A short post today: this month's LCBBQ is "What did you learn about learning in 2008?"

By a coincidence, I covered this query in my November post "A Year in E-Learning: One Blog’s Progress"

It’s definitely worthwhile heading over the the Learning Circuits Blog to check out what the other contributors have to say. There’s usually a good mix of conventional opinions, outlandlish views, and even the occasional inspired comment.

--

Chris Argyris, Professor Emeritus at Harvard Business School, has made significant contributions to the development of organizational learning theory and experiential learning.

Any company that aspires to succeed in the tougher business environment ...must first resolve a basic dilemma: success in the marketplace increasingly depends on learning, yet most people don’t know how to learn. What’s more, those members of the organization that many assume to be the best at learning are, in fact, not very good at it.

(Argyris, C. 1991)

Over the next couple of weeks (taking digressions where appropriate) I will examine the significance of his work (focusing in particular on single-loop and double-loop learning) on organizational learning systems.

Today however, I will begin by reminding you of the basis for Chris Argyris’ work: Constructivism.

In her comprehensive reference text Psychology of learning for instruction, Marcy Driscoll describes constructivism as having

…multiple roots in psychology and philosophy, among which are the cognitive and developmental perspectives of Piaget, the interactional and cultural emphases of Vygotsky and Bruner, the contextual nature of learning, the active learning of Dewey, the epistemological discussions of von Glasersfeld and the paradigm and scientific revolutions of Thomas Kuhn.

(1994, p.375)

Constructivism is an approach to learning based on the premise that cognition, or learning, is the result of mental construction: it is an active process in which learners construct new ideas, skills and behaviors based upon their prior and current knowledge, behavior and skill assets. The learner transforms information, constructs knowledge, and makes decisions based upon extant cognitive structures or mental models. These cognitive structures - what Roger Schank calls “scripts” in his Dynamic Memory Model (1982) - provide meaning and organization to experiences and allow the individual to go “beyond the information given” (Bruner, 1974). Even though there are numerous interpretations of constructivism, several central concepts inhabit all constructivist theories. Cunningham and Duffy (1996) identified two major similarities that are the foundation of all constructivist thought. They are that “learning is an active process of constructing rather than acquiring knowledge” and “instruction is a process of supporting that construction rather that communicating knowledge” (1996, p.172).

Bruner’s 1966 text Toward a Theory of Instruction described the key principles of constructivism (p.225):

Table 1 Principles of constructivism

Extending from these basic constructivist principles as well as from the work of other key figures in the constructivist school, Driscoll (1994) outlines five conditions for learning (p.382-3). Very much like the multiple approaches and interpretations that exist in constructivism, a number of conditions must be met for the approach to be implemented. It is useful to elaborate briefly on these conditions, as they are relevant to the learning approach discussed in the rest of this series of posts.

…and I will do this tomorrow.

____________________

References:

Argyris, C. (1991) Teaching Smart People How to Learn. Harvard Business Review Reflections 4(2). [Internet]. Available from: http://www.velinperformance.com/downloads/chris_argyris_learning.pdf [Accessed 12 November 2008]

Bruner, J. S. (1974) Going Beyond the Information Given. New York: Norton.

Cunningham, D. J. & Duffy, T. M. (1996) Constructivism: Implications for the design and delivery of instruction. IN: Jonassen. D. H. (Ed.), Handbook of Research for Educational Communications and Technology (pp. 170- 198). New York: Simon & Shuster Macmillan.

Driscoll, M. P. (1994). Psychology of learning for instruction. Boston, MA. Allyn & Bacon.

Schank, R. (1982) Dynamic Memory: A Theory of Reminding and Learning in Computers and People. Cambridge University Press.

--

A true learning person also has a “to-learn” list, and the items on that list carry at least as much weight in how one organizes his or her time as the to-do list.

