Category Archives: knowledge community

Catching Up, CSCL, and Comps

Catching Up

So much has been accomplished since my last post about the Common Knowledge Alpha launch!  Since then, we’ve launched Common Knowledge Beta and subsequently, a 9-week enactment of Common Knowledge Solar in 2 grade 5/6 classrooms, as a major component of the EPIC project’s year 2 classroom interventions.   I’ve also done 2 presentations at AERA 2013 (San Francisco, CA, USA), and co-presented a webinar (with Jim my supervisor – Prof. Jim Slotta) to graduate students at Beijing Normal University and 3 other universities in China.  These events have been somewhat monumental in my academic journey, and they each deserve their own post (which I’ll have to do some other time).

CSCL & Comps

More pressing deadlines are nipping at my heels:

  1. CSCL 2013 presentations (workshop & short paper presentations)
  2. My comprehensive exam (7000 word literature review) – affectionately known as “comps”

Yesterday, I read 3 Gerry Stahl papers, in preparation for the “Across Levels of Learning: How Resources Connect Levels of Analysis” CSCL pre-conference workshop I’m attending. Funny thing is, Gerry Stahl (respected scholar and a workshop organizer) offered me a time slot to present my work and have discussion/feedback about it (I had only asked to attend, not present at this). So of course I’ll take it – what an honour, right? I have to make 1 slide (due tomorrow) for this workshop presentation.

His 3 papers speak to what Jim  was saying about my dissertation work at our recent meeting – that my work doesn’t quite fit with scripting and orchestration literature, and that I should focus on KB discourse and KB practice. A bit surprising to hear, since one of my main interests and analysis focuses has been to look at how teachers orchestrate online and offline classroom discussions to facility community progress in collective/collaborative inquiry.  Anyway, in Stahl’s 3 papers (and what this workshop is about), he says that “a central research issue for CSCL” is how does collaborative knowledge building take place? He also says we need to understand how individual cognition and societal institutions affect small-group meaning-making processes.

Looking at Levels of Learning and How They’re Interconnected

Gerry Stahl points out there are 3 planes in which learning, cognition, and knowledge building can be analyzed:

  1. individual learning
  2. small-group cognition
  3. community knowledge building

Stahl says we need to understand how these planes interconnect, and he’s particularly interested in the conceptual connections between these planes. This brings me full circle back to what Jim was saying at our recent meeting – that the Knowledge Community and Inquiry (KCI) model doesn’t address:

  1. how discourse informs the knowledge base, and
  2. how learners use the shared collective knowledge base to decide what to do next

Stahl suggests looking at “interactional resources” – how are these generated/modified as a result of their interaction with individuals/small-groups/community. To my mind, “interactional resources” in my case, would be the Common Knowledge (CK) notes themselves. The CK tablet UI would be personal inquiry spaces, the CK interest group “Knowledge Boards” would be small-group shared inquiry spaces, and the CK “Common Board” displayed on the classroom’s SMARTBoard would be the community shared inquiry space.

Still playing with these ideas (mostly because I have to figure out what to put on this 1 slide – which Gerry Stahl has scripted to have the following headings):

  • Main claim
  • Illustrative resource
  • Supporting data
  • Current status

My main struggle right now is what to put for “Main Claim”.  I think this is also really pivotal for my comps and dissertation work, so this workshop prep is very timely :).

If you’re interested, here are my Researchr notes from those 3 Gerry Stahl papers:

  • Stahl, G. (2012). Traversing planes of learning. International Journal of Computer-Supported Collaborative Learning, 7(4), 467-473. Springer.
  • Stahl, G. (2013). Learning across levels. International Journal of Computer-Supported Collaborative Learning, 8(1), 1–12. Springer.
  • Stahl, G. (2013). Transactive discourse in CSCL. International Journal of Computer-Supported Collaborative Learning, 8(2), 1–3. Springer.

Distributing Situated Cognition to Mimic Generalizable Knowledge

Update on Project Natal
In my October 21, 2010 blog post on situated learning spaces, I mentioned Project Natal’s virtual boy named Milo (there’s also a virtual girl named Kate), and posted a 2009 demo launch of Milo.  Peter Molyneux, head of Microsoft’s European games division, has since appeared on TEDGlobal to talk about Project Natal (July 2010), where he showed the real Milo technology on TED’s stage:

We see the demonstrator interacting with Milo using body gestures, facial gestures, and voice – all of which needs to be “taught” to Milo.

Milo’s Mind as Metaphor of Knowledge Building
What really interests me about Milo is what Molyneux says in his TED presentation about Milo’s mind:  “Milo’s mind is in a cloud”.  In other words, the more people who use Milo, the more objects he’ll learn and recognize.  Fascinating!  To me, this implies that Milo’s artificial intelligence is distributed, and Milo’s mind is the synthesis of training combinations contributed by a community of Milo users.  Milo’s mind is a wonderful metaphor for collaborative knowledge construction, where Milo’s mind represents a knowledge community’s World 3 Rise Above knowledge artifact, and the community of Milo users is the knowledge community.

