Archive for June, 2011

This was a fascinating article, which makes an argument similar to the one I have been working on.  The authors do note that there is little hard evidence to support their argument that, “[a]t the core, the network organization depends on a network of relationships forged on the basis of face-to-face interaction” (304). Nonetheless, I think the ideas are worth thinking over.

Nohria & Eccles recognize that “because of the efficiency and ease of use of electronically mediated exchange the temptation is that it will replace relationships based on face-to-face interaction” (p.  289) (the so-called substitution hypothesis). Using the same term that Graham took from Reigeluth’s “valued outputs”, they ask “whether these electronically mediated exchanges can be as effective. Our view is that they cannot” (p. 289, emphasis added).

When the interactions are “role based, certain, routine, and unchanging,” or “impersonal, unambiguous, standardized, and atomistic,” and follow “the more traditional market or hierarchical organization” (p. 300), electronically mediated exchange to replace face-to-face interaction may be quite effective, state the authors. However, we live in a world of great and rapid change: globalization, rapid entry and exit of competitors, unpredictable emergence and obsolescence of products and technologies, customization of demand, flexible manufacturing, and an increasingly mobile and heterogeneous work force.  These factors “combine to create conditions of unprecedented knowledge intensity, uncertainty, ambiguity, and risk (Piore and Sabel 1984; Miles and Snow 1986; Child 1987; Drucker 1990; Eccles and Nohria 1991)…. [T]o respond to these conditions…firms must be fast, flexible, responsive, and knowledge intensive. They must be action-oriented…” (p. 290).  These responses to such conditions “are difficult to address through electronically mediated exchange” (p. 289).

Three fundamental differences between electronically mediated and face-to-face exchange combine to create this difficulty.  First, face-to-face interaction is always copresent, whereas in electronically mediated exchange “all kinds of social context clues are filtered out” (p. 293) (an argument which concurs with Graham’s dimensions of space and fidelity).  Secondly, face-to-face exchange has high fidelity, for ir “captures the entire bandwidth of human interaction. It covers all the senses…, [and] it also captures the full range of psychoemotional reactions….” (p. 293). The authors cite Goffman (1963), who writes that beyond impressions “given,” there are also those “given-off” inadvertently.  These can be assessed in face-to-face settings but are difficult if not impossible to recognize with electronic mediation.  Thirdly, “relative to electronically mediated exchange, the structure of face-to-face interaction offers an unusual capacity for interruption, repair, feedback and learning (Schegloff 1987)” (p. 293).  Electronically mediated exchanges are sequential, whereas face-to-face interactions occur sometimes in almost simultaneous time.

The result of these factors are four issues that impact interaction.  First, identities are more uncertain without face-to-face communication: “Before face-to-face communication occurs, our mental image of aperson is incomplete; therefore so is our strategy for interacting with the person” (p. 294).  Secondly, electronically mediated exchange less effective than face-to-face interactions in conditions of ambiguity and uncertainty (p. 295).  Thirdly, mobilizing collective action is difficult at a distance.  While electronically mediated discussions tend to be more egalitarian, they are also more disorganized, with much proposal generation, but a lack in decisive action-taking (see p. 297). It is also harder to get people to commit, to “sign up” electronically than it is to motivate them in person.  Finally, electronically mediated exchanges are “highly susceptible to opportunistic behavior” (p. 297), making trust, the “‘cement’ of all social organization” (p. 298), harder to develop.

Though this is an argument for the business world, it seems that the same applied to education as well. Nohria & Eccles do not argue that electronically mediated exchange has no place in the world of business.  However, in situations of ambiguity, risk, and intensity, face-to-face interaction is the more efficient and effective form of exchange.  Similarly, machine-mediated learning can certainly occur.  However, we suggest that certain types of learning — some skill-based learning and the development of dispositions in particular — is more effective and efficient.  While machines are excellent at consistency and computation, as well as at providing vast quantities of information, humans can much better deal with the risk, intensity, and ambiguity that have been recognized as essentials in transformative learning or becoming.


Nohria, N. & Eccles, R.  (1992). Face-to-face: Making network organizations work. In N. Nohria & R. Eccles (Eds.), Networks and organizations: Structure, form, and action, (pp. 288-308). Harvard Business School Press.