More specifically, The Big Question is about:

• If you have a to-learn list and are willing to share, and willing to share how you work with that list, that would likely be helpful information.
• As Knowledge Workers, work and learning are the same, so how does a to-learn list really differ from a to-do list? How are they different than undirected learning through work, blogging, conferences, etc.?
• Are to-learn lists really important to have? Are they as important as what Jim Collins tells us?
• Should they be captured? If so how?
• How does a to-learn list impact something like a Learning Management System in a Workplace or Educational setting?
• What skills, practices, behaviors do modern knowledge workers need around to-learn lists?

So it's really a bunch of Big Questions this month. I'm not going to answer any of them, as I'm not so conceited as to think that you haven't better things to do with your time, than to think about what I do with my time. However, the topic did get me thinking...

First of all, some context - I undertook some research on the text that the idea of the To-Learn List originated from. Learning Journeys contains 37 two- to three-page essays by

some of the best and most well known of human resources and organizational leaders and pioneers. From Stephen Cover to Dave Ulrich, from Marshall Goldsmith to Robert Eichenger, these individuals have done much to shape current thought in the areas of organizational development and leadership.

Amazon.com reviewer

As such, the text is orientated towards the needs of HR and organizational development people, rather than learning & development professionals. No harm: it's always useful to get a different perspective (or to put it another way - a friend of mine reads a certain national newspaper because he "...likes to know what the enemy is thinking!"). One of the elements of the text that became apparent to me (from reading a part of the text using Amazon.com's Look Inside functionality) was that the learning perspectives discussed would probably work better for people who are not professionally involved with training others: in this capacity, it indicated some potentially useful approaches on how to engage others in continuous learning, and pointed towards some avenues that might assist in achieving this objective.

As discussed in a previous blog entry on the E-Learning Curve, one of the central components of the impact of learning (and specifically the development of knowledge workers’ expertise in organizations) is the context within which the learning takes place. A central element of this context is the type or format of the learning taking place. In the literature, it is apparent that a dichotomy exists between the paradigms of formal, goal-directed training programs, and informal “learning at the watercooler” (Grebow, 2002); what Michael Eraut (2000) describes as incidental learning that takes place almost as a side effect of work: “it is difficult to make a clear distinction between formal and informal learning as there is often a crossover between the two” (McGivney, 1999, p.1). Another complexity in the discussion is where is non-formal learning located in relation to the diametric opposites?

I support Alan Rogers’ (2004) view that a “new paradigm” for learning exists, in which “most programmes will be partly formal and partly informal” going from formal to informal and from informal to formal in both directions along a continuum (see Figure 1) . “Both forms of education are important elements in the total learning experience” (looking again at non-formal and informal education - towards a new paradigm, 2004).

Figure 1 the Learning Continuum

Similarly, Hodkinson and Hodkinson argue that focusing on the extent to which learning is planned and intentional may be a way of by-passing the distinction between formal, non-formal and informal altogether.” (Colley, Hodkinson & Malcolm, 2002).

So, to return to the topic, my To-Learn List has one entry: to learn.

I would categorize myself as a "learnivore" - I continually acquire new knowledge and information through my Web-, book-, podcast-, and presentation reading, blogging (reading and writing), academic study and research, and work-based learning-related tasks. These activities are drivers for the information I try to take on board in my attempts to enhance my skills, abilities, and expertise.

_____________

References:

Colley, Hodkinson, Malcolm (2002) non-formal learning: mapping the conceptual terrain. a consultation report [Internet] Available from: http://www.infed.org/archives/e-texts/colley_informal_learning.htm [Accessed 28th January 2008]
Coombs, P. (1968) The World Educational Crisis, New York, Oxford University Press.

Eraut, M. (2000) Non-formal learning, implicit learning and tacit knowledge, in F. Coffield (Ed) The Necessity of Informal Learning: Policy Press. Bristol

Goldsmith, M. Kaye, B. Shelton, K (eds.) (2000) LEARNING JOURNEYS Top Management Experts Share Hard-Earned Lessons on Becoming Great Mentors and Leaders. Davies-Black Publishing

Grebow, D. (2002) At the Water Cooler of Learning [Internet] Available from: http://agelesslearner.com/articles/watercooler_dgrebow_tc600.html [Accessed 30th January 2008]

McGivney, V. (1999) Informal learning in the community: a trigger for change and development NIACE. Leicester.

