Feature

posted 31 May 2006 in Volume 9 Issue 9

Masterclass

E-learning strategy Part I

Oliver Schwabe presents an in-depth three-part masterclass for creating a corporate-wide e-learning strategy.

On the face of it, implementing an e-learning strategy ought to be easy. But despite the increasing maturity of e-learning software and the e-learning marketplace – as reflected in the prolific merger and acquisition activity that has taken place in recent years – it remains a costly and sometimes unsatisfactory process.

In this three-part masterclass, value and social networks methodologies¹ will be used to explain how to build high-performance e-learning spaces that can deliver business benefits at a relatively low cost.

This article is the first of a series of three that will start by defining the focus of the real value of e-learning in a knowledge-based organisation, before moving on to key process definition and, finally, tackling e-learning space design.

Introduction

In the knowledge-based economy, effective and efficient delivery of learning to staff across the organisation is vital for it simply to maintain a competitive position, let alone to achieve competitive advantage, especially as staff must increasingly share information and make decisions across business and national boundaries.

The delivery of such learning experiences is commonly termed ‘e-learning’, but it is modelled on traditional learning approaches that have been developed over the centuries. Essentially based upon a classroom and teacher paradigm, e-learning as it is commonly conducted today, at best provides a multi-medial translation of these paradigms into a technology-supported virtual environment.

High-performance e-learning spaces²:

1. Ensure that knowledge is created by all participants;

2. Move knowledge from origin to the point of highest need;

3. Encourage collaboration for mutual benefit.

While the efficiency of such learning methods represents a significant improvement, from a traditional return on investment (ROI) perspective compared to traditional educational approaches, the overall effectiveness remains in line or even somewhat lower when examined from the learner’s perspective. A fresh approach is therefore required if an organisation is to make the most of e-learning.

This three-part article will explore how more effective e-learning methods can be designed, developed and managed in a manner that makes full use of the technology available today. From a practitioner’s perspective the following critical questions will be addressed:

How can e-learning (or ‘virtual learning’) costs be minimised?
How can the value generated for the learner through virtual learning be maximised?
How can the value generated for the organisation through virtual learning be maximised?
How can resistance to virtual learning measures be managed more successfully?

There are a number of good reasons to ask these questions³:

Even though the financial ROI of e-learning can be impressive, the break-even points are shifting further into the distance due to the increasing cost of packaged learning-management systems – not just licences, but also implementation and ongoing management, too;
E-learning is significantly less powerful in transferring tacit knowledge than traditional classroom-based learning;
Training departments are being forced into the role of information technology specialist when selecting learning management and delivery solutions.

Re-defining goals

The first step in this exploration is to re-define the goals of e-learning. A common approach to assessing and measuring virtual-value creation is to focus, naturally enough, on training effectiveness. Assessing training effectiveness often entails using the four-level model developed by Donald Kirkpatrick⁴. According to this model, there are four levels of evaluating the effectiveness of learning:

Level one – Reactions

Measuring the reaction of the students and their perception of the teaching activity attended;

Level two – Learning

Measuring the improvement in competency, ability, capacity and skills that have been acquired due to the training activities;

Level three – Transfer

This level measures the transfer that has occurred in learners’ behaviour due to the training program;

Level four – Results

Level four evaluation attempts to assess training in terms of business results.

However, it cannot be emphasised strongly enough: e-learning performance metrics today must be defined based upon the impact on business systems.

The challenge most often encountered when using this assessment structure is that while the first two levels can be quite easily achieved by a dedicated training department, levels three and four depend heavily upon the help of those who will benefit from the knowledge gained by a participant and who will fund the effort (that is to say, the participant’s employer, also called the ‘knowledge beneficiary’).

It is this stakeholder that determines the effectiveness of virtual learning but they are also the stakeholder who is usually the least involved in this evaluation effort. Therefore, assuming that the knowledge beneficiary has eluded successful integration into virtual learning concepts, it is well worth reflecting upon the other critical roles involved. If we have missed one key player, have we perhaps missed others?

When we focus on the knowledge that will be generated through e-learning and put to use for value generation, we quickly recognise that the participant of such an experience (that is to say, the student), is in fact a ‘knowledge creator’. Assuming that knowledge is always tacit, then the deliverer (the teacher) in fact becomes a ‘knowledge creation enabler’. Based upon this re-definition we can then proceed to mapping the value network of a virtual learning experience.