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This article discusses tacit knowledge, using the definition proposed by Polanyi (1967) of what we know but find hard to articulate.  I think tacit knowledge is part of becoming, or the learning that goes a step beyond knowing and doing.  Tee & Kareny argue that “although text book publishers or e-learning course producers can process formal or explicit knowledge effectively …, they are unable to help learners cultivate the kinds of tacit knowledge needed to thrive in the world we live in today….  Ultimately, the more widely available explicit knowledge becomes, the greater the importance of tacit knowledge. Tacit knowledge forms a critical foundation for meaning making and developing understanding that helps learners differentiate the relevant from the irrelevant during an era of information explosion …” (p. 386).

The authors draw on the naturalistic methodology proposed by Lincoln & Guba (hey! I just learned about them a few days ago in my Evaluation course!), who feel that “the sole research instrument that can uncover tacit knowledge is the human instrument” (p. 388).  They list a few key human characteristics, which interested me as I continue to think about human- versus machine-interaction: “responsiveness, adaptability, holistic emphasis, knowledge base expansion capabilities, and processual immediacy” (p. 388).

Tee & Karney therefore did a qualitative study of the interactions of an online course, to see how tacit knowledge was shared and cultivated in the course.  They write: “Knowledge—particularly tacit knowledge—is best shared and cultivated in a climate oflove, care, trust, and commitment (resulting in a safe learning environment)” (p. 409).  They also comment that the course instructor “seemed to have inadvertently created an elementary ba, or a shared context for knowledge sharing, creation, and utilization (Nonaka & Konno 1998)…. Without an enabling ba, the knowledge acquired is decontextualized and tends to be inert and of little practical utility, because knowledge, thinking, and the context for learning are inextricably linked (Bereiter 2002; Brown and Duguid 2000; Lave and Wenger 1991; Whitehead 1929)” (p. 407-8).

In addition to creating the conditions for cultivating tacit knowledge, Tee & Karney believe that there are certain “inducing processes” for cultivating it as well.   These concepts come from Nonaka, who also writes on the concept of ba. Together these inducing processes help cultivate tacit knowledge.  They are:

  • Socialization: particularly shared experiences
  • Externalization: for example, discussion boards which require students to elaborate on a concept or explain an idea
  • Combination: synthesis, reconfiguring knowledge to form a new basis of knowledge. Requires greater organization of knowledge
  • Internalization: generally a personal process, but also happens in group context

I would have liked even more theoretical background about tacit knowledge, but this did make interesting connections between the development of tacit knowledge (becoming) and human interaction (socialization and the overarching concept of ba which they feel is vital to sharing tacit knowledge.

Tee, M. Y. & Karney, D. (2010). Sharing and cultivating tacit knowledge in an online learning environment. International Journal of Computer-Supported Collaborative Learning, 5(4): 385-413. doi:10.1007/s11412-010-9095-3. http://www.springerlink.com/index/10.1007/s11412-010-9095-3.


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Olson & Olson argue in this article that “[t]here are characteristics of face-to-face human interactions, particularly the space–time contexts in which such interactions take place, that the emerging technologies are either pragmatically or logically incapable of replicating” (p. 140-1).  For example, though one study showed no difference in the output produced by a face-to-face (collocated) group as compared to one working at a distance, nevertheless “the process of [the distance group’s] work changed, however, to require more clarification and more management overhead…” (p. 152).  This connects to our choice of Reigeluth’s valued outputs, including efficiency. Thus these author feel, as do I, that certain types of work (and I would also say learning) are inefficient when attempted at a distance.

The authors refer to one study that found that collocated groups had double the function points per unit of staff time as corporate average (p. 145).  They attribute this to factors such as the fluidity of participation (p. 146), “the spatiality of human interaction” (p. 146), and the fact that the teams had worked together long-term and held established working habits (p. 148).  Olson & Olson note several key characteristics of collocated synchronous interactions (p. 149), namely: rapid feedback (allowing quick corrections), multiple channels (allowing redundancy, as well as many ways to convey subtle or complex message), personal information (enabling participants to judge the characteristics of the source), nuanced information (allowing very small differences in meaning to be conveyed and information to be easily modulated), shared local context (enabling easy socializing and mutual understanding), informal “hall” time (making possible opportunistic information exchanges and important social bonding), individual control (providing rich, flexible monitoring of how all are reacting), implicit cues (wherein the natural operations of human attention provide access to important contextual information), and spatiality of reference (whereby both people and ideas can be referred to spatially).

Despite this judgment, the authors “focus on the sociotechnical conditions required for effective distance work and bring together the results with four key concepts: common ground, coupling of work, collaboration readiness, and collaboration technology readiness. Groups with high common ground and loosely coupled work, with readiness both for collaboration and collaboration technology, have a chance at succeeding with remote work” (p. 139).

