve obeys what is called a power law (Ritter & Scholler, 2002).

As such they are often said to conform to “the power law of practice”. Cognitive psychology has shown that the power law of practice is ubiquitous, and cognitive modeling has explained both the general speedup and variability in performance.

So, as a worker learns a task, skill, or process (”progresses along the learning curve”), their competency improves and productivity increases with some variations but broadly within generally accepted parameters.

As workers advance from their neophyte status, they begin to attain what Marc J. Rosenberg (2006) calls “performer” status; the are transitioning from being Novice to Competent, along a path that will enable them to become Experienced, until they achieve Expert (or Master) status.

We can also say that once a worker reaches a certain level of competence, their learning needs are met less by generic courses and curricula, and more by specific, even personalized, learning interventions such as task/skill practise and coaching, access to knowledge and performance resources, and collaboration and problem solving (see Figure 1).

As an extension of this (and effectively demonstrated by Rosenberg), organizations failing to move beyond the classroom or traditional CBT-type courseware for their ongoing learning and development needs, are probably impeding the development of their workers, as well as negatively affecting their (the organization’s) own potential (see Figure 2).

In order to provide effective learning and performance support to workers after they become competent, organizations must strive to develop their workers’ skills as employees undertake their regular workplace activities. It is my view that this level of performance support can only be provided through access to networked knowledge assets.

And that is what I’ll be discussing tomorrow.
______________________

References:

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

Ritter, F. E., & Schooler, L. J. (2002). The learning curve. In International encyclopedia of the social and behavioral sciences. 8602-8605. Amsterdam: Pergamon.
[Internet] Available from: http://www.iesbs.com/ Accessed 27 May 2008.

Rosenberg, M. J. (2006) Beyond e-Learning. San Francisco, CA: John Wiley & Sons, Inc.

–

• entry-level or new hire orientation and competency building
• internal transfers to a new discipline (i.e. the worker moves from Production to QA)
• retraining on a new production system (i.e. a new type of widget-making tool or a new software system)
• employee career advancement (i.e. from individual contributor to manager)

Psychology tells us that the learning curve obeys what is called a power law (Ritter & Scholler, 2002).

As such they are often said to conform to “the power law of practice”. Cognitive psychology has shown that the power law of practice is ubiquitous, and cognitive modeling has explained both the general speedup and variability in performance.

So, as a worker learns a task, skill, or process (”progresses along the learning curve”), their competency improves and productivity increases with some variations but broadly within generally accepted parameters.

As workers advance from their neophyte status, they begin to attain what Marc J. Rosenberg (2006) calls “performer” status; the are transitioning from being Novice to Competent, along a path that will enable them to become Experienced, until they achieve Expert (or Master) status.

We can also say that once a worker reaches a certain level of competence, their learning needs are met less by generic courses and curricula, and more by specific, even personalized, learning interventions such as task/skill practise and coaching, access to knowledge and performance resources, and collaboration and problem solving (see Figure 1).

As an extension of this (and effectively demonstrated by Rosenberg), organizations failing to move beyond the classroom or traditional CBT-type courseware for their ongoing learning and development needs, are probably impeding the development of their workers, as well as negatively affecting their (the organization’s) own potential (see Figure 2).

In order to provide effective learning and performance support to workers after they become competent, organizations must strive to develop their workers’ skills as employees undertake their regular workplace activities. It is my view that this level of performance support can only be provided through access to networked knowledge assets.

And that is what I’ll be discussing tomorrow.
______________________

References:

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

Ritter, F. E., & Schooler, L. J. (2002). The learning curve. In International encyclopedia of the social and behavioral sciences. 8602-8605. Amsterdam: Pergamon.
[Internet] Available from: http://www.iesbs.com/ Accessed 27 May 2008.

Rosenberg, M. J. (2006) Beyond e-Learning. San Francisco, CA: John Wiley & Sons, Inc.

–

Why? Well, by analysing the key terms in Morrison ’s definition, and scrutinising them in the context of the literature. I’ve looked at “andragogy” and “synchronous & asynchronous” so far; today, I’m dissecting “knowledge management. As a reminder, here’s Don’s definition:

The continuous assimilation of knowledge and skills by adults stimulated by synchronous and asynchronous learning events – and sometimes Knowledge management outputs – which are authored, delivered engaged with, supported and administered using internet technologies.

(2004, p.4)

The term Knowledge Management (KM) has been described as “the process of capturing, sharing, and leveraging a company’s collective expertise” (Botkin, 1999, p.40). I would assert that there is an anthropological aspect to the process of managing knowledge in an organisation; as we have seen earlier in this chapter, it can be argued that there is a social-cultural element to how individuals work and learn together in an organisation’s structures.

Claude Levi-Strauss, eminent structuralist and ethnographer of the Trobriand Islanders coined the phrase ‘the raw and the cooked’ in Mythologiques, Volume 1 to signify the dichotomy between elements falling along the ‘raw’ category as being of ‘natural’ origin, and those on the “cooked” side being of ‘cultural’ origin – i.e. products of human creation (Lévi-Strauss, 1966). Morrison echoes this comparison when he describes e-learning as processed (i.e. cooked) knowledge – it “takes subject matter expertise, puts it through an instructional design process and presents the result in an obvious framework. KM delivers raw, or at the very least, less processed knowledge” (p.7). Rosenberg (2006, p.106) places KM at the core of the Smart Enterprise (see Figure 1.1) Rather than seeing e-learning and KM as information in differing states of mediation existing on a knowledge and e-learning continuum, he views them as modular elements within a larger Learning and Performance Architecture. He sees the goal of any KM strategy as to enhance the organisations performance by making “undiscovered” (2006, p.106) or tacit knowledge “common” (p.106) or organisational, and making information “known and available” (p.106) to all those who need it. Like Morrison, he suggests that knowledge assets within organisations can manifest themselves in numerous shapes and sizes, from learning IM chat messages, email, content assets, learning objects, business process documents, white papers and so forth.

Figure 1.1 Learning and Performance Architecture ((after Marc J. Rosenberg))

Rosenberg also posits that KM can function as a framework for learning content – what he describes as the difference between “Course-centric and Knowledge-centric viewpoints” (p.112). Taking the example of a Java software development course (see Figure 1.2), he argues that this viewpoint is more “robust” (p.113) than the course-centric viewpoint, as the learner has the ability to navigate through a “wide array of resources: experts, information repositories, live events and virtual communities” (p.113) as well as the relevant courseware.

Figure 1.2 Knowledge-centric View of Knowledge (after Marc J. Rosenberg)

This arrangement provides a much more comprehensive and interrelated set of relationships between knowledge assets by systematically exposing more resources to where they can be found (pp.112-113).

References:

Botkin, J. W, (1999). Smart business: how knowledge communities can revolutionize your company. New York: The Free Press.

Lévi-Strauss, C (1966) The Raw and the Cooked: Mythologiques, Vol. 1. Penguin Books Ltd.

Rosenberg, M. J. (2001) e-Learning: Strategies for Delivering Knowledge in the Digital Age London: McGraw-Hill.

Morrison, D. (2004) E-Learning Strategies: how to get implementation and delivery right first time, Chichester: John Wiley & Sons, Ltd.

Rosenberg, M. J. (2006) Beyond e-Learning. San Francisco, CA: John Wiley & Sons, Inc.