Rogers, A. (2004) Looking again at non-formal and informal education - towards a new paradigm [Internet] Available from: http://www.infed.org/biblio/non_formal_paradigm.htm [Accessed 30th January 2008]

--

Welcome to my blog, The E-Learning Curve.

So began my first post to the E-Learning Curve Blog on this day in 2007. Upon reflection, I don’t think that I really had any idea about what I was letting myself in for, in terms of the discipline and commitment, not to mention the sheer effort required to create and maintain a high-quality blog about Electronic Learning & Development.

I don’t think that I had any real knowledge about how the blog would unfold either; I guess that for me, that was part of what attracted me to the idea of keeping a blog in the first place: I wanted to see what would emerge over time.

In that sense I was lucky: in it’s first year the E-Learning Curve Blog transitioned from a world with a stable economic climate, to the 2007 subprime mortgage financial crisis, through the tipping point of the Credit Crunch, and now, the Great DepRecession* of Aught Eight.

This has given me the opportunity to discuss e-learning in society-at-large, and in the workplace in particular. What better opportunity is there for learning professionals to introduce the benefits of education than now? From my own experience over the last year, I have seen attitudes to e-learning change - for the better – as individuals and organizations I have worked with have finally begun to let go of the idea that e-learning today is not about “Webified” instructor-led courseware, or worse, dull and boring Authorware-style page-turners, but is an effective means to deliver knowledge and information across many channels, and takes a range of technologies under its aegis.

The emergence of the Read / Write Web into the broader consciousness has demonstrated that learning online can be as immersive an experience as a face-to-face training experience.

What better time, then, for individuals and organizations to look at educational strategy and learning technologies than in a period of profound change – these are the times that test the mettle of ideas and concepts and where they prove their value; if the reality lives up to the perception, if the potential can be realized.

What have I learned?

In a response to a recent Learning Circuits Blog Big Question, I once described myself as a 'learnivore' - a bit of a naff term, but accurate. Writing and maintaining a blog is one of the best motivators I know to continue developing my professional knowledge - to discuss the kind of topics I like to cover requires a comprehensive and in-depth of the subject of e-learning and all that understanding e-learning entails.

As a constructivist, I would assert that the practise of blogging is a excellent example of Bruner's Learning Spiral: the act of writing a blog post transforms information and enables the construction of knowledge, based upon my extant cognitive structures or mental models. These cognitive structures - what Roger Schank calls “scripts” in his Dynamic Memory Model (1982) - provide meaning and organisation to experiences and allow the individual to go “beyond the information given” (Bruner, 1974).

My view is that the e-learning blogosphere is inhabited by a population of knowledgeable, dedicated, and critical (in the positive sense) contributors, and if you want to be in that company, you have to know your stuff; of the blogs I read - see the nav panel to the right - the bar is set pretty high.

Top Ten

On a more practical note, here’s a list of the top ten topics according to the readers of The E-learning Curve Blog, courtesy of the fantastic blog analysis tools available on Statcounter – not just cool because they’re Irish.

1. Definition of E-learning
2. Economic downturn and the challenge to e-learning
3. The principles of constructivism
4. Non-formal learning in the workplace
5. Evaluating Non-formal Learning
6. Open Source E-Learning
7. E-learning & Knowledge Management
8. Using Kirkpatrick's Four-level model
9. Applying the e-learning curve in the corporate environment
10. E-Learning and the Economic Downturn: A Salutary Lesson

--

* DepRecession: A portmanteau word to describe the current Recession and / or Depression. Also has the benefit of being an homonym for “Deep Recession”

FOGRA: Googling “elearning blog” about a week ago, this happened:

Certainly an unexpected (but rewarding) first anniversary present!

