Acknowledgements:

This article has benefited from comments by a number of researchers, among whom Bo B. Nielsen (Western Washington University, USA & Copenhagen Business School), Steen Ehlers, Michael Pettersson, Henrik Herlau, Claus G. Jacobsen (all four of the Copenhagen Business School) and Lasse Rangstrup (Catinet Research) are the most important. It has also benefitted from comments provided by two anonymous referees. Any oversimplification or outright errors that remain are entirely my own responsibility.

E-learning, one of the buzzwords of the early 21^st century, is usually understood as learning by electronic means, but this definition is very broad and signifies different things for different firms and people. Thus the e-learning label has been pinned on everything from off-line learning software to advanced on-line learning in virtual learning spaces.

Correspondingly, all possible notions and ideas of e-learning have thrived among suppliers and buyers; this diversity of interpretation is also apparent in the press coverage and academic treatment of e-learning. If the field appears multi-faceted to academics, it must seem somewhat chaotic to decision-makers, who, in the end, may have little to gain from consultants with a vested interest in selling their particular products.

This article maintains that while ideas, notions and products are subject to great variation, this variation still follows certain systematic and ordered patterns. The observed order can be used to disentangle the field of e-learning and identify several possible avenues of development. By implication, the development of a successful e-learning strategy in educational institutions as well as in corporations and society at large can be facilitated.

Much research on e-learning is predominantly inspired by theories of communication, organization and pedagogy and by developments in information technology. This article, in contrast, draws inspiration from theories of economics and sociology, the theory of marketing management and strategy, and especially from the author’s practical work on developing e-learning systems and processes (for example, as described in Smith & Duus, 2001; Pettersson, 2002; Duus and Ehlers, 2002; 2004; Pettersson, 2005, 2008; Lindberg & Pettersson, 2007).

Following the introduction, the article proceeds with some conceptual and methodological considerations on how e-learning can be researched and how the field can be subdivided and understood. These considerations are heavily influenced by theories from economics, corporate strategy and marketing. Subsequently, a sociological model is developed for the subdivision of views on e-learning into four different ideal-typical paradigms. The differences, similarities, possibilities and limitations of each paradigm are identified and used to evaluate the potential of each paradigm. To conclude, strategic implications for firms, learning institutions and society are developed and outlined.

What is meant by e-learning and how should the field be researched? In recent years, scholars, analysts and journalists have attempted to describe and analyze the field of e-learning to create some order, structure or overview. Many of these attempts have been only marginally successful. One reason is that most such attempts can be classified in one of the three following categories, each of which focuses on a specific aspect of e-learning, thus excluding the big picture:

A number of studies also suffer from methodological problems that make it difficult to attain an overview. Among the most common are:

Therefore, a sensible research approach to the field of e-learning should include action research among forefront suppliers combined with an angle not derived exclusively from pedagogy, technology and communication studies or from simple superficial market studies.

Since e-learning solutions are produced by someone (the suppliers) and are in demand by others (buyers or users), an economic point of view may prove useful, especially in regard to achieving a correct picture of the industries and markets within the field. Received economic theory states that there are two different (only partially complementary) ways of defining industries as well as two complementary ways of defining markets.

The Porterian industry definition posits that an industry is a group of firms producing products that are close substitutes (Porter, 1980), whereas the Abellian definition defines an industry as a group of firms sharing identical supply characteristics (in the form of technology, knowledge and competencies) that may potentially satisfy several distinct customer groups and their needs (Abell, 1980, 1993) [1].

Correspondingly, the classic market definition states that a market consists of products that are close substitutes (Rasmussen, 1977). This is accordance with the more complex Abellian market definition, which defines the market by the distinct needs of a specific customer group. These needs may potentially be satisfied by different firm-specific bundles of technology, knowledge and competencies (Abell, 1980, 1993).

Put briefly, a market and an industry are two very different concepts that mirror one another. An industry is defined by its supply characteristics and is open-ended on the demand side, whereas a market is defined by its demand characteristics and is open-ended on the supply side.

If the tools of economic theory are applied to the field of e-learning, it becomes clear that it is meaningless to talk about one single e-learning market. Rather, the field consists of literally thousands of smaller markets, depending on how many customer groups and adjacent needs are defined.