  • Common ground: the knowledge people have in common, and are aware that they have in common. “[W]e construct common ground from whatever cues we have at the moment. The fewer cues we have, the harder the work in constructing it, and the more likely misinterpretations will occur” (p. 158).  Since distance interaction provides fewer clues, it is harder for such teams to establish common ground. “The more common ground people can establish, the easier the communication, the greater the productivity. If people have established little common ground, allow them to develop it, either by traveling and getting to know each other or by using as high-bandwidth channel as possible” (p. 161).
  • Coupling in Work: “Tightly coupled work is work that strongly depends on the talents of collections of workers and is nonroutine, even ambiguous. Components of the work are highly interdependent. The work typically requires frequent, complex communication among the group members, with short feedback loops and multiple streams of information” (p. 162).  They note that “tightly coupled work is very difficult to do remotely” and therefore advise “design[ing] the work organization so that ambiguous, tightly coupled work is collocated” (p. 163).
  • Collaboration readiness: They state that “one should not attempt to introduce groupware and remote technologies in organizations and communities that do not have a culture of sharing and collaboration” (p. 164).
  • Technology readiness:  Their advice is that “advanced technologies should be introduced in small steps” (p. 166).

For my interests, the most important argument is the efficiency one which Olson & Olson make, that “[t]here are characteristics of face-to-face human interactions … that the emerging technologies are either pragmatically or logically incapable of replicating” (p. 140-1).


Olson, G.M. & Olson, J. S. (2000). Distance matters. Human–Computer Interaction, 15 (2): 139–178. http://www.informaworld.com/index/784767943.pdf.

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In this article, Jarvela & Hakkinen (2003) use Selman’s (1980) sociocognitive construct of “perspective-taking” to evaluate the level of asynchronous discussions.  As they do, they had some interesting things to say about human- and machine-interaction.  They write, for example, that “[s]ome of the most important processes in human communication, like creation of mutual understanding or shared values and goals, are hard to reproduce in the Web environment” (p. 77-8).

This made me ask: which kinds of learning require “the creation of mutual understanding or shared values and goals”? Do knowledge acquisition or skill development require mutual understanding or shared values?  Perhaps this quotation sheds light on the kind of knowledge they indicate: “Studies report how networked interaction in many learning projects results in superficial and experience-based discussion, but does not reach the level of theory-based reflection and argument. Yet, theory-based discussions and expert knowledge are crucial for high quality knowledge construction and learning (Bereiter & Scardamalia, 1993)” (p. 78). I wondered whether this has anything to do with becoming, or whether it was just about critical thinking.

The authors discuss the challenge to continuously construct a common cognitive environment in asynchronous discussion without immediate social interaction (see p. 79).  There is a loss of the rich fidelity of face-to-face communication.  This affects our ability to solve the “mutual knowledge problem (they reference Graumann, 1995; Krauss 8c Fussell, 1990; Nystrand, 1986), which the authors state is part of effective communication. “According to the researchers in the field of sociolinguistics, the mutual knowledge problem derives from the assumption that to be understood, speakers must formulate their contributions with an awareness of their addressees’ knowledge bases. That is, they must develop some idea of what their communication partners know and do not know in order to formulate what they have to say to them. Research on collaborative learning also calls for reciprocity in social interaction (Crook, 1994)” (p. 79).

At this point they begin to focus on the issue of reciprocity, referring to their own earlier research which gave “evidence that reciprocal understanding is a typical phenomenon in technology based interactions…” (p. 79).  Then they invoke Selman (1980) and Flavell, Botkin, Fry, Wright & Jarvis (1968) to argue that “[p]erspective taking skills are critical to successful human functioning and involvement in everyday social interaction” (p. 80).  They also state that “…Web-based interaction basically involves the essential features of reciprocity…”(p. 81). As Graham and I have talked about human- and machine-interaction, it is clear that the authors here are referring to human interaction that happens to be mediated by a machine.

I would have loved to see them write a bit more about how “speakers … formulate their contributions with an awareness of their addressees’ knowledge bases” (p. 79) when they are communicating online versus face-to-face. This “mutual knowledge problem” is an interesting element of human interaction which, it seems, can be handled face-to-face and at a distance, though perhaps more effectively with co-presence.


Jarvela, S. & Hakkinen, P. (2003). The levels of web-based Discussions – using perspective-taking theory as an analysis tool.” Cognition in a digital world.