Thanks to all who’ve read, contributed to, and debated the topics covered over the last twelve months, and I hope you'll continue to engage with me in the times to come.

_________________

References:

Bruner, J. S. (1974) Going Beyond the Information Given. New York: Norton.

Schank, R. (1982) Dynamic Memory: A Theory of Reminding and Learning in Computers and People. Cambridge University Press.

--

Previously, I looked at rates of adoption for

• Innovators
• Early Adopters
• The Early Majority

In this last post in this series, I will describe the final categories of adopters of diffused ideas.

The Majority

As a group, the Majority can be characterized as having less education and are older than the Early Majority. While they participate less in formal and non-formal groups with their peers, they probably form the largest cohort of the membership of such groups. They belong to fewer organizations than the early adopters. They access fewer blog, wikis, and other means of discovering information about new ideas and technologies. They do not participate in as many activities outside the organization than people who adopt earlier.

Nonadopters

The final category include the nonadopters. This group has the least education and is the oldest. They participate the least in formal groups and other initiatives.

Conclusion

In my view, one of the phenomena that emerged form researching this topic was the power of informational social influence, or social proof:

[It] is a psychological phenomenon that occurs in ambiguous social situations when people are unable to determine the appropriate mode of behavior. Making the assumption that surrounding people possess more knowledge about the situation, they will deem the behavior of others as appropriate or better informed.

(Wikipedia)

We can say, based upon the evidence of Bohlen’s and Beal’s research, that people often do and believe things because many other people do and believe the same things.

In this context, innovators – pioneers - are initially ignored by the majority during their initial evangelizing of a new idea or technology, almost as if their preference for such an idea is idiosyncratic because of an innovator’s role. only after early adopters (who are perceived by the community-at-large to be the “smart money”) take on a new idea, will true diffusion begin to take place. This is case of “the pioneers get the arrows, the settlers get the land.”

_______________
References:

Bohlen, J. M., Beal, G. M. (1957) The Diffusion Process, Special Report No. 18 (Agriculture Extension Service, Iowa State College) 1: 56-77. [Internet] Available from: http://www.soc.iastate.edu/extension/presentations/publications/comm/Diffusion%20Process.pdf [Accessed 3rd November 2008]

Wikipedia contributors, "Social Proof," Wikipedia, The Free Encyclopedia [Internet] Available from: http://en.wikipedia.org/wiki/Social_proof (accessed November 10, 2008).

--

Today's post concludes my short review of Kineo's 80/20 approach to rapid learning content prioritization and development.
Previously, I considered how the 80/20 Rule could be applied to e-learning, and suggested that Juran's Axiom of "the vital few and the trivial many" meant that we could say 80 percent of learning results originate from 20 percent of inputs for any activity or process. For example, 80 percent of an organization sales come from 20 percent of customers, or 80 percent of performance in an organisation is attributable to 20 percent of workers.

In the learning domain, this rule can be applied to the process of training prioritization. In organizations the purpose of learning and development is to improve worker performance. There are many ways and opportunities for employees to improve their performance:

• reducing procedural mistakes
• identifying new customers
• influencing the behavior of others
• reducing error in products

Effective training should focus on providing what’s necessary to enable people to improve performance. However, the 80/20 rule suggests that not all performance improvement opportunities merit the same focus. Rather it suggests that 20% of opportunities, if addressed 80% of the total potential value of a training solution (assuming the ‘perfect’ solution will address 100% of opportunities completely. Focusing training efforts on that top 20% is a far more efficient model than attempting to cover the remaining 80%. For rapid e-learning with a relatively short duration, having this focus is critical.

In this context, Kineo recommend a value-driven model for identifying and prioritising opportunities for rapid e-learning to influence performance that will contribute the most to organizational performance.