Situating Milo’s Distributed Mind
In my October 21, 2010 blog post, I had hypothesized that “the more the situated learning context approximates a realistic context of the domain of study, the deeper and more meaningful the learning will be”, implying that Milo could contribute to deeper situatedness in wider contexts.

Since then, I have re-read Carl Bereiter’s 1997 book chapter, Situated Cognition and How to Overcome It.  He mentions what he and Scardamalia (1989) have termed intentional learning, which has 3 goal levels:

  1. Task completion goals – to be completed immediately (e.g., assignment due date tomorrow); World 1; highly situated
  2. Instructional goals – to be completed summatively in the near future (e.g., end of the course); world 2; less situated; somewhat transferrable
  3. Knowledge building goals – may extend indefinitely into the far future and past; World 3; weakly situated (i.e. immediate situation); highly transferrable
In my December 7, 2010 blog post, I mentioned Bereiter’s reasoning behind why it would be prudent to overcome situated cognition – situated learning is inversely proportional to generalizability of that knowledge.  Thus, an individual’s knowledge would be high transferrable if that knowledge was learned with an intentional orientation toward knowledge building goals.
Continuing on this train of thought, when I consider the “learning” that Milo “does” as he is being used by multiple members of the Milo user community, I would say that almost all of these learnings are for task completion goals.  Thus Milo’s artificial intelligence should be highly situated and therefore highly ungeneralizable.  If we assume that Milo will have a large and active globally-distributed user community, this alone would exponentially increase Milo’s potential learning situations/contexts.  If Milo is taught by this large globally-distributed user community to recognize an object – a chair for example – in multiple and varied situations, then he should be able to recognize chairs of all types and across all situations.  In other words, the object “chair” mimics generalizability.  Have I found a way to achieve a mimicry World 3 with a low-level goal of task completion – by exponentially increasing learning situations contributed by a large knowledge community?

This brings to mind the authors of Wikinomics (2008) and Macrowikinomics (2010) Don Tapscott and Anthony Williams’ idea of Murmuration Macrowikinomics.  Here’s a narrated video metaphor of it:

Tapscott is careful to note that “…this is not a collective intelligence or collective consciousness of course, because individual birds are not intelligent or conscious…”.  He describes the thousands of starlings moving as one mass, as a “…loosely conjoined network of relationships and impulses” – much like a globally-distributed Milo user community?

Tapscott asks:  “Will we come to consider networking as the neural roots that connect human beings in a way that creates something fundamentally new?”  I do not hesitate to say “YES – but…..!”  Much like Milo’s “mind” (i.e. artificial intelligence) cloud, that grows as his distributed user community “teaches” him more, Milo’s knowledge base will only ever mimic World 3, and appear to be generalizable.  What allows Milo’s mind to mimic generalizable knowledge is the numerous situations in which he has learned the same thing.  If millions of users around the world “teach” Milo to recognize the object known as “chair”, presumably, they’re all using different kinds of chairs available in their homes.  These chairs could vary greatly in age, design, style, size, etc.  Hence, Milo acquires the ability to recognize any chairs that match any one of the millions of chairs his distributed user community has inputed into his memory stores – giving the appearance that Milo has generalized recognition of the object called “chair”.  Milo’s seeming intelligence is indeed artificial.

Back to Tapscott’s question.  I think that networking neural roots connecting people would create something fundamentally new, but not necessarily better.  Like Milo’s mind cloud, this new thing would only mimic World 3 due to the exorbitant number of task-completion-oriented contributions to its knowledge base from its massive and globally-distributed user community.  Highly transferrable World 3 knowledge can only be created with an orientation toward knowledge building goals, and must consider the far past and continue into the far future (Bereiter, 1997).

Bereiter, C. (1997). Situated cognition and how to overcome it. In D. Kirshner & J. A. Whitson (Eds.), Situated cognition: Social, semiotic, and psychological perspectives (pp. 281-300). Hillsdale, NJ: Erlbaum.  Available:

Harnessing the Power of YouTube for Distributed Cognition

I’ve been learning a lot about knowledge communities – including Reciprocal Teaching – (Ann Brown, Anne Marie Palincsar), collaborative knowledge construction (Marlene Scardamalia, Carl Bereiter), and distributed learning (Yvonne Rogers, Michael Cole & Yrjo Engestrom).  However, when I think of “the tubes” (i.e. YouTube, SchoolTube, TeacherTube) and all the learning opportunities they have to offer via traditional transmission instructional strategies – the very strategies we are desperately trying to steer away from – I find myself at a crossroads.  The examples of YouTube learning below have absolutely ZERO aspects of community knowledge creation other than YouTube’s role as video tutorial repository.  Granted, YouTube does allow for the posting of comments for each video, but I have yet to see this feature being used in a way that remotely resembles a community discourse with the goal of deeper understanding.  What follows are some examples of the learning power of YouTube.