Accordingly, more than one e-learning industry must be defined depending on the distribution of competencies and knowledge. Industry definitions may be conceived along the lines of a functional subdivision depending on what the e-learning delivery systems “do” and are potentially capable of. The premise here is that such a functional subdivision reflects underlying differences in competencies and knowledge.

Over the last decade, several economists have maintained that such a functional subdivision has emerged in the distinction between knowledge creation e-learning and knowledge transfer e-learning (Pettersson 2002, 2005, 2008; Lindberg & Pettersson, 2007).

Knowledge creation e-learning is characterized by providing learners with the ability to learn by creating their own knowledge and by targeting selected groups with high quality solutions and processes. In practice, this is achieved using online asynchronous problem-oriented learning through highly intense, multiple, person-to-person dialogs in closed virtual learning spaces (Pettersson 2002, 2008). Knowledge creation e-learning is also characterized by being very capital-intensive and by suppliers following a differentiation strategy leading to high profit margins (Selling and Stickney, 1989).

Since 1997, the approach has disproved several common myths about what can be achieved by e-learning. For example, participant evaluations have shown that even purely virtual knowledge creation e-learning is rated better on all accounts, not just when compared to traditional chalk-and-talk teaching but also when compared to blended knowledge creation e-learning. The academic level is higher, allowing participants to reach higher levels on the Bloom (1956) scale. Because of the intense dialog, participants state that they do not even miss the social interaction found in physical settings (Duus, 2000a, 2000b, 2001, 2002; Smith and Duus, 2001; Duus and Ehlers, 2002; Duus, 2003; Duus and Ehlers, 2004; Pettersson, 2008).

By contrast, knowledge transfer e-learning is more in line with mainstream notions of how e-learning should be practiced. Knowledge transfer e-learning, which is what most suppliers provide, accordingly draws most attention in the press and academic research.

Knowledge transfer e-learning is comprised of all the e-learning products, solutions and processes that focus on the simple transfer of given knowledge to learners. Suppliers typically follow a cost minimization strategy with a low profit margin on products and solutions (Selling and Stickney, 1989). In their marketing, knowledge transfer e-learning suppliers tend to stress how much time and money companies, learning institutions and individuals can save by buying and using this form of e-learning (Duus, 2002).

Following the Abellian definition of industry, two distinct e-learning industries can be identified: the knowledge creation e-learning industry and the knowledge transfer e-learning industry. This distinction, which reflects underlying differences in knowledge and competence between developers and suppliers of e-learning was first proposed by Michael Pettersson [2]. However, it reflects development work carried out by various researchers throughout the nineties. The terms “knowledge creation e-learning” and “knowledge transfer e-learning” are in full accordance with earlier uses of the terms “high-end e-learning” and “low-end e-learning” respectively by Duus (2000a, 2000b, 2001, 2002). Figure 1 is an attempt to provide an overview of the distinction and its characteristics.

Three further aspects of knowledge creation e-learning deserve particular mention. While most examples of knowledge transfer e-learning are found in either learning institutions, such as universities, or in companies buying or selling learning technology, it is peculiar that knowledge creation e-learning in most cases seems to involve trans-disciplinary cooperation between learning institutions and business firms similar to that found in mode 2 research settings as described by Gibbons, et al. (1994).

Another characteristic is the practice-based development associated with knowledge creation e-learning. While many academic suppliers of knowledge transfer e-learning pride themselves on solutions based on the latest theoretical advances in pedagogical research, knowledge creation e-learning suppliers instead pursue development by experimental and experiential means. The latter “action research” approach is completely logical given that e-learning development involves the development of methodologies and systems dealing with the actions and reactions of human beings (Baskerville & Wood-Harper, 1996a, 1996b; Itoh, 1996; Gummesson, 2000). Thus, it cannot be pursued without the development and utilization of tacit knowledge (Polanyi, 1966; Nonaka & Takeuchi, 1995) [3].

The third aspect is perhaps the most staggering. Knowledge transfer e-learning clearly embodies what may readily be labeled the mainstream approach, whereas knowledge creation e-learning is more advanced on a wide number of accounts. The observed differences thus imply that a divide exists between the mainstream approaches and certain leading edge suppliers.

