M-Learning via the iPhone 3 – some approaches and technologies

After yesterday’s excursion into sci-fi to show that the concept, if not the reality of mobile learning (m-learning) has been around for a good part of the last century, today’s post returns to the altogether more prosaic task of identifying the characteristics of m-learning. I think that the best way to approach this is to characterize m-learning’s parent domain, e-learning.

So, let me remind you of my favorite definition of the characteristics of e-learning and consider if they also apply to m-learning. In his influential 2001 text E-Learning: Strategies for Delivering Knowledge in the Digital Age, Marc J Rosenberg argues that e-learning is based on three fundamental criteria (pp.8-29):

1. E-learning is networked making it capable of updating, storage and retrieval, distribution and sharing of instruction or information. So important is this criteria that Rosenberg describes it as fast becoming an “absolute requirement” [his italics] of e-learning.
2. It is delivered to the end-user via a computer using standard internet technology so that even though the definition of what a standard technology is may evolve as the internet matures, e-learning will be deliverable on that channel
3. It focuses on the broadest view of learning: learning that goes beyond “e-training” (Beyond E-Learning, 2006, p.11). E-learning is at the core of the “smart enterprise – a high-performing organization that allows knowledge and capabilities, enabled by technology, to grow and flow freely across departmental geographical or hierarchical boundaries, where it is shared and made actionable for the use and benefit of all” (2006, p.39).

A discussion on m-learning then, must in part be dedicated to the technologies underpinning the broader e-learning domain. In this context, ‘mobile’ generally means portable and personal, like a mobile phone or media player. While ‘mobile device’ typically means PDAs and digital mobile phones, it might more generally be taken to mean any device that is

small, autonomous and unobtrusive enough to accompany people in every moment in their every-day life, and that can be used for some form of learning, for example an MP3 player.

(Kineo and UFI/Learndirect Mobile Learning Reviewed. p.5)

Many examples of learning with mobile technologies fit in to this description, and broadly speaking they all align to the “absolute requirement” to receive and transmit digital voice and data communication over a network – though not necessarily wirelessly, as we shall see).

According to a number of sources including Gartner (M-Learning Opportunities and Applications) and Kineo & UFI/Learndirect (Mobile Learning Reviewed) mobile handsets are, and will be the “dominant m-learning devices for some time: there were more than 1.2 billion shipped in 2008” (Gartner, p.6). There are five basic categories of devices:

1. ‘Smartphones’ or Converged Media Devices (CMDs) have an identifiable operating system, are Web-capable and support installable applications, such as PDF and content readers. They are able to render a wide range of digital data types so they can act as sophisticated m-learning platforms.
2. Enhanced phones don't have an open operating system but have some audio, video and Web capability, and typically support simpler installable applications using programming tools such as Java Platform, Micro Edition (Java ME).
3. Basic phones are low-cost devices that can support voice and text messaging
4. Non-telephony mobile devices are audio/MP3 players and video-enabled media players, the dominant product in both markets belonging to the Apple iPod family of players.
5. Hand-held games consoles are lightweight, portable devices include in-built screens, games controls and speakers. The dominant manufacturers include Nintendo (DS) Sony (PSP) and Nokia (N-Gage).
   
   

In 2008, CMDs were a growing minority, comprising approximately 15% of all devices shipped globally; enhanced phones made up a little more than 60%, and the remainder were basic phones. Of the potential mobile learning devices, mobile phones are clearly the most commonplace. According to a recent report by Strategy Analytics (cited in Mobile Learning Reviewed, p.4), there are 1.5 billion mobile phones on earth, with 10% year-over-year adoption expected through 2008. In 2005 the Financial Times reported that UK mobile phone penetration was about 86% of the adult population. By 2006, the penetration rate for Western Europe was reported as 100%, which means there was a mobile phone for every person in the population.

The media player market is one of the biggest IT success stories in recent years. The market leader is Apple’s iPod. Since 2001, Apple has sold over 100 million iPods worldwide. Many other players compete in the personal media player marketplace including Archos, Sony, iRiver, Creative, and Microsoft. While functionality varies according to manufacturer and brand, we can say that a media player is a portable mass storage device that allows content to be downloaded and used offline. Music storage is obviously their primary use, but their mobility and storage capacity makes them ideal mobile learning devices. A significant increase in the audio- and video podcast download market demonstrates that consumers have extended the potential of these devices beyond their intended capacity as über Walkmans.

