Taxonomy Of eLearning: Does eLearning Need A New Taxonomy?

Taxonomy Of eLearning: Does eLearning Need A New Taxonomy?
Summary: How do we measure success? The accomplishment of one’s goals, right? So, how do we measure success in eLearning? That would depend on who is asked; teacher, student, school manager, or vendor? It is easy to see how this question, then, could cause confusion. Do we then need a new taxonomy of eLearning?

Do We Need A New Taxonomy Of eLearning?

When we think about eLearning and taxonomy we often think of Benjamin Bloom’s well-known taxonomy of educational objectives (created in 1956), which is easily understood and is probably the most widely applied today, serving as the backbone of many teaching philosophies. Bloom's taxonomy is most often used when designing educational, training, and learning processes; particularly when wanting to promote higher forms of thinking in education, such as analyzing and evaluating concepts, processes, procedures, and principles, rather than just remembering facts (rote learning, etc.). Bloom identified 3 ‘domains’ of educational activities or learning:

  1. Cognitive.
    Mental skills (knowledge).
  2. Affective.
    Growth in feelings or emotional areas (attitude or self).
  3. Psychomotor. 
    Manual or physical skills (skills).

When considering educational objectives, we perhaps need to consider ‘whose’ educational objectives? Where Bloom spoke of analyzing and evaluating concepts, processes, procedures, and principles, he clearly had the learner in mind as he classified educational goals. I ask if eLearning would not be better served by its own taxonomy (framework) where the separate objectives of the various parties involved in eLearning are distinctly and separately categorized. This is important because there are many aspects to eLearning. And none of them can promise a successful learning outcome. Successful learning outcomes (the result, or not, of educational objectives) require a multi-faceted approach to delivery. Also, these educational objectives need to be untangled so that we know from whose perspective we are looking, this will help us determine success, ... or not.

Untangling eLearning

Let us first consider the complexity of the simple question, ‘what is eLearning?’. For one person its learning delivered by electronic means, for another it's utilizing electronic technologies to access educational curriculum outside of a traditional classroom, for another it’s an avenue for corporate growth, it’s a product to be sold, it’s an investment opportunity, it’s a revenue-making exercise, it’s an institutional outlay, it’s a tool I use every day. You can see the wide disparity of interests (between students, academics, educational staff, policymakers, vendors, and other contributors) and their subsequent interpretations that are evoked by a simple question. We don’t have a universal understanding of the term. The difficulty with this is even though eLearning has been proven to be a successful method of training and education, and is becoming a way of life for many, we simply do not have a common understanding of it. When different interests are involved this can result in issues that become lost in translation.

In looking at the research we do not find evidence of whether, and to what extent, eLearning technologies achieve the learning goals for which they were designed. Research to date has failed to investigate, or find out, what learning goals eLearning technologies had when implemented, and, whether they achieved them? Therefore, I argue that we need to know more.

In 2016 I wrote an academic paper called ‘In my end is my beginning: eLearning at the Crossroads’ published with The Turkish Online Journal of Educational Technology (TOJET) that described the lack of a universally accepted framework in the eLearning industry to be used when implementing digital technologies in education. What this paper suggested is that 3 distinct categories of eLearning exist, each with differing stakeholders, interests, and points of view. These are:

  1. Top Down.
    Official management instructions or commands.
  2. Commercial.
    Profit driven business.
  3. Bottom-up.
    Academic and teaching staff.

All 3 categories in this taxonomy are affected by educational pedagogy, cultural values of the society in which they are placed; plus, geographical, political, and technical influences. These categories of eLearning do not always pull in the same direction and neither are they always placing the ‘student’ in the center of importance. Nor do they necessarily equate to delivering effective forms of learning. As each category has its own distinct set of drivers and influences success can only be measured with the particular category in mind. We have, for example, witnessed profit-driven technology solutions that are not liked by students nor welcomed by their teachers. If measuring 'success' on the part of the business that made the sale, we could say they were very successful and have secured profits and employment for their staff. However, success in the way of learning outcomes may not have been achieved.

The question is, therefore, if there are these very differing ways of interpreting eLearning, do we then not need a new taxonomy that we can use to best identify interests and thus measure outcomes/success? The ‘taxonomy of eLearning’, for example. Understanding these different categories of eLearning (between industrial models, bottom-up innovation, and top-down institutionally-led changes) would help us more accurately define the point-of-view of an outcome in order to measure its level of success.

Taxonomy Of eLearning - Categories Explained

So what are the differences in the categories of the taxonomy of eLearning? Figure one below provides a diagrammatic view of the taxonomy. The 3 categories are each influenced by the different cultural, geographic, and political situations in which they exist. Advances in technology and our understanding in pedagogy also impact each category.

Firstly ‘Top-Down’

The first category, ‘top-down’ eLearning from an Administrator’s point of view and who make decisions based on bottom-line interests. Educational administrators (policy makers such as School Managers, Senior Administrative Officers, Governing Bodies, etc. who perform a wide array of tasks to ensure the proper functioning of an institution) are often trying to maximize income generation and increase their institutions profit margin whilst reducing costs. They are also pressured and influenced by governmental policy and the legal environment in which they operate. One way for them to reduce costs is to reduce the expenses associated with education delivery. One method of doing this is using digital formats that offer substantial cost savings through the unlimited scalability of resources.

This group is interested in the financial success of their organisations and make decisions on where to invest funds, expected return, and what strategies best achieve economic security for the future. Members of this group ultimately make decisions of financial payments for products and services from the ‘commercial’ category to be used by the ‘bottom-up’ category. Directives on improvement initiatives are made at this level influencing the tools to be made available which impacts teaching staff (and ultimately students). We can see here distinct influences that drive this group’s decision making. Note, none of these influences appear to be in the interest of the learner and eLearning.

