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Archive for January, 2011

I just finished an older article by Garrison in which he argues that distance education has primarily followed an industrial approach thus far, but with the use of computer conferencing tools can transform to a post-industrial one.  According to Garrison, the dominant industrial model focuses on mass communication and mass production, with learners engaged in independent study (rather than collaborative work).    “Industrialised distance education is mass education,” (p. 7) Garrison writes.  The approach is therefore prescriptive, objectified, and depersonalized; communication is rarely two-way in this model.

Computer conferencing has the potential to frame distance education with an entirely different world view, the post-industrial model.  This “emerging world-view of distance education incorporates highly interactive communities technology along with the ideal of both personalised and collaborative learning” (p. 3).  At the time of this article’s publication, most computer-mediated communication (CMC) was asynchronous text-based communication in one-to-one or one-to-many context, and thus much of the article focuses on the advantages of asynchronous written communication.  For example, it is argued that there is a “qualitative difference between real-time verbal and asynchronous written communication [because of]… the reflective and precise nature of written communication” (p. 4).

In addition to offering time for reflection and precision, CMC offers the potential for collaborative learning.  Garrison quotes one of his own earlier articles, writing that “[c]ollaborative constructivist approaches to learning at a distance … reflect the ideals of collaboration and independence respectively (Garrison 1993a; 1995)” p. (8).

As one who has taught high school English for 10 years, and perhaps also because of my own personality (I like to mull things over), I definitely am attracted to the “reflective and precise nature of written communication” (p. 4).  I have loved the depth of the asynchronous discussion boards my OHSU and BYU students have written.  I also like the possibility that “[d]iscussion in a computer conference … tends to be focused on content issues and less on personality” (p. 5).  I do know, however, that some students struggle with this text-based form of communication.  Garrison cites several (White, Fuweiler, Applebee) who argue that writing is essential to cognitive development.  I need to look into their arguments; if the connection is strong, then it seems important to me that we use writing activities even with more reluctant writers.

References

Garrison, D.R. (1997). Computer conferencing: The post-industrial age of distance education.  Open Learning, 12(2), 3-11.

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Note: I wrote this last month, but neglected to post it to this blog.

We all want to know what it takes to excel.  Perhaps there is not a single domain that we passionately wish to dominate, but we admire excellence and are astounded by the feats of those great performers in history.  We wonder, too, what it takes to shoot hoops like Michael Jackson or compose music like Mozart.  Typically, we explain great performance in one of two ways: those who truly excel work harder than the rest of us.  Or, they possess some inborn talent for excelling in their chosen field.  In Talent Is Overrated, author Geoff Colvin, a highly respected journalist and the senior editor-at-large of Fortune Magazine, attacks both of these explanations for greatness, and offers an alternative: deliberate practice.  In this review, I will explain Colvin’s arguments, make some comparisons to a similar book published in the same year (Outliers by M. Gladwell), and connect the book to the field of instructional design.

Of the two beliefs about where great performance comes from, Colvin spends more time attacking the role of talent (hence the title of the book).  There may still be some gene that predisposes one to excellence at golf, but as of now, no research has turned it up.  Specifically targeted innate abilities – “gifts,” we often call them – are fictions.  In fact, Colvin explains, many of the world’s “greats” are “amazingly average” (Colvin, 2008, p. 7).  Intelligence is useless in predicting most great performance, for performance relies on developed abilities in specific domains, while intelligence only demonstrates extraordinary general abilities.  It is true that IQ is a decent predictor of performance at unfamiliar tasks; however, once a person has learned the domain, IQ no longer gives an edge.  Colvin’s argument draws heavily on the work of Anders Ericsson, whom he credits in his acknowledgements.  Ericsson saw subjects increase their ability to memorize numbers from the accepted seven-number limit (plus or minus two) to digit lists stretching into the hundreds, and argued for “the remarkable potential of ‘ordinary’ adults and their amazing capacity for change with practice” (p. 38).  Thus memory too, often seen as a quality that many excellent performers have in overabundance, is also a developed and not an innate ability (p. 46).

