Category Archives: Bereiter

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).

References
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: http://www.ikit.org/fulltext/1997situated.pdf

Preparing Students for the 21st Century Knowledge Age

If this is what life is going to be like in 2019, what skills do today’s students need to be successful in the Knowledge Society?  How can we help them develop these skills?

Readings
Lately, I’ve been reading about Knowledge Building and Online Communities:
One can look up all the various 21st Century Skills projects to see a list of skills, which commonly include creativity, digital literacy, critical thinking, and problem solving:
Teacher A, B, and C (Scardamalia & Bereiter)
Dr. Marlene Scardamalia and Dr. Carl Bereiter, founders of the Institute for Knowledge Innovation and Technology at OISE / University of Toronto, maintain that schools need to adopt a culture of collaborative knowledge building if they are to prepare our society for the Knowledge Age.  Whereas traditional schools adhered to what they call a “Teacher A model” – teaching reduced to tasks and activities; I find that much of our current schooling adheres to what they have termed the “Teacher B model” – a focus on learning objectives/outcomes/expectations with students’ responsibility directed at tasks and activities, and the teacher taking on the cognitive responsibility.  The education utopia Scardamalia and Bereiter espouse is the “Teacher C model“.  In this model, strategic cognitive activity is turned over to the students.  Whereas Teachers A and B roles resembled that of “Engineer”, Teacher C does what Teacher B does – but with the added “objective of turning more of the learning process over to the students” (Bereiter, 2002; Ch. 8, p. 39).
Collective Cognitive Responsibility (Scardamalia, 2002)
Scardamalia defines Collective Cognitive Responsibility as the condition when learners “take responsibility for knowing what needs to be known and for insuring that others know what needs to be known” (2002, p. 2).  She and Bereiter assert that schools actually withhold cognitive responsibility when they operate on a Teacher A and/or Teacher B model.  They espouse that engaging a class in collaborative knowledge building, particularly in an online discussion forum such as Knowledge Forum, effectively enculturates students into the collective cognitive responsibility of their community knowledge.  Scardamalia goes on to elaborate on her 12 Knowledge Building principles (2002, p. 9-12), the basic building blocks of Knowledge Building (KB) pedagogy:
  1. Real ideas, authentic problems
  2. Improvable ideas
  3. Idea diversity
  4. Rise above
  5. Epistemic agency
  6. Community knowledge, collective responsibility
  7. Democratizing knowledge
  8. Symmetric knowledge advancement
  9. Pervasive knowledge building
  10. Constructive uses of authoritative sources
  11. Knowledge building discourse
  12. Embedded and transformative assessment
The following have been my KB-related learning goals since I first learned about KB 10 years ago at OISE (Master’s work):
  • how to implement KB in a publicly-funded classroom
  • possible modifications to the pure form of KB for realistic classroom implementation
  • how to recognize true KB
  • how to foster true KB in the classroom, given the realities of the publicly-funded classroom
My classmate, Kyungmee, writes:  “Moreover, according to Scardamalia (2002)’s paper, knowledge creation processes are basically CHANCY. ‘… knowledge creation depends on chancy processes of discovery and invention.’  Then, how to define knowledge creation processes? Is there any particular steps or conditions? If not, how teacher can try to teach or provide students knowledge building opportunities?”
I have been wrestling with this very question since I first learned of constructivist knowledge building at OISE 10 years ago!  I find that the concept of KB is far too open and abstract to be implemented in its pure form – especially if KB is to be implemented in public schools which are mandated to follow provincial curriculum expectations.
I did a pilot project in a few schools at my school board where I tried to add some structure to KB – a compromise between KB and the realities of time and curricular constraints that public school teachers face.  Teachers chose a curricular area to address, in which their students would begin the unit using the inquiry process infused with face-to-face (f2f) KB cross talks and virtual KB Knowledge Forum discussion.  We used Wiggins & McTighe’s Understanding By Design framework to co-design and backward map a curricular unit.  To satisfy current provincial assessment and evaluation policy which states that summative evaluation can only be of a product, students were then required to create a final flashy ICT-infused project to demonstrate their learning.
I’m sure Bereiter and Scardamalia would cringe at the way I chose to go about implementing KB in these pilot classrooms, but I had to start with where the teachers were at, while considering the realities of policy and classroom constraints that these teachers face.
Systemic Changes Needed for Knowledge Building in Ontario
I see 2 systemic changes necessary for authentic KB implementation in the classroom and Teacher C-ism:
  1. Provincial Assessment and Evaluation (A & E) policies must recognize that Knowledge Building (KB) and collaboration skills can and should be measured, evaluated, and reported upon.  As per Bereiter, A & E policy should recognize that KB is productive work, IS learning, and is a necessary skill for success in the knowledge society.
  2. To avoid Teacher B-ism (a focus on learning goals), is not, in my opinion, a realistic endeavour given our provincially mandated curriculum.  To get rid of a mandated curriculum is unrealistic as well, because I do think that a society should have a certain baseline of common knowledge in order to function cohesively.  However, might there be some sort of a compromise, where provincially mandated learning expectations exist, but does not drive education?  