Khan Academy
Not sure if anyone has heard of the Khan Academy?  Salman Khan, who quit his job in finance, runs this non-profit educational organization out of a closet in his home.  He regularly creates tutorial videos about an astounding number of science and math topics, and posts them to YouTube.  Here’s a chemistry video about the atom, proton, neutron, and electron:

Common Craft
Then there’s Common Craft, who makes wonderful videos to explain various technologies (e.g. wikis, blogs, augmented reality, etc.).  Here’s Common Craft’s YouTube channel.  Their latest video is about augmented reality:

My 8-Year-Old Nephew
Just to illustrate my classmate, Maria’s, point about the power and appeal of YouTube, I’d like to use my 8-year-old nephew as an example.  Aside from a few ukelele classes he got at his after school program, he has taught himself how to play the ukelele and the guitar by surfing YouTube.  YouTube has fed his motivation to learn both these instruments so much, that he now creates his own ukelele songs (sometimes with accompanying lyrics).  He also gets his parents to take him to local open mic events at least once a week so that he can perform his music.  Furthermore, he gets his mom to video-record his performances so that they can be uploaded to YouTube.  Makes me wonder what he’ll do at age 10.  Here’s my nephew’s YouTube channel if you’re interested.  My favourite song is “I Don’t Know” – hysterical!!!

YouTube for Knowledge Communities & Distributed Cognition?
Contrary to everything I’m learning in graduate school about learning, YouTube, for the most part delivers knowledge in the most pedagogically traditional way.  There is no knowledge community discourse, no distributed cognition, no acknowledgement/accommodation of individual learning styles…it is simply transmission teaching in a digital medium!  Yet, it’s undeniable that such instructional YouTube videos have learning value.  So how might we better use YouTube to enhance learning, promote distributed cognition, and foster knowledge communities?

My first thought is to make better use of the YouTube’s commenting functionality, and use this as a community discussion forum.  However, I think it is better to establish an online learning environment on some other platform, and refer to specific YouTube video resources as the need arises.  This way, the instructor has more tools to work with, in terms of creating an effective online learning environment.  Furthermore, the instructor and participants (through their virtual social presence) may have a clearer picture of how the community’s cognition is distributed and therefore take reasonable actions in their responses to focus on topics/directions that suit the group’s needs.

Case Study Approach
A more concrete strategy to ensure distributed cognition and distributed problem solving within a knowledge community would be to design a specific and authentic problem to be solved by the group as a whole.  Some of my classmates have suggested the case-study method to achieve this.

Knowledge Community & Inquiry (KCI)
Another framework that comes to mind is Knowledge Community and Inquiry (KCI).  The theoretical tradition of classrooms as knowledge communities (Brown & Campione, 1996; Scardamaila & Bereiter, 1999; Hakkarainen, 2004), engages students with a sense of “collective cognitive responsibility” for continuous community knowledge advancement (Scardamalia, 2002).  KCI is a recent effort within this tradition espoused by James D. Slotta and his colleagues (e.g., Slotta & Peters, 2008; Peters & Slotta, 2010). KCI engages the students and teacher as a knowledge community, building a cooperative “knowledge base” that serves as a resource in scaffolded inquiry activities designed to target specific learning goals.  I believe KCI can be a powerful approach to focusing a knowledge community’s distributed cognition on the collaborative inquiry and problem solving.

SMART Board + Science = Situated Cognition Knowledge Community Wiki?

I recently ran a F2F workshop for elementary preservice science teachers to introduce them to SMART Boards and to get them thinking about how best to use this technology with students to enhance science teaching and learning.  As a way to organize activity centres, I created a wiki.

For 1 hour, the preservice teachers, in groups of 4, worked through 4 activity centres:  SB1, SB2, SB3, and SB4.  Each “SB” wikipage followed the “5E’s” science instructional model:  engage, explore, explain, extend, and evaluate.  This was a deliberate attempt to model how the 5E’s could be used to frame a lesson, since they would soon be learning about the 5E’s instructional model in their science education class.

I took a Piagetian approach – having students work on their own, then with a partner, and finally within a group of 4 preservice teachers.  Thus progressing from invidividual to socialized thought.  As the students worked through the tasks outlined on the various SB wikipages, they often had online videos that they could view on their own.  They were instructed to complete the “explore” tasks in pairs and also to “extend and evaluate” their new learnings by discussing within their group of 4 to connect these learnings with science teaching strategies.  “Homework” consists of adding these connections to the wikipages’ “extend and evaluate” sections, and asynchronous discussions about this may take place via the discussion forum accessible by clicking on the “Discussion” tab at the top of every wikipage.

The F2F portion of the class went extremely well.  The preservice teachers were immersed in the SMART Board material presented, and as I was dropping in on their conversations, I could tell that they were looking at these resources through the lens of science educators.  Did I succeed in situating them in context of teachers considering how best to use a technology for science education?  I think so!  They have until December 9, 2010 to complete their homework, and I’m looking forward to seeing how this community will take shape online.