Secondly ‘Commercial’

The second category, ‘commercial’ a profit-driven corporate view of the education market that looks at eLearning from a corporate profit nexus. This category of the taxonomy representing a plethora of vendors operating in the education market. The vendors of technology who develop software and try to gain as much market share as possible. The interest of the student is secondary, as shareholders push for profits, and contracts/sales are sought for security and growth.

This market, whilst relatively new, is today worth several billion dollars. In fact, a report by Global Market Insights valued the eLearning market at over USD 165 billion in 2015, and, it is likely to grow at over 5% from 2016 to 2023, exceeding USD 240 billion. Factors such as low-cost involvement accompanied by flexibility in learning are expected to drive industry growth. With such lucrative figures vendors position themselves as the best supplier of educational software and/or services in order to generate sales, securing their own futures. In fact, this has been described as a “vendor feeding frenzy” (Kay, 2003), as software vendors attempt to exploit the new and potentially lucrative market for knowledge management.

Said sales are made by members of the ‘top-down’ category, not the ultimate end-users of the software and/or services, those in the ‘bottom-up’ category and students. There are various pressures on members of the ‘commercial’ category, mostly economical. Start-up companies and established companies with larger staff payrolls desperately need to secure large contracts to placate shareholders and other investors. Market competition is dynamic as we see jostling for the self-interests of profits and cash flow. To influence the decision making of policy makers and senior educational management in the ‘top-down’ category (in order to win a sale), education suppliers promote extensive lists of capabilities. Though, often the end-users of their products, the students and teachers using them, are not consulted in the product development phase. Again, none of these influences appear to be in the interest of the learner and eLearning.

Thirdly ‘Bottom-Up’

The third category, ‘bottom-up’ eLearning viewed from the point-of-view of educators working at the ‘coal-face’ of education in corporations, colleges, and universities. These people, on average, have a deeper understanding of the pedagogics (teaching methods) of learning, and, are interested in student outcomes. They interact daily with students, they know what works, and what doesn’t, they hear student concerns, witness their success/failures, develop courses, and are best placed to inform what works, and where we could do better. Unfortunately, all too often, this group does not have a voice, neither in the software development stage nor the software purchase decision phase. We can see what influences them are issues that are, however, strongly aligned with teaching, and, the interest of eLearning.

These teachers and staff work with educational software and services provided to them through the buying decisions of the ‘top-down’ group members, ultimately influenced by ‘commercial’ category members. Often, they have little voice in buying decisions.

Taxonomy of eLearning

Figure 1: A taxonomy of eLearning

Why The New Taxonomy?

In a field which changes with astonishing speed as ever new technologies or start-ups flood the market what is lacking is an accurate measure of the cost and sophistication of educational technology intervention with its impact on pupil learning outcomes. We need to better analyse eLearning implementation and whether implementation efforts to date have typically been for the benefit of the student, or for commercial gain. This is of particular interest for students, teachers, school administrators, and communities, as it provides perspectives on the implementation and management of learning with technology giving a better understanding on technology for learning and teaching activities that are in the students’ interest, not commercial ones.

With profits driving the development of eLearning products (courseware and delivery tools) the students’ actual needs/requirements/benefits are often overlooked, or completely ignored, in the drive to increase profitability. Also, students’ acceptance of eLearning as an educational medium does not appear to be of importance to school administrators. Often the students’ perspective on how they use and consider eLearning technology is ignored. This suggests a gap between what administrators of eLearning programs believe and what students experience in practice.

I argue that eLearning should be centered on the learning not the platform on which it is delivered. Too often we witness the mistakes of focusing on the technology first and then the pedagogy. We know from research that the pedagogy of eLearning as student-centered technology can benefit students’ learning, however, this is often not a driver for stakeholders with prominent commercial interests. Given the various perspectives held by different interests I suggest a need for an eLearning taxonomy to establish distinct categories of eLearning between industrial models, bottom-up innovation and top-down institutionally-led changes.

When reviewing eLearning implementation, it is important to distinguish between skill and luck. Therefore, we need to be able to accurately measure the outcomes according to the different interests involved. To be inclusive and to be able to understanding and assess the viewpoints of all stakeholders this taxonomy gives us a more comprehensive picture. For more on introducing eLearning and avoiding traps that block successful implementation, please read an earlier article, eLearning Introduction - Best Practice.

In the end, we all have the ability to achieve success in eLearning. But, we need to be able to determine the viewpoint first from which to measure the level of that success. If we don’t do that we could be comparing apples with pears.

For a complete report of the study, see Blackburn, G. (2016). In my end is my beginning: eLearning at the Crossroads, The Turkish Online Journal of Educational Technology, July, 15(3). DOI: 10.13140/RG.2.1.5111.4483



  • Bloom, B., Englehart, M. Furst, E., Hill, W., & Krathwohl, D. (1956). Taxonomy of educational objectives: The classification of educational goals, 1st ed., Cognitive domain, New York, Toronto: Longmans, Green.
  • Global Market Insights, (2015). eLearning Market Size, Industry Analysis Report, Regional Outlook (U.S., Germany, UK, Italy, Russia, China, India, Japan, South Korea, Brazil, Mexico, Saudi Arabia, UAE, South Africa), Application Development, Price Trend, Competitive Market Share & Forecast, 2016 -2023, Global Market Insights Inc., Ocean View Delaware, United States.
  • Kay, A. S. (2003). The curious success of knowledge management, in Handbook on Knowledge Management, Eds. Clyde Holsapple, C. (2003). 2: 679-687, Berlin: Springer.