Fundamental to this is the understanding that we are not enabling value generation within static environments. The value of knowledge – particular in the current fast-moving economic climate – needs to be understood as the knowledge flow⁵ required by the ‘knowledge beneficiary’. It is this environment, the way in which knowledge moves between people within organisations – that we consider the ‘value network’⁶ of the virtual learning experience.

Dealing with this therefore places high demands on the approaches and tools used for enabling value creation through e-learning. Gaining knowledge, a process we call ‘learning’, is therefore something inherently dynamic, volatile, personal and individual. When we explore the value network that the e-learning experience exists within, we identify participants and transactions – the ‘knowledge exchanges’ between participants. A full schematic outlining the complex inter-relationships involved here is available on request from the author.

Roles in the business system

The high-performance e-learning space consists of a number of core roles that interact to generate value. These roles are:

Knowledge creators

Knowledge creators are those people who, either individually or in groups, attend an e-learning event in order to create and learn the knowledge they require to fulfil their needs. They are not passive recipients of information, as in a classic classroom setting, but intensively and actively engage with content, their peers and others (including the knowledge beneficiary, knowledge creator supporters and the knowledge creation enablers) not just to learn, but also to help create the desired knowledge and generate the intended value. The challenge that knowledge creators face is moving from passive content consumption for a single stakeholder (ie: teachers) to pro-active content intended for multiple stakeholders.

Knowledge creation enablers

Knowledge creation enablers are those individuals who facilitate the e-learning event. Their primary task is to facilitate the ‘learning curve’ and experience of the knowledge creators in accord with the requirements of the course provider. It is their goal to ensure that the needs of the knowledge beneficiaries are fulfilled as expected. Of significant importance in this respect is the intangible side of their relationship with the knowledge creators, since this acts as the catalyst for knowledge creation. The knowledge creation enabler also helps facilitate the relationship of the knowledge creators to the course provider and the knowledge creator supporters.

Knowledge creator’s supporters

The knowledge creator’s supporters are those individuals who enable the knowledge creators to fulfil the needs of the knowledge beneficiary. In some environments this could simply be the family that encourages the knowledge creator to master the challenges being faced, that provides the time for this to be accomplished and the context for celebration when goals are reached. In other contexts it may be the organisation that employs the knowledge creator. The knowledge creator’s supporters are also heavily involved in the motivation and expectation setting of the knowledge creator.

The knowledge beneficiary

The knowledge beneficiaries are those individuals and organisations that intend to benefit from the value generated from the knowledge created by the knowledge creators – typically a company or employer. This role is often assumed by organisations that need staff with new knowledge to perform certain tasks. It is important to note in this respect that while the knowledge beneficiary communicates needs to the course provider, the process for this ‘needs identification’ can be quite varied.

The course provider

The course provider is the organisation responsible for designing, developing, hosting, marketing, selling and managing the delivery of courses (or ‘knowledge-creation opportunities’) to the knowledge creators. The course provider ensures that the requirements of the quality controller are met in the delivery of knowledge-creation opportunities to the knowledge creators. It is the course provider that contracts formally with the knowledge beneficiary.

The quality controller

The quality controller is a local, regional, national, international or global organisation that audits and reviews the performance of course providers in accord with common standards – similar to an examination board or the way that Microsoft sets the standards for training courses on Microsoft software products. In many cases the quality controller also heavily influences the brand of the course provider, hence the relationship between the course provider and the knowledge beneficiary.

The information compiler

The information compiler is tasked by the course provider to collect, collate and prepare practitioners’ content and experience based upon the knowledge beneficiaries’ needs. This role is usually filled by an individual who is an experienced practitioner with close ties to the content practitioner community and who also has an understanding of the aptitudes of knowledge creators. The main challenge for the information compiler is to turn the tacit knowledge of content practitioners into information that can be structured for delivery to the knowledge creators.

Content practitioners

Content practitioners are the experts – the people who make their living from developing and using the concepts, skills and stories of particular courses for the course provider. It is their knowledge that the knowledge beneficiary is interested in attaining. This community is usually a virtual one and publishes information about its activities in a multitude of environments.