Kineo (p.6) assert that:

The commercial market for MP3 downloads is highly developed, though monetizing non-music formats (e.g. podcasts and vodcasts) has proved more challenging. In effect the ‘book on tape’ market has jumped formats to become the commercial podcast market via iTunes and Audible.
The ease of providing podcasts and vodcasts for download has a potential cost advantage, as they can be downloaded for free (assuming the user is on a fixed price broadband line), unlike download or access to learning content via a mobile phone or CMD. Thus, mobile devices used for learning do not require continuous connection. Also, once on the iPod, learning content does not require internet connection for it to be accessed, so there need be no ongoing costs of access after initial download.

Given the almost ubiquitous nature of these devices, it’s not surprising that educators and organizations with an interest in distributing electronic learning content are now considering the potential for these devices to support a previously unavailable channel to communicate and transfer knowledge to learners.

More…

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References:

Jones, N. (2008) M-Learning Opportunities and Applications. ID Number: G00163293 Gartner Research [Internet] Available from: http://www.gartner.com (Subscription or purchase required) Accessed 17 February 2009

Kineo and UFI/Learndirect (2009) Mobile Learning Reviewed. [Internet] Available from: http://www.kineo.com/documents/Mobile_learning_reviewed_final.pdf Accessed 17th February 2009

Rosenberg, M. J. (2001) e-Learning: Strategies for Delivering Knowledge in the Digital Age London: McGraw-Hill.

Rosenberg, M. J. (2006) Beyond e-Learning. San Francisco, CA: John Wiley & Sons, Inc.

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M-Learning via the iPhone 2 – some approaches and technologies

In M-Learning via the iPhone 1, I started to investigate the characteristics of mobile learning by going back to basics, specifically looking at the technological and conceptual foundations of this domain: training, instruction, education and learning. Today, I’m going to begin in earnest by telling you a story about a book - a wholly remarkable book in fact, that was first conceived nearly forty years ago.

Are you sitting comfortably? Then I’ll begin. And Remember…

The Hitchhiker’s Guide to the Galaxy is the most successful book every written. A handy electronic reference book, its chief selling points are the words 'Don't Panic' written in large friendly letters on the cover, and that it’s cheaper than its closest competitor, the Encyclopedia Galactica. The Guide’s reporters travel the length and breadth of the Milky Way, drinking heavily, going to lots of parties and generally having a great time. Their experiences, which include everything from how to mix the greatest cocktail in the galaxy to life on Earth (“mostly harmless”) is then passed on via the SubEtha net to every copy of the Guide, giving people the opportunity to misinterpret the inaccurate copy. Much of the guide's content is plagiarized from the back of cereal packets, and some of it is just made up. Its most useful advice concerns towels.

Now I’m not going to labor the point about blogging (without the wild parties, sad to say), Wikipedia, and the SubEtha / world wide web “net” but here’s a description of the Guide itself:

…A device that looked rather like a largish electronic calculator. This had… a screen about four inches square on which any one of a million “pages” could be summoned at a moment’s notice. It looked insanely complicated, and this was one of the reasons why the snug plastic cover it fitted into had the words DON’T PANIC printed on it in large friendly letters. …The reason why it was published in the form of a micro sub meson electronic component is that if it were printed in normal book form, an interstellar hitchhiker would require several inconveniently large buildings to carry it around in.

The Hitchhikers Guide to the Galaxy (pp.26-27)

Sound familiar? Of course it does.

Man seeks Nokia charger for his retro cell phone

That was 30 years ago. Back in the future, we can say that the we live at a time where the socio-cultural, economic and technical foundations exist to change the way that we acquire learning and knowledge in as profound a way as the introduction of printing in Western Europe in the 15th Century. We can now potentially carry our knowledge with us without “several inconveniently large buildings” to carry it around in. The current generation of portable digital devices (including smart phones, PDAs, and media players) is that they can support a digitally-mediated, connected learning environment, providing a convenience of instant access to a range of people and resources, as well as the ability to process data in a way that wasn’t possible even five years ago.

Next time: The altogether more prosaic task of describing the characteristics of E-Learning as I understand them, and a context for M-Learning.