The observed differences between knowledge transfer e-learning and knowledge creation e-learning allow us to underline a problematic characteristic of the treatment of the field of e-learning in the press and in many academic publications. The problem is that knowledge transfer e-learning has been given very extensive coverage at the expense of knowledge creation e-learning.

Within academia, this can be evidenced by referring to a number of studies in recent years, which presented themselves as definitive treatments of the whole field, but which focused exclusively on what can be labeled as knowledge transfer e-learning. Rightfully, to avoid any misunderstandings, it should be stressed that this critique is concerned with substance and not with terminology. In other words, it is not simply a matter of omitting specific words like knowledge creation and knowledge transfer but of avoiding the description of a certain class of approaches in works described as definitive.

A few examples are Johansen & Terkelsen’s (2001) research on corporate e-learning strategy development, Elkjær & Olsen’s (2001) comparative studies on the use of e-learning and Kinch & Leinenbach’s (2003) charting of the field of e-learning in Denmark, all of which ignore knowledge creation e-learning and are limited to knowledge transfer e-learning. The cross-case study of advanced e-learning solutions by Hansen & Borup (2001) has only one example of knowledge creation e-learning in a large sample and it is not identified as a distinct approach. The advanced and theoretically ambitious treatment by Dirckinck-Holmfeld & Fibiger (2002) makes a case for their concept of Computer Supported Collaborative Learning, which resembles knowledge creation e-learning in some respects. However, the general approach and their conclusions are limited to the knowledge transfer e-learning approach.

One probable reason for this seems to be rooted in the fact that a substantial number of investigations have been broad and comprehensive and have not involved extensive in-depth studies of leading edge suppliers. If the latter approach had been chosen, we would probably have seen a better treatment of knowledge creation e-learning. The main impression is that the three categorical biases and five methodological fallacies previously mentioned abound.

Marketing efforts by e-learning companies and the treatment of the field in the press have to a great extent reflected this situation. In the late nineties and the first few years of the new millennium, many companies producing and selling learning technology referred to themselves in pompous terms far removed from reality and several supposed e-learning experts “lectured” in the media with little or no real knowledge of the topic [4].

Why did many companies and supposed e-learning experts produce such exaggerated or one-sided statements? One possible explanation is the hype that seems to be an integral part of most growth phenomena in economics and which certainly played a part in the dot.com boom of the late nineties. The downturn in the first few years of this millennium has, however, only reduced the frequency of such fallacious statements.

Economic distress may be a more valid explanation for at least some of the one-sidedness and the exaggerations produced. Most knowledge-transfer e-learning companies have faced a situation in which a low profit margin has provoked a volume-based strategy accommodated by very aggressive and opportunistic marketing efforts (Selling & Stickney, 1989; Duus, 2002). It is quite understandable that most e-learning firms have fared badly when one considers the pressure created by a low profit margin in combination with a faulty understanding of market conditions [5].

Presenting the last part of the puzzle, another explanation may be simple ignorance combined with an opportunistic search for academic merit. Many “experts” were able to attract a great deal of attention and recognition without having much concrete practical experience with e-learning. This tendency seems to have been reinforced by an insufficient recognition of the fact that e-learning is a new kind of learning, for which traditional pedagogical competence and knowledge is of limited use only (Duus, 2002; Duus & Ehlers, 2002; Jacobsen, 2002; Duus & Ehlers, 2004; Lindberg & Pettersson, 2007). This was earlier referred to as the fallacy of transferable competence.

In general, it seems that ignorance created by the joint effect of investigative bias, methodological fallacies, academic and/or economic opportunism and lack of practical experience with the subject seem to have been at work within the field. This joint effect is a highly probable reason for the observed slow implementation of e-learning in many companies and learning institutions. However, a more detailed explanation can probably be created by attempting to understand the motives of various e-learning actors (i.e. suppliers and researchers) through the use of ideal-type methodology. This implies that the subjectively held ideas, attitudes, opinions and notions of the various actors are seen as mirroring observed actions in the field.