This emphasis on practice and development might initially seem to support the second belief about great performance: those who truly excel do so because they work harder than the rest of us.  After all, Colvin describes a study of British musicians, which showed that only one factor “predicted how musically accomplished the students were, and that was how much they practiced” (p. 18).  Colvin also refers to the “ten year rule,” a general rule of thumb that it takes at least ten years to master a domain.  However, Colvin distinguishes between deliberate practice and the type of practice most of us do, which “hasn’t accomplished a thing” (p. 66).  For the rest of his book, he first explains what deliberate practice is, and then, finding the principles widely generalizable, applies them to his own domain of expertise: the business world.  It is important that American business people understand and practice these principles, Colvin notes, because today’s large-scale global labor market has dramatically increased the pressures on individuals and businesses to excel: today they truly must “go up against” (p. 15) the world’s very best.

Read the rest of my review here:  Lit Review – Talent Is Overrated.final.

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Today in Charles Graham’s course we discussed Terry Anderson’s article alongside two by Michael Moore.  Anderson combines theories of learning with the context of online education to suggest some outlines for a theory of online learning.  I was a little unsatisfied when I finished the article, perhaps because I wanted a full-blown theory, not just something moving “towards” one.

Anderson adopts the argument of Bransford, Brown and Cocking (1999), who state that “effective learning environments are framed within the convergence of four overlapping lenses. They argue that effective learning is community-centred, knowledge-centred, learner-centred, and assessment-centred” (p. 47).  Anderson first discusses being “learner-centered,” which seems most fundamental to teaching.  I found this line especially interesting as he discussed “knowledge-centered” learning: “John McPeck (2000) and other critical thinking theorists argue that teaching general thinking skills and techniques is useless outside of a particular knowledge domain in which they can be grounded” (p. 48).I think that I want to study online and blended courses in the domains of the humanities and history.  What are “the epistemology, language, and context of disciplinary thought” in these fields?  How does that impact what arguments I can hope to make?  I also found the concept of community-centered learning to be important.  I was surprised to read that Lipman was responsible for the idea of “community of inquiry,” something I had attributed to Garrison.  Need to do some reading up on this!  Finally, as Anderson discussed the concept of being assessment-centered, I appreciated the “growing list of tools provide such assessment without increased teacher participation” (p. 50).  Some of the listed items were even among things I proposed while teaching online, to lessen the workload, though the ideas were not accepted.  Glad to see such a list exists!

Anderson adds three more interactions to the list begun by Michael Moore.  Later, he writes that “sufficient levels of deep & meaningful learning can be developed as long as one of the three forms of interaction (student-teacher; student-student; student-content) is at very high levels. The other two may be offered at minimal levels or even elimimated without degrading the educational experience (Anderson 2003b)” (p. 66).  I don’t think I agree with this.  I feel that at least two of the forms of interaction must be present.  I guess you can go out and read a book on your own, with only student-content interaction.  But even then, the learning and retention will be greater if the ideas are shared with others.  Also, after reading Talent Is Overrated by Geoff Colvin, I’m more convinced than ever that even the most “expert performers” rely not only on practice (student-content interaction) but also on the feedback they receive from mentors (student-teacher interaction).

Thereafter he is to propose a “model of e-learning.”  But I didn’t feel there was a model.  Did I miss something?? I see a diagram, but it is never fully explained, and frankly, it is confusing without explanation.  Is that the “model of e-learning”?  Anderson also discusses Prensky’s idea that “different learning outcomes are best learned through particular learning activities” (p. 62), but that isn’t turned into a model, either.  As he ends, not having proposed a full-fledge theory, he does write that “we can expect, however, … that online learning – like all forms of quality learning – will be knowledge-, community-, assessment-, and learner-centred” (p. 68).  Here he comes full circle, but without ever having explained what online learning that is knowledge-, community-, assessment-, and learner-centered will look like.