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References:

Adams, D. (1979) The Hitchhikers Guide to the Galaxy (pp.26-27) London: Pan Paperbacks

“Don’t Panic” image Courtesy British Broadcasting Corporation

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M-Learning via the iPhone 1 – some approaches and technologies

In my last blog post, I discussed how I had resigned myself to the fact that the Adobe Flash Player will never be deployed on the iPhone†.

However, that is not much use if you, as an e-learning professional, have an audience for knowledge- and content delivery via mobile devices including the iPhone. In this series of articles, I will discuss approaches to delivering training via PDAs like the iPhone based on applications and functionality already available on that device. Let’s see what happens after that.

Let’s set the context. There are a growing number of extensions to the well-established core term ‘E-Learning’ including this list of candidates (compiled in 2008 by CramerSweeney):

• C-Learning - learning via collaboration with co-workers and associates
• M-Learning - learning via a portable digital media device
• V-Learning - learning inside a virtual world (such as Second Life)
• G-Learning - learning via computer games

The latest term I have discovered is Ubiquitous Learning, or U-Learning, first discussed by Gary Woodill in his excellent Workplace Learning Today column, who encountered the term in the title of a Masters dissertation called The dawn of uLearning: near-future directions for 21st century educators). Can we now take this trend to its logical conclusion and define

• T-Learning - learning via reading educational books, academic and other Textual material
  
• S-Learning - learning via lecturers & teachers Speaking
• W-Learning - learning via the medium of pen, paper, and taking Written notes

[Image courtesy Flickr user tryingtimes]

‘X’ is one of the cooler letters – let’s have X-Learning. I’ll send a Mars Bar to the person who contributes the best definition of X-Learning.

Or should we stop. Now. Please.

In my view, each of these descriptors implies that the alphabetti-spaghetti of C- G- M- V-Learning activities are discrete verticals or silos, standing alone and untouched by their siblings.

Of course this is not the case: if anything, we can say that each of these terms describes a learning channel that relies on or emphasizes one modality of learning, but doesn’t - I would assert can’t – occlude other learning modalities.

So whither M-Learning among this cacophony of uppercase modifiers? Does what we commonly call ‘M-Learning’ deserve to be treated as a domain in it’s own right? Can we discover if there are any unique characteristics that differentiate learning via mobile technologies?

I think we need to take a step back. First of all, what is learning? I would assert that learning is

The acquisition of new knowledge, behaviors, skills, values, preferences or understanding, and may involve synthesizing different types of information. The progress of this acquisition over time tends to follow learning curves. Learning is a Constructivist activity.

Harold Stolovitch puts it succinctly in his 2002 text Telling Ain’t Training when he says that “learning is change, adaptation” (p.18). According to the author, we use training, instruction and education as strategies to enable people to learn.

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†Probably.

Apple has a habit of denying that they are developing a range of devices and technologies. Right up to the moment that Apple announce their newest gizmo / solution / partnership. Until 2009 this typically occurred at an Apple Expo event with Steve Jobs uttering the famous phrase “One more thing…” as the latest object of geeky desire walks up the aisle of the technological Chapel O’ Love.

Next time: What is E-Learning (Slight Return)

Coming up: What is M-Learning?

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References:

Publish Post

Nalder, J. (2008). The dawn of uLearning: near-future directions for 21st century educators. Unpublished Master’s thesis, Queensland University of Technology, Brisbane. [Internet] Available from: http://www.scribd.com/doc/12398804/The-dawn-of-uLearning-Jonathan-Nalder-Masters-thesis Accessed 18th February 2009

Stolovitch, H. (2002) Telling Ain't Training. ASTD Press.

Sweeney, J. (2008) Let's Talk Terminology CramerSweeney Training Blog [Internet] Available from: http://www.cramersweeney.com/cs_id/trainingblog/ Accessed 17th February 2009

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Can we re-invent e-learning?

Somebody once said:

Although e-learning began as a new way to deliver training, it cannot remain that way because it is no longer able to adequately support all the learning needs of individuals and organizations by itself - if it every was. E-learning has moved in a new, somewhat unanticipated direction that is not always reminiscent of an instructional framework. To be more influential, e-learning must be reinvented. While continuing to provide a viable instructional option in a formal learning setting, it must also move toward informational and collaborative solutions that focus more prominently on the specific jobs people do. It must move beyond courseware and classrooms and into work. To reinvent e-learning is, in many ways, to reinvent learning itself.