According to Stephen Walsh from Kineo, this process has a number of key activities:

• Ensure that you have identified prioritized needs that rapid e-learning is best placed to address
• Use the 80/20 rule to guide your analysis of the prioritization of training
• Use the three-step approach (see Figure 1) to conduct rapid training needs analysis

1. Identify the full range of performance improvement opportunities
2. Establish criteria and rank accordingly with experts – concentrating your efforts on top 20%
3. Translate to objectives and seek approval

• Use rapid tools (check-lists) and rapid methods (phone, workshops, virtual classroom, surveys) to gather your data.

Figure 1. Value-driven model for rapid training needs prioritisation (courtesy Kineo)

For a more detailed look at this approach, go to Kineo's website, or download the Rapid Guide on How to Rapidly Identify Training Needs.

--

You'll know if you're a regular reader of The E-Learning Curve Blog that I have discussed the usage of the Pareto Principle (also known as the 80/20 Rule) in previous blog posts. Elsewhere in the e-learning blogosphere, Tony Karrer at the eLearning Technology blog has also discussed what he calls the "Corporate Learning Long Tail" in some depth.

Over the weekend, I encountered a very useful paper describing a practical application of the 80/20 rule (though not, as we'll see, the Pareto Principle).

Now read on...

My experience of the e-learning industry is that the best and most effective practitioners are always looking for even more efficient content development methodologies, media production technologies, and approaches to content distribution to enable them to design, develop and deliver content to learners. In this regard, British e-learning development house Kineo always seem to have something interesting to say about the potential uses - and value - of Rapid E-learning, and one particular piece published in this month's Newsletter struck me as being particularly useful. In the article How to Rapidly Identify Training Needs Stephen Walsh discusses a strategy to pinpoint and prioritize training needs - "rapidly of course."

The value of any learning intervention is the change it achieves. If you know where the business challenge is, and you can pinpoint how learning can change behaviour, correct costly errors, and improve performance at the right time, you're setting yourself up for laser-accurate learning.

In his seminal article Rapid E-learning: Disintermediate or die! Ted Cocheu asserts that:

Learning is rapidly changing from today’s hierarchically-driven, curriculum-based training process where instructional designers and trainers intervene to transform subject matter knowledge into courseware, into a “flattened” world where experts transfer their knowledge more directly to those who need it. In this brave new flattened learning world, training professionals will focus more time on capturing and transferring expert knowledge than developing formal courses.

To support these changes in the design, development, and delivery of content, a number of factors need to be considered:

• Speed is king.
• Knowledge is exploding.
• Budgets are shrinking
• Classrooms are not scalable.
• Workplace learning is informal.
• People forget.
• Key knowledge is proprietary.

Rapid E-learning "changes the development model, leverages new tools, and dramatically changes the economics of content development" (p.2). By focusing on specific learning needs, e-learning developers can generate a much higher return on investment in training when compared to content designed using a more traditional ISD-based approach.

The methodology suggested by Kineo is designed to assist learning professionals identify and prioritize learning needs that are appropriate for rapid e-learning in organizations using a "value-based analysis."

This will get you to the outcome that a more detailed training needs would, but in a fraction of the time, by focusing specifically on the greatest points of pain and potential to add value. Identifying those key points means taking an 80/20 approach to needs analysis.

The Kineo interpretation of the Pareto Principle is based upon Dr. Joseph M. Juran's pioneering work in Quality Management in the 1930s and '40s. He "reduced to writing" his generally applicable observation (which I suggest that we should really call Juran's Axiom) of the relative importance of the "vital few and trivial many." Juran observed that in any activity or set of tasks, a few (20 percent) of the functions are vital, and many (80 percent) are trivial. However, as he stated in his 1975 article The Non-Pareto Principle; Mea Culpa he "...mistakenly applied the wrong name to the principle." In Pareto's case it meant one-fifth of the people owned four-fifth's of the wealth. In Juran's research for the US Government, he identified 20% of defects in a production process causing 80% of the quality issues. Project Managers know that 20 percent of the work (the first 10 percent and the last 10 percent) consume 80 percent of time and resources. Extending from this, Juran asserted that the 80/20 Rule could be generalized, from the science of management to the physical world, and indeed to learning and development processes.