This points to the method of “understanding”, the objective being to analyze subjective motives for action by letting researchers put themselves in the position of the acting individual (Weber, 1949) [6]. The premise is that acting individuals (as human beings) ascribe a subjective meaning to their actions by an implicit or explicit reasoning regarding the cause of their actions. According to this view, human beings are seen as genuinely creative individuals interpreting their social reality and acting creatively within it. Empirical observations of human action can thus be systematized along ideas, notions and attitudes. In other words, human action is evaluated in the light of the goal-orientation of the individual (Kalberg, 1994).

This research method follows neither the purely materialist/positivist position of quantification and representative populations nor the subjectivist position involving focusing on individuals and single cases. In short, it is based on neither statistics nor cases. It is, in contrast to the above positions, a method focusing on (the) typical instance(s) or representation(s) based on subjectively meaningful ideas, which can be ascribed to them within a frame of methodological individualism (Kalberg, 1994; Rangstrup, 2000).

Larger sets of subjective meanings do, of course, exist and can accordingly be ordered in what Weber (1949) calls ideal types. Ideal types are pure types of the subjective motives of human beings and rationalizations of actions, which may or may not correspond to single empirical cases. Ideal types are neither attempts to construct an extensive description of reality nor attempts to introduce theories or law-like generalizations. Ideal types are solely attempts to create yardsticks by which to assess reality (Kalberg, 1994).

Use of the ideal-typical method must thus proceed with some qualifications. While the idea is to create a general classification on the basis of observations of factual empirical conditions, it is not implied that it is possible to reverse the analysis, claiming that some specific firms and individuals possess these characteristics in full. Ideal types provide a way to structure reality in all its complexity by accentuating certain typical aspects in their purest form even though these pure forms are not found in reality. While they are not thought of as real firms, individuals or instances, an approximation of real forms can nevertheless be found by combining features from the ideal types or by pointing to nearly perfect matches.

Ideal types are often used in strategic and economic literature. Their use is, however, so frequent that they are often not referred to as ideal types. Some examples are Porter’s (1980) generic strategies, Galtung’s (1981) classification of researchers and their methodological dependence on culture, Mintzberg’s (1983) classification of organizational forms, Mintzberg, Ahlstrand & Lampel’s (1998) classification of strategy theories, Sundbo’s (2001) classification of innovation theories and Hougaard & Bjerre’s (2002) classification of relational strategies.

Given the great differences that exist between various types of e-learning, it should be possible to make an ideal-typical classification that goes beyond the simple distinction between high-end knowledge creation e-learning and low-end knowledge transfer e-learning. A classification that takes into account the subjective human aspects of e-learning construction may be able to shed more light on why some developers and producers choose low-end solutions while others choose high-end solutions.

What can be underlined here is that the simple distinction mentioned above only specifies or rather describes which main forms of e-learning exist. The distinction does not answer the crucial question of why such forms come about. Questions of “origin” imply a need for an ideal-typical classification based on subjective development aspects.

A bird’s eye view of the field of e-learning enables us to represent an ideal type classification with two dimensions: the degree of business orientation vs. the degree of traditional academic orientation and the degree of learning orientation vs. the degree of teaching orientation.

Business orientation is seen here as the opposite of a traditional academic orientation. The traditional academic system (i.e. research and teaching in schools of higher learning) has its mirror opponent in the still faster development of recent years that takes part in the business sector, where the advent of e-learning, global competition, mass individualization, mass customization and the new status of private firms as mode 2 knowledge producers are exerting pressure on the existing system (Cova & Haliburton, 1993; Gibbons et al., 1994; Angell, 2000). This implies that a substantial part of all knowledge production today takes place in trans-disciplinary ventures outside of the traditional academic system and that many knowledge producers in the academic sector face a demand for action and adaptation, making it reasonable to ascertain that a process of “creative destruction” is going on (Schumpeter, 1983).

Business orientation should, however, not be interpreted as a quality possessed only by actors outside of the traditional academic system. Rather, it should be interpreted as a counterpart to the traditional academic system, where mono-disciplinary mode 1 knowledge, exclusively in the form of publications, is produced (Duus & Jørgensen, 2004). Thus, business orientation reflects merely the degree to which knowledge is produced according to the needs and wants of business.