(Marc J. Rosenberg, Beyond E-learning)

In essence, this means transforming learning, so that learning activities and resources are situated around

1. the learner
2. their environment
3. their tasks

enabling learners to construct their own knowledge in the context of what resources they need to carry out their activities effectively.

David Jonassen says:

In constructivist learning environments, technologies are used to situate learning tasks in a variety of contexts. With video, very rich and engaging contexts can be created.

He asserts that in the traditional organizational approach that

[u]nfortunately, most e-learning replicates the worst features of face-to-face instruction. So, it may be cheaper to "deliver" knowledge over the Internet, but it will not be more effective.

In the context of organizational development and workplace learning, this is commonly known as the systems-based approach to instructional design & development (ISD). A system is a set of elements or components that must integrate to perform a specific function. Every job in an organization is used by the organizational ecosystem to produce a product or output. The product or output is the means by which a organization generates its assets and remains self-supporting. In theory, this leads to the creation of a virtuous circle of continuous growth and development.

In learning and development, this systems-based approach is epitomized by the ADDIE conceptual framework, most notably refined by Dick & Carey in The Systematic Design of Instruction (1996).

The ADDIE approach has been one of the core tenets of instructional design for the best part of two decades.

I think ADDIE is a myth.

And I'm not alone in reaching this conclusion. In his article In Search of the Elusive ADDIE Model (2003), Michael Molenda undertook a Livingstonian attempt to discover the source for the original reference to the ADDIE model. Molenda’s research uncovered no original reference for the ADDIE model. This lack of an original reference led Molenda to write,

I am satisfied at this point to conclude that the ADDIE Model is merely a colloquial term used to describe a systematic approach to instructional development, virtually synonymous with instructional systems development (ISD). The label seems not to have a single author, but rather to have evolved informally through oral tradition. There is no original, fully elaborated model, just an umbrella term that refers to a family of models that share a common underlying structure.

(p.1)

My view is that ADDIE emerged from the principles of project management, and resemble the philosophy and practice to this discipline's methodology more than a pedagogy. Treating learning like a project leads to "training outcomes" equivalent to project deliverables.

While these training deliverables may have value in and of themselves, they have limited value for learners in the longer term. We could even say that the training outputs are valid; some of the objectives of the learning intervention designed according to the precepts of ADDIE may be met but

Our field of educational communications is founded on the premise that communicating content to students will result in learning. In educational communications, information or intelligence (in many different forms) is encoded visually or verbally in the symbols systems employed by each technology. During the "instructional" process, learners perceive the messages encoded in the medium and sometimes "interact" with the technology. Interaction is normally operationalized in terms of student input to the technology, which triggers some form of answer judging and response from the technology in the form of some previously encoded (canned) message. Technologies as conveyors of information have been used for centuries to "teach" students by presenting prescribed information to them which they are obligated to "learn."

(Jonassen, 2001)

So, can we re-invent e-learning?

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References:
Dick, W. & Carey, L. (1996). The Systematic Design of Instruction (4th Ed.). New York: Harper Collins College Publishers.

Exclusive Interview with Professor David Jonassen (2001) IN: elearningpost [Internet] Available from: http://www.elearningpost.com/articles/archives/
exclusive_interview_with_professor_david_jonassen [Accessed 12th January 2007]

Molenda, M. (2003). In Search of the Elusive ADDIE Model. [Internet] Available from: http://www.indiana.edu/~molpage/
In%20Search%20of%20Elusive%20ADDIE.pdf Accessed 12 May 2008

Rosenberg, M.J. (2001) What Lies Beyond E-Learning? learningcircuits.org e-zine [Internet] Available from: http://www.learningcircuits.org/2006/March/rosenberg.htm Accessed 14th April 2007

Knowledge Worker Information Processing - an Overview

The goal behind this series of posts about knowledge working and knowledge workers is to understand something of the audience that most of the efforts of organizational learning and development professionals are targeted at; the knowledge workers (KWs) themselves. Today, I'm will wrap up the series by concluding my analysis of the William P. Sheridan's How to Think like a Knowledge Worker (2008).