In this context, 20 percent of learning interventions, if properly identified, should address 80 percent of the learning needs of an organization, and 80 percent total potential value of a training solution (assuming the ‘perfect’ solution will address 100% of learning.

Focusing training efforts on that top 20% is a far more efficient model than attempting to cover the remaining 80%. For rapid e-learning with a relatively short duration, having this focus is critical.

(How to Rapidly Identify Training Needs p.2)

As such, implementing a value-driven model based on the 80/20 Rule for identifying and prioritizing learning interventions can be a highly effective means to enhance worker performance in an organization.

More..

References:

Cocheau, T. (2005) Rapid eLearning: Disintermediate or Die! [Internet] Available from: http://ww.elearningforum.com/downloads/rapid_elearning.doc [Accessed 15th May 2006]

Juran, J.M. (1975) The Non-Pareto Principle; Mea Culpa [Internet] Available from: http://www.projectsmart.co.uk/docs/the-non-pareto-principle.pdf [Accessed 30 August 2008]

Walsh, S. (2008) How to Rapidly Identify Training Needs [Internet] Available from: http://www.kineo.com/documents/Kineo_Rapid_Guide_Identify_Needs.pdf [Accessed 30 August 2008]

--

In this, the penultimate post in this series, I will describe some more categories of early adopters, before concluding the series tomorrow.

As discussed in yesterday’s post, there are there are five categories of adopters of diffused ideas:

1. Innovators
2. Early Adopters
3. Early Majority
4. Majority
5. Nonadopters

I covered the first category, Innovators previously.

Early Adopters

The second category of adopters are Early Adopters. Typically, they are younger than the majority of adopters (but are not necessarily younger than Innovators). They are also better-educated that people or organizations that adopt at a slower rate, or do not adopt at all. They tend to participate more in the community of users through organizations like the ASTD and the E-Learning Guild, as well as using blogs, wikis and forums.

According to Bohlen and Beal (1957)

there is considerable evidence that this group furnishes a disproportionate amount of the formal leadership in organizations.

(p.5)

Early Majority

The third category of adopters is called the Early Majority. Table 1 (below)demonstrates that the rate of diffusion increases rapidly after this group begins to adopt.

Table 1 Rate of diffusion

[Click on image to enlarge]

The early majority are slightly above average in age, education and professional experience. They tend to participate in the community of users through organizations like the ASTD and the E-Learning Guild, as well as by reading blogs, wikis and forums occasionally. They have medium-high social and economic status. While less active in peer-related activities than early adopters, they participate more than the majority of adopters.

In many cases, they are not formal leaders in organizations, but they are active in and influencing formal leaders to promote new ideas and technologies in organizations. It can be said then, that the early majority are likely to be informal leaders – in a sense they are a “weather vane” that indicates to the majority “which way the wind is blowing.”

People in this category are typically more conservative than Innovators or Early Adopters: “they must be sure an idea will work before they adopt it” (p.6). Because this category of people have fewer resources than the previous two, they “cannot afford to make poor decisions.” The people tend to associate with their own group within organizations. They value highly the opinions of their peers, as this is the primary source of their status and prestige.

More…

_______________
References:

Bohlen, J. M., Beal, G. M. (1957) The Diffusion Process, Special Report No. 18 (Agriculture Extension Service, Iowa State College) 1: 56-77. [Internet] Available from: http://www.soc.iastate.edu/extension/presentations/publications/comm/Diffusion%20Process.pdf [Accessed 3rd November 2008]

--

As you’ll know if you’re a regular reader of The E-learning Curve Blog, I haven’t been corresponding with my usual regularity; this isn’t a case of blog fade, but rather is because of unusually heavy work commitments.