Learning orientation is accordingly the natural counterpart to what can be called teaching orientation. It is thus possible to create a spectrum of pedagogical objectives ranging from teaching to learning by following the taxonomy of levels of understanding created by Bloom (1956) or by seeing learning as the counterpart of teaching. The not so implicit meaning is that the very fact that something is taught does not imply that it is learned. Also, a focus on learning draws attention to the learner and learning processes as something happening partly within the learner. According to this perspective, understanding and knowledge are inwardly created rather than externally given. In contrast, a focus on teaching draws attention to the teacher and what is taught. In this case, knowledge is presented as something given (Illeris, 2002) [7].

In a classification we may refer to ideal-typical views as “world views” held by people working with and talking about e-learning. Following the tradition of Kuhn (1962), a more fitting word could be paradigms as this word is often used by philosophers of science to describe world views in a scientific community. With this in mind, the following model (see Figure 2) applies:

Figure 2: The Four E-Learning Paradigms.

Figure 2 depicts four basic ideal-typical paradigms that find empirical expression in four different interest groups and four corresponding worldviews from which four different strategies for the development of e-learning can be derived.

The above paradigm descriptions do not follow the same overall pattern. An explicit comparison is shown in Figure 3.

An important key to understanding the differences between the four paradigms is, of course, their point of departure, or the central focal point in the design process, as it is called in Figure 3 [12]. Each paradigm is based either on technology, content, pedagogy or market/business as governing the e-learning design process. At the same time, the central focal point is of immense importance for the choice of development model and for the understanding of individual choice in the development process. This is shown in Figure 4, which depicts the design practice of each paradigm.

As shown in Figure 4, the choice of central focal point is important in the design process. It is not impossible that the success of each paradigm in creating and managing e-learning development is attributable to this choice. An example is found in the market-based paradigm, which to a large degree distinguishes itself from other paradigms by being the only paradigm that separates content and the needs and wants of users/buyers. The very fact that in the market-based paradigm, development work is explicitly based on the needs and wants of users and buyers implies that success, measured as the ability to cater to the said needs, becomes more probable.

Empirically, a close connection between knowledge creation e-learning and the market-based paradigm, can be observed. In point of fact, wherever we observe knowledge-creation e-learning we also tend to find market-based development work. An explanation may follow from Pettersson (2002), one of whose central points is that efficient knowledge creation e-learning depends especially on user perceptions of the empirical and/or practical relevance of e-learning processes, which are enabled by a sharp focus on the empirical and practical reality of the academic/professional content. One important reason given is that participants will be very reluctant to partake in extensive virtual dialogs if they do not perceive that the practical problem being dealt with is relevant to their situation. This indicates that content should be designed with regard for the real world situation in which participants are to apply their knowledge. Thus, efficient knowledge creation e-learning would seem to imply that the real world situation of the participants must be taken into account by a market-based approach.

The immediate usefulness of the above four-paradigm model lies in its ability to give users, buyers, (university) managers, public servants, politicians and investors a map charting the political landscape within e-learning, thus enabling knowledge of interest groups and design models. This can help decision makers to make better and more informed choices on the strategic development of e-learning.

An important fact concerning the above depiction of the four paradigms is that no objective e-learning expertise or knowledge exists. Each of the four paradigms expresses a distinct political reality, implying that it is misleading when certain supposed e-learning experts pretend to pursue “objective research”.

However, the Randian view may be advanced that the market process constitutes an objective reality to which all individuals and organizations may sooner or later need to adapt (Angell, 2000). For this reason, a purpose may be served by evaluating e-learning research and development activities on the resultant practical effects in connection with the development and management of e-learning processes. A natural implication is that e-learning development will become closely associated with the mode 2 idea of knowledge production (Gibbons et al., 1994).

Further, it must be stressed that since the four paradigms are easily associated with plainly recognizable interest groups, the empirical correspondence of the above four-paradigm model can be estimated to be rather high (again, see Figures 1 and 3).

An important feature of the four-paradigm model is that it has a recursive organizational logic meaning that it works on several organizational levels. As such, the model does not just identify interest groups that are institutionally and commercially distinct. Thus observations suggest that the same organization can encompass several attitudes, notions and groups belonging to each of its paradigms. For example, Copenhagen Business School and the A. P. Møller-Maersk Group are examples of a university and a large corporation respectively, which house different notions and interest groups, each with its own position on e-learning development.