References:

Anderson, T. (2008). Towards a theory of online learning. In T. Anderson (Ed.), The theory and practice of online learning (2nd ed., pp. 45-74). Edmonton, Canada: Athabasca University Press.

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For Dr. Graham’s class this week, we read two articles by Michael Moore, one of the pioneers and leaders in the field of distance education, and currently the editor of the American Journal of Distance Education.  In one article, from 1989, Moore discusses three types of interaction in distance education: learner-content interaction (without which there is no education, he writes), learner-instructor interaction (especially important, he points out, at the point of application, an idea echoed in the book Talent is Overrated which I read about a month ago), and learner-learner interaction (which Moore says is a newer development to distance education and one more important to younger or less autonomous learners).  These categories seem pretty straightforward to me (though must they only apply to distance education? are they not also the categories of interaction in face-to-face settings?), so I would like to know more about the critiques of this method of categorization.  I do know that other writers, such as Terry Anderson, have added additional interactions on the part of teachers and content.  The idea that struck me most in this article was Moore’s argument for the importance of using a variety of media.  With only one form of media, he says, interactions can only take place in one way.  He closes the article by stating that “it is vitally important that distance educators in all media do more to plan for all three kinds of interaction, and use the expertise of educators and communication specialists in both traditional media – printed, broadcast, or recorded – and newer teleconference media” (p. 6).

Moore’s second article discussed the key concepts and the impact of his theory of transactional distance.  The three concepts — structure, dialogue, and autonomy — seem straightforward at first glance.  However, I have found myself wanting more clarity in the distinction between autonomy and structure.  While autonomy is said to be a characteristic of the learner, yet it is broken down into elements (goals, evaluation, and execution) which are at least in part structural and all frequently decided by the instructor.

Of his three components, dialogue is of the greatest interest to me.  Moore himself notes the overlap between his concept of “dialogue” and Holmberg’s concept of “conversation.”  Yet as I wrote before, Holmberg’s use of conversation is not as compelling to me as Andy Gibbons’ metaphor of instruction as conversation.  Gibbons writes that “conversation [is] the most comprehensive and useful metaphor that an instructional designer could use today to inspire and generate designs” (p. 6)  He defines instruction as “the intentional engagement of two or more agents capable of decision-making in purposeful conversation.” (6)  What would a study based on the metaphor look like?

References

  • Gibbons, A.S. (In press). Instruction and learning, technology and design.
  • Moore, M.G. (1989).  Three types of interaction.  The American Journal of Distance Education, 3(2), 1-6.
  • Moore, M.G. (2007). The theory of transactional distance.  In M.G. Moore, Handbook of Distance Education Today (2nd ed.), pp. 89-108.  Mahwah, NJ: Lawrence Erlbaum Associates.

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Note: I wrote this last month, but neglected to post it to my blog.

We all love stories.  Bedtime stories, stories around the water cooler, aviation stories told by President Uchtdorf in General Conference.  Abraham Lincoln was loved by many (and scorned by not a few) because of his propensity to respond to any situation with “That reminds me of a story….” As I listen to the young adult novel Goose Girl for my upcoming book club (in which we will share the stories which touch us most), I can tell that storytelling will be increasingly important as the tale continues.  In Tell Me A Story, author Roger Schank explains how stories are powerful not merely as entertainment but as the very core of knowledge and intelligence.  As he does so, he delves into issues of understanding, memory, indices, culture, and artificial intelligence.  In this review, I will summarize the key points of each chapter, and comment on what I found to be most compelling or significant.