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This article is the opening editorial for the journal E-learning.  I wanted to just record one insight that I found especially interesting.  The author writes that Jonathan Swift’s “writing machine” in Book 4 of Gulliver’s Travels reminds him “of various ‘teaching machines’ that promised an automation of teaching and learning. And perhaps also thinking, in the sense of metacognition models based on computer simulations…” (p. 2).

Peters writes this because he wants readers to understand that “[w]ith e-learning, then, we must be willing to recognise the deep structure of the medium…” (p. 1).  Nevertheless, E-learning, he states, was founded with “the clear policy intention of scrutinising the dominant technicist view” (p. 5).  More importantly, in our “rapidly evolving contemporary history, one might be tempted to think that the history of teaching and learning machines, indeed, the history of e-learning, was purely a technical matter, prescribed by technological change and the invention of machines. Yet this machinic history certainly gives way when the events are relocated within a wider political economy of learning and educational change and when the ‘culturalisation’ of technical knowledge raises the stakes of the argument, as an example of symbol manipulation” (p. 3).

I think these statements are interesting about the importance of the wider political and cultural factors.


Peters, M. A. (2004). E-learning machines. E-Learning, 1(1): 1-8.

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Just a few words on this article by Richard Prawat (1989).  Prawat is making an argument about acccess, which he defines as “the ability to draw on or utilize one’s intellectual resources in situations where those resources are relevant” (p. 1).  He discusses three major sets of variables identified by the cognitive psychologists: knowledge base, strategy, and disposition.  These variables are affected, Prawat argues, by two factors: organization and awareness.  I want to discuss briefly his three variables, which overlap to some extent with knowing, doing, and becoming.

Knowledge base: In this category reside “several overlapping but distinguishable types of knowledge,” including formal and informal knowledge, conceptual and procedural knowledge, and concrete or representational knowledge (p. 2).  Organization affects knowledge base as teachers make linkages and connectedness between topics and ideas.  Good teaching, Prawat argues, fosters “relationship understanding” (p. 6).  Awareness likewise affects the learner’s knowledge base, and for this reason Prawat suggests techniques of verbalization; writing about content; classroom dialogue; conditionalizing knowledge; and broadening the problem-solving purview.

Strategy: Prawat defines strategy as “a broad range of routines that facilitate both knowledge acquisition and utilization” (p. 3).  This category seems to overlap with “skills” or “doing” in my mind, though I’m sure he sees distinctions.  He feels that organization affects strategy because one must negotiate a trade-off between general and specific strategies.

Dispositions: Prawat offers the definition given by Katz for dispositions: “‘habits of mind’ (Katz & Raths, 1985)” (p. 3).  This is a term we have interchanged with becoming (for lack of a better word, because becoming does seem to be more than only dispositions).  Here Prawat differentiates between actions (an aspects of strategy) and action identity (an aspect of disposition).

Prawat, R. S. (1989). Promoting access to knowledge, strategy, and disposition in students: A research synthesis. Review of Educational Research, 59(1): 1-41. doi:10.2307/1170445. http://links.jstor.org/sici?sici=0034-6543%28198921%2959%3A1%3C1%3APATKSA%3E2.0.CO%3B2-D&origin=crossref.

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Tonight I finished an article by Jonathan Lazar & Jennifer Preece (2003), which discusses the factors which lead to and possible measures by which to gauge success in online communities.  One factor is usability — how useable the software and internet interface is.  The other factor discussed is sociability, since “[i[nformation from a disembodied source has limited value and soon lacks appeal” (p. 128).  This statement relates to ideas about human interaction which we have been discussing.

The authors refer to three general principles for software uability, proposed by Shneiderman (1998).  I found these interesting, since they are part of the strengths of machine-interaction.  They are:

  1. consistency
  2. control
  3. predictability

Web usability must also consider these factors: navigation, access, and information design (content comprehension & aesthetics).

The authors write:

Success of an online community is encouraged by a blend of welldesigned software (i.e., usability) and carefully crafted social policies (i.e., sociability. (p. 134)

In applying the idea to my research, I wondered if you could also say:

Success of a blended course is encouraged by a blend of well-designed machine interaction (i.e., usability) and carefully crafted social or human interactions (i.e., sociability)

The authors listed three sociability issues to consider, namely: registration, trust & security, and governance.

Finally, this quotation from the authors ties in to my research about human versus machine interaction in blended learning settings, and the effect those types of interaction can have on becoming:

The way that information is conveyed can affect your emotional reactions to it and the way that you subsequently behave. (p. 129)


Lazar, J. & Preece, J. (2003). Social considerations in online communities: Usability, sociability, and success factors. In Cognition in a digital world, 127-151.


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