The information designer

The information designer transforms the raw content provided by the information compiler and turns it into a form suitable for presentation to the knowledge beneficiary via the platforms provided by the information provider. This content can be produced in a variety of multi-medial forms and be structured in such a manner that an iterative learning track is provided to the knowledge beneficiary.

The information provider

The information provider is, in essence, the provider of the technical platforms associated with the delivery of the course information to the knowledge creator. This role therefore provides a variety of technical channels between course content and the knowledge creator, as well as the collaborative infrastructure required to enable the relationship between the knowledge creator, knowledge creator enabler and course provider. The information provider supports e-learning by providing the optimally structured content via a suitable technical platform.

The key relationships

Based upon the definition of the high-performance e-learning space and its roles above, we can now turn to exploring the five key pair-relationships involved. These are illustrated in figures one to five [please contact author for schematics] and show both the tangible and intangible relationships.

A question of purpose

Based upon the value-network defined, we need to explore the core purpose the e-learning course has been designed to fulfil. Every system has a real purpose it works to fulfil. But we need to be aware that this purpose may differ from the purpose originally expected, desired or demanded by any single stakeholder.

Indeed, sometimes the espoused purpose of a value network can actually be quite different from its actual purpose, as revealed by its activities. As we have seen above, knowledge creation is unique in every context and, hence, when designing, developing and deploying such value networks we need to reflect carefully why they really exist – their core purpose – and, indeed, which other value networks it may serve. Nor do they exist in isolation – each node is a gateway to other value networks.

In general, and in the interest of practicality, a close look needs to be taken at the needs of the knowledge creator, the knowledge beneficiary, the knowledge creator’s supporters and the knowledge creation enabler. It is these four roles that could be considered the customers of a more condensed value network, as presented in figure six on page 36.

However, it is always important to ask what is missing or who has not been included. In traditional settings the roles of the knowledge creation enabler and the knowledge beneficiary are often overlooked since examining the latter demands a higher accountability of the course provider for value generation, and examining the former opens up the discussion whether it is the content or behavioural knowledge of a facilitator that is more critical and should be the performance basis.

Overall, the value network presented here can be understood as a model for designing, developing, and implementing high performance e-learning systems. The key factors associated with this are, or should be:

The participants all consider themselves to be part of a single ‘living system’ that is serving the purpose of improving organisational impact. Value gained by one participant therefore extends to other participants in a way that accrues value for the value network as a whole;
There is a high level of trust among participants;
All participants share common measures for evaluating overall value network performance;
Every interaction is used consciously to create value and build relationships;
All participants understand their interdependence;
Every participant is both contributing and receiving value from the network as a whole. None gain value at the expense of another;
There is a consistent pattern of reciprocity of exchanges is an indicator of healthy value flows and whole-system optimisation;
There are no bottlenecks, constraints, or instability in the flow of value;
Every action either triggers another transaction or has an internal impact on the participant who is the recipient;
Individuals will regularly participate in a number of other roles;
There are no disconnects between the role people think they play and the role that is actually represented by their interactions;
The ‘heartbeat’ of the network is formed by those with the greatest passion for the business value created – the knowledge beneficiary, the knowledge creator and the knowledge creation enabler.

Towards new measures for learning⁷

Based upon our reflections so far, the need for a re-definition of performance metrics becomes apparent. If the focus lies on enabling the value network to deliver what Kirkpatrick describes as level three and level four benefits, then we indeed need to re-frame the indicators of relevance.

While the third article will explore the specific indicators of relevance, there are some fundamental questions we can apply to the value network in order to determine whether it is functioning with reasonable efficiency. Prime questions to ask include, to what extent do the participants:

Keep each other sufficiently informed?
Proactively share their expertise and competence as needed?
Continuously bring in new competencies and build expertise?
Are open in their communication and respect each others different perspectives?
Continuously come up with innovative solutions?
Continuously and naturally share competencies, know-how and expertise?
Build their own competencies/ expertise through collaboration; need each other?
Help each other to learn the skills they need?