Schank opens Chapter 1 (“Knowledge is Stories”) by explaining the concepts of reminding (“the mind’s method of coordinating past events with current events to enable generalization and prediction” (p. 1)) and scripts (sets “of expectations about what will happen next in a well-understood situation” (p. 7)), both of which function as segues into a discussion of knowledge, intelligence, and stories.  For Schank, knowledge “is experiences and stories, and intelligence is the apt use of experience and the creation and telling of stories….  In the end all we have, machine or human, are stories and methods of finding and using those stories” (p. 16).  With intelligence defined as “the ability to tell the right story at the right time, understanding a story means being able to correlate the story we are hearing with one that we already know” (p. 21, italics added).  To make this correlation, we must construct labels (or indices) which can be used to retrieve similar situations.  We then show understanding through “responsive storytelling,” and conversations “are really a series of reminding of already-processed stories” (p. 24).  As we search for a comparable story to share in conversation, we are not trying to remember every detail of the original experience, but to find the “gist” of a story, which we can then transform into language and thus into conversation (p. 25).  Schank closes the chapter by explaining the interactions between stories, gists, language, and conversation:

[T]he problem of generating language can be reduced to the problem of selecting the gist or gists of thousands or millions of not necessarily conscious ideas to be transformed into a particular linguistic expression…. [T]aking one’s part in a conversation means no more than searching for what one has already thought up and saying it….  Even innovative thinking relies upon the mechanisms of reminding and the transformation of existing stories to new situations. (p. 26)

These provocative statements left me with much to chew on.  I’m a horrible joke teller, because I never remember the details of the storyline: does this mean I am missing a key part of intelligence?  What is creativity, if everything relies on merely transforming the old into something new?  How do we better index our memories, so that we may more readily be reminded and have the “just right” story to share in conversation?  Schank does tackle some of these questions in subsequent chapters.

Read the rest of my review here: Lit Review – Tell Me A Story.final

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I just finished reading several chapters from Borje Holmberg on conversation theory and his empathy approach.  I was excited to read these to find out Holmberg’s theory of conversation.  Ever since reading Andy Gibbons’ chapter from his still unpublished work, Instruction and Learning, Technology and Design, I have been drawn to Gibbons’ “definition of instruction: Instruction is the intentional engagement of two or more agents capable of decision-making in purposeful conversation.” (6)  I have wanted to read other theories of conversation in instruction, and felt that perhaps I could address this topic in further research.

I find Holmberg’s theories and suggestions interesting.  But at least in these three chapters, I do not see a clear definition of “conversation.”  With Gibbons’ definition of instruction through conversation, concepts of intentionality, agency, and purpose arise.  I don’t get that sense from Holmberg’s use of “conversation.”  Holmberg is more interested in the adjective (“conversational” or “conversation-like”) than in the noun, I think.  For example, he encourages “conversation-like presentations of learning matter” (2003, p. 82) and “the conversational approach” (1999, p. 59).  He quotes Harri-Augstein to argue that “learning conversation is not idle chatter” (50), and then explains a theory of using reflection and metacognition to increase learning.  These are important concepts, but they aren’t what I expected (after Gibbons’ definition) in terms of a theory of conversation.

I am having a gut reaction without knowing enough, but I want something that more deeply explores how to structure learning as conversation, not just conversation-like.

References

  • Holmberg, B. (1995).  Course development—fundamental considerations.  In B. Holberg, Theory and practice of distance education.  London and New York: Routledge. pp, 45-67.
  • Holmberg, B. (2005).  A theory of distance education based on Empathy.  In M.G. Moore & W.G. Anderson (Eds.).  The handbook of distance education (1st ed.), pp. 79-86.  Lawrence Erlbaum Associates: Mahwah, NJ
  • Holmberg, G. (1999).  The conversational approach to distance education.  Open Learning, 14(3), pp 58-60.

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With the opening of the new semester, I’ve begun teaching “Introduction to Middle Eastern Studies” at Brigham Young University.  This is a face-to-face course, but we are implementing some asynchronous elements, including a weekly discussion board using BrainHoney and the sharing of tweets about current events in the Middle East.  For the latter activity, students signed up on a GoogleDoc for different countries or issues pertaining to the region.  Now they are posting tweets about that country or issue.  I’m excited about all they are sharing, including links but even more so their commentary on those links.

From my part, it was exciting to “see” the collapse of the Tunisian government while they were tweeting.  I felt somehow more involved in the event because students were capturing tweets on the fall while it happened.

Check out our conversations at #mesa201!

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