I believe that knowledge working is intimately bound within the organizational context: knowledge workers use their skills and experience to innovate solutions to real-world problems. One of the primary conditions of knowledge working is the social aspect – knowledge workers typically collaborate with their peers, whether they are individuals with similar skill assets, such as application development teams working in an agile software development environment, or in project teams which require knowledge workers from different disciplines (technical architects, business analysts, and product consultants, for example) to cooperate in the implementation of the solutions on a customer site.

Figure 1. Human Knowledge Mindmap (after Sheridan)

In this context, Sheridan uses the Human Knowledge MindMap (see Figure 1. to converge the skills and knowledge of domain experts to look at the internal processes a knowledge worker uses to codify and utilize information in a fashion to what Donald Schon calls reflection-in-action.

We can say that the purpose of the mindmap is to enable KWs to "think effectively" (p.13). Most peoples’ thinking, is not clear, focused, or systematic enough to perform knowledge work competently. The purpose of the Human Knowledge MindMap is one approach that enables users to do this. Whether during learning, or on a job, effective thinking consists of a set of components as characterized in the mindmap.

Table 1 Knowledge worker thought processes

Sheridan suggests that to carry out this activity, the worker should do the following:

• Pick a situation, problem, challenge, decision or choice of interest or concern (on whatever basis you regard as appropriate).

Then proceed with the following steps:

• Identify which aspects are of most interest or concern to you.
• Prioritize (rank) your interests or concerns.
• Using the Human Knowledge MindMap as a visual guide, apply the relevant concepts to the most important (prioritized) aspects of your interest or concern (limit it to the top three aspects on your list to begin with).
• If you don’t recall whether or nor a particular concept is relevant, refresh your memory by re-reading the one-page outline.
• From this point apply the methodology as outlined above (this may, in addition to other things, require reading more materials to acquire the necessary depth of understanding in the issues you are trying to deal with).

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References:

Sheridan, W.P. How to Think like a Knowledge Worker:A guide to the mindset needed to perform competent knowledge work. United Nations Public Administration Network, New York. [Internet] Available from: http://unpan1.un.org/intradoc/groups/public/documents/unpan/unpan031277.pdf [Accessed 24 August 2008]

Thinking like a Knowledge Worker

Return again to a topic I looked at recently, here's some insights to thinking like a knowledge worker I discovered while undertaking my research on the subject. The concepts explored here are investigated in much more depth in a paper called How to Think like a Knowledge Worker by William P. Sheridan. I'd love to go into the level of detail that the author does, but to invoke the spirit of Star Trek's Dr. McCoy "For God's sake Jim, - I'm a blog, not a research paper."

"I'm a Doctor, not a blog..."

Moving on...

In his paper, Sheridan asserts that

Knowledge consists of concepts available to process information and guide action. Knowledge Management refers to "smart use of know-how." In a knowledge economy more and more tasks involved "think work."Thinking involves the separation of relevant information from irrelevant information. Therefore, "think work" is a component of "knowledge work," specifically the information processing part - the other part is just the "informed action" part.

(2008 p.5)

The author asserts that by assembling a "Human Knowledge Mindmap" (see Figure 1) we can develop a method to ensure the quality of knowledge worker outputs. He cites the example of W. Edwards Deming's methodology for quality control in industrial economies being "shunned" in the US, but being a key component in the growth of the Japanese automobile industry in the middle- to late 20th century as an example of how ignoring such approaches is done at organization's peril.

The central ideas of Sheridan's approach are Conceptual Pragmatism and Cognitive Economy.

If your question is "How do I know?" then [your answer] will involve some combination of empiricism, rationalism and constructivism. Such cognitive amalgamations do what makes "knowing" possible.

(p.9)

Figure 1. Human Knowledge Mindmap (after Sheridan)

We can say that there are three factors that characterize knowledge:

1. Empiricism (observable facts)
2. Rationalism (thinking things through)
3. Constructivism (formulating new ideas)

While we all undertake all three of these approaches, most people emphasize one of the trio; these "habits of emphasis" lead to partial or at best inadequate learning and knowing.

More...

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References:

Sheridan, W.P. How to Think like a Knowledge Worker:A guide to the mindset needed to perform competent knowledge work. United Nations Public Administration Network, New York. [Internet] Available from: http://unpan1.un.org/intradoc/groups/public/documents/unpan/unpan031277.pdf [Accessed 24 August 2008]