Note: The performance of the e-learning value network is directly related to the capability of its facilitator. Finally, through the application of value and social network analysis principles [see IK, June-October 2005], the following key indicators⁸ can be examined based upon a current state assessment of the relevant e-learning value network:

The relationship between tangible and intangible transactions actually lived;
The perceived transactional value;
The network density;
The reciprocity in the network;
The geodesic distance in the network;
The degree centrality;⁹
The ‘betweenness’ centrality;
Krackhardt’s graph theoretical dimensions (GTD) measures of hierarchy.¹⁰

What this also illustrates is that the performance level of a business system can be measured!¹¹ Taking the above two perspectives together the basis is set for the definition of new performance and hence management measures of e-learning efforts. Critical to remember, though, is that since we are dealing with living systems complexity is a firm factor in our efforts, which demands distance from command-and-control efforts and a movement towards an exploratory learning focus.

Summary

Designing, developing and deploying high-performance e-learning spaces must focus on the fast and cost-effective impact on business systems. Traditional e-learning performance metrics are not suited for the "e-" context of virtually collaboration knowledge workers and organisations.

To ensure that e-learning spaces deliver high-performance their value network must be facilitated in a manner akin to the ‘jamming’ of musicians, where relationships become the focus of interest and a living system evolves. This facilitation demand calls for a redefinition of many present roles, processes and performance measures.

In the next article the focus will be placed on the key scenarios that the value network presented here must deliver upon. In essence these can be considered as the processes within the value network.The key scenarios in e-learning are:

Needs analysis;
Content design and development;
Content provisioning;
Knowledge validation;
Knowledge creation;
Knowledge application.

Once these have been defined a number of case studies will be presented and contrasted against the benchmark being set in this article. Based upon an exploration of these scenarios the third article will focus on the specific performance measures required to build and maintain e-learning spaces where the impact is significant and fast, including the relevant measures that must be taken to create such spaces.

Dr. Oliver Schwabe has been involved with virtual learning since 2000. In this time he has personally designed, delivered and deployed a wide variety of academic and professional distance learning courses for a wide variety of non-profit, private and commercial organisations, and to approximately 200 different students monthly – about 2400 students every year. His company, Eurofocus International Consultants, www.euro-focus.com, is among others specialised in using advance e-learning approaches for effective e-learning approaches. He can be contacted at oliver_schwabe@t-online.de

Definitions

E-learning space: The context within which the e-learning event takes place;
E-learning: Value generation through virtual relationships;
Knowledge: Competence held exclusively by people;
Learning: The creation, evolution, exchange and application of knowledge;
Relationship: The sustained synchronous or asynchronous exchange of information between people;
Value: The creation, evolution, exchange and application of knowledge for economic and other benefits¹²;
Virtual relationship: A relationship supported and enabled through collaborative technologies.

References

1. http://en.wikipedia.org/wiki/ Social_Network_Analysis;

2. Based upon the "Laws of Knowledge Dynamics", Amidon, Debra M., Formica, Piero and Mercier-Laurent, Eunika (Eds.) (2006), Knowledge Economics: Principles, Practices and Policies. Tartu University Press;

3. See also Allee, V. 1997. The Knowledge Evolution: Expanding Organizational Intelligence. Boston: Butterworth-Heinemann;

4. Kirkpatrick, D.L. (1994). Evaluating Training Programs: The Four Levels. San Francisco, CA: Berrett-Koehler;

5. A Knowledge-based Theory of the Firm to guide Strategy Formulation.http:// www.sveiby.com/articles/Knowledgetheoryoffirm.htm;

6. Allee, V. 2002. The Future of Knowledge Increasing Prosperity through Value Networks. Boston: Butterworth-Heinemann;

7. Measure for Learning! (Sveiby 2004). Key note IC Congress, Helsinki. http://www.sveiby.com/ articles/measuretolearn.pdf;

8. Partially based upon Hanneman, Robert A. and Mark Riddle. 2005. Introduction to social network methods. Riverside, CA: University of California, Riverside;

9. Freeman LC. Centrality in social networks I: conceptual clarification. Social Networks. 1979;1:215–239;

10. McGrath C, Krackhardt D. Network conditions for organizational change. J Appl Behav Sci. 2003;39:324–336;

11. See Borgatti, S.P., Everett, M.G. and Freeman, L.C. 2002. Ucinet for Windows: Software for Social Network Analysis. Cambridge, Mass: Analytic Technologies; 2002., and GenIsisTM for value network creation and analysis, Germany;

12. Amidon, Debra M., "The Innovation SuperHighway: Harnessing Intellectual Capital for Sustainable Collaborative Advantage" 2003.