E-Learning along the curve: adapting to knowledge workers learning needs in organizations

As I discussed in the previous blog entry, formal, structured approaches to learning (such as to both instructor-led and traditional CBT-type training interventions), which by their nature are long in duration, relatively generalized in terms of subject matter, and are best deployed to novices in the relevant discipline or skill area. As such, they represent the best value for organizations when to knowledge worker is not expected to be a full contributor in their role. In this context, I would suggest that organizations can justify using these learning solutions for situations such as

• 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.

(The Learning Curve, p.2)

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).

Figure 1. Levels of mastery and appropriate learning strategies (after Marc J. Rosenberg, 2006)

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).

Figure 2. Advantages of workflow learning (after Marc J. Rosenberg, 2006)

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.
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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.

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E-learning & Knowledge Management

As you'll know if you've been following the last few posts, I've been evaluating the term "e-learning." After a brief investigation of the current thinking on this term, I chose Don Morrison's definition as the most satisfactory.

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.