Apart from the descriptive possibilities in distinguishing between the four paradigms, the four-paradigm model suggests several normative areas of application. These areas all have one thing in common, namely, an increased opportunity to focus efforts by choosing one decisive paradigm in the development of e-learning. Thus, by distinguishing between several levels of aggregation, the following four different normative areas of application can be identified:

An important element connected to the strategic and political choice of paradigm is how well each paradigm pushes the frontier of development, i.e. which paradigm works best in developing the field of e-learning. This vital question can be answered in two ways, first, by looking at how each paradigm may follow as a natural choice from given stated objectives, and second, by considering the performance of each paradigm in an absolute sense, i.e. what has been known to work best so far.

If, for example, on the organizational level, aspirations and ambitions are low and decision makers just intend to “electrify” existing education, i.e. if an electronic correspondence school is the only ambition, then the content-based paradigm and a scientistic strategy will be the obvious choice. If, on the other hand, high-level pedagogy-based e-learning within the existing academic system is the objective, then the pedagogical paradigm and a pedagogistic strategy seem preferable.

If the ambition is to support business learning processes through the provision of inexpensive and efficient teaching, then the technological paradigm and a technologistic strategy are the relevant choice. However, if what is called for is a thorough change in the total system of knowledge production according to the needs and wants of business, then the market-based paradigm, and consequently, an agoristic strategy, is the relevant choice.

It is remarkable that results by and large have followed the levels of ambition, since the cutting edge within e-learning is pushed along by the best suppliers within the technological and the market-based paradigm. The most radical approach is without doubt the market-based paradigm and this also seems very promising when it comes to results. One strong argument in support of a market-based paradigm emerge from the simple fact that advances should be beneficial to users and buyers. If results are gauged accordingly, an approach built on the needs and wants of users and buyers would naturally emerge as promising. This calls for an agoristic development strategy.

The million dollar question appears to be what such an agoristic strategy should look like? This author has developed e-learning solutions for years within the market-based paradigm and is able to draw extensively on personal experience when suggesting the components of such a strategy. There are several aspects too detailed to outline in a comparatively short article like this (Pettersson 2002, 2008). However, empirical observations by this author suggest that the following seven tenets in Figure 5 may constitute the foundation of a general agoristic strategy that may lead to the development of advanced e-learning solutions within a market-based paradigm (Duus, 2002; Duus & Ehlers, 2002, 2004). The crux of the strategy is that all efforts (be they innovative/experimental or administrative/controlling) should be subjugated to externally given needs and conditions.

The mapping of the field of e-learning presented above may be criticized for polarizing the field into different camps of suppliers and for giving a much too biased perspective on the various interest groups within the field. However, it must be noted that this polarization already exists, as illustrated by the heterogeneity of the field. As a result, this article is nothing more than an attempt to map the field without resorting to the usual technological, pedagogical or superficial market analytic bias.

Mapping the field will result in ideal types, which to a greater or lesser degree will resemble the real world. If the real-world correspondence is found to be small, the Weberian proviso exists that ideal types are only a way to structure reality by emphasizing certain central aspects in a pure form, thus creating yardsticks against which to measure reality. If, on the other hand, real-world correspondence is high, hence resulting in paradigmatic distinctions that easily find their correspondence in existing interest groups (as in this case), then a high probability exists that this model is correct.

Interestingly, the normative implications exist independently of whether the model is fully correct. The point here is that the four strategic implications of the harmonization of organizational and national e-learning strategies, the creation of strategic alliances and the creation of a common language are independent of the correspondence of the ideal types to real-world interest groups.

Further research in this direction is advisable. For one thing, this article has shown that the field of e-learning can be systematically mapped by using insights from economics and sociology. In this way, this article distinguishes itself from most other literature on e-learning by its approach as well as in its conclusions. While most mainstream research within the field of e-learning has been founded on insights from pedagogy, communication, organization and an incorrect application of market analysis, this article has, in contrast, outlined a potential different approach.

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