It’s uncomfortable for me not to be able to correspond, as I’m serious about my commitment to the activity, and in my view it’s a great discipline to set yourself a target of writing 500-1000 words a day of publishable material. Much as in my daily attempts to run or go to the gym, I believe that if you can find a good reason not to undertake this task, sooner or later you’ll find a bad excuse, and then the whole thing falls apart.

Even though I have not had the time to blog, I have been keeping an eye on my blog stats, and I’m pleased (even gratified) to find that the number of hits on my blog has not reduced by any significant margin.

Interesting.

What can this suggest? Intuitively, I would consider that if a blog isn’t updated frequently, then access and usage would drop off over time, but this doesn’t seem to have been the case.

Based on my blogs metrics, the number of hits via RSS – the daily feed – have gone down: obviously if I’m not posting regularly, the RSS doesn’t update, and subscribers have no new content to access. The other useful metric – number of hits through searches – has increased to the degree that it’s actually compensating for the fall-off in RSS-based or return viewers.

This suggests to me that an appreciable number of people are using my blog as an information-, knowledge- and learning resource, which, as far as I’m concerned, is the core value of my blog, and it’s certainly the reason that I subscribe to the blogs I read on a regular basis. I tend to write in what I call part-works and occasional series. For example, I will take a topic, such as open-source software for learning, and undertake a multi-part exploration of the topic over a period of time (usually about two weeks or so). This, I feel, enables me to cover a subject in some depth, but without overloading the reader with too much information in any given blog post.

In my occasional series posts, I will return to a particular theme over time. I find that this approach is especially useful when discussing new or fast-changing stories like elearning and the current recession.

It seems that what has emerged over the last year or so is that I have created an archive of material that addresses the needs and concerns of a significant number of other learning and development professionals. Hopefully I have also managed to challenge some preconceptions about the e-learning industry, and inspire others to enter into a dialogue with me about the nature of our profession, with the ultimate aim of enhancing the role of elearning as an means to educate.

--

People (and organizations) do not adopt new ideas at the same time. Some adopt ideas when they are first introduced; others wait for varying periods of time; some never adopt an idea. In The Diffusion Process, Bohlen and Beal maintain that "...the time span over which people adopt ideas will vary from practice to practice" (p.4).

The diffusion curve (see Table 1) illustrates the typical slow initial rate of adoption, the a substantial acceleration of update, followed by leveling off of the adoption rate. Bohlen and Beal's research shows "significant differences" (p.4) in the individual and social characteristics of people in alignment with the time they adopt an innovation.

Table 1 Rate of Adoption over Time (after Bohlen and Beal, 1957)

[Click on the image to enlarge]

As we can see form the table, there are five categories:

1. Innovators
2. Early Adopters
3. Early Majority
4. Majority
5. Nonadopters

Innovators

The very first to adopt a new idea are innovators. Innovators probably have a high net worth and a large amount of risk capital. "They can afford to take some risks" (Bohlen and Beal, p.5). Innovators have prestige and respect within their society or culture (and at the macro level, within their organization). Their sphere of influence often goes beyond social or organizational boundaries.

Innovators typically belong to formal organizations such as user groups and professional associations (such as the ASTD and the E-learning Guild) - such informal and formal associations provides them with access to more potential sources of information. Innovators also get their information from higher level research; they go directly to subject matter experts and researchers. Innovators also tend to subscribe to and regularly read specialized blogs, forums and wikis about current and potential future innovations.

Interestingly, Bohlen and Beal discovered that while their peers may watch the innovators and know what they are doing, they are not often named as colleagues or influencers that they (the peers) rely on for information.

More...

______________

References:

Bohlen, J. M., Beal, G. M. (1957) The Diffusion Process, Special Report No. 18 (Agriculture Extension Service, Iowa State College) 1: 56-77. [Internet] Available from: http://www.soc.iastate.edu/extension/presentations/publications/comm/Diffusion%20Process.pdf [Accessed 3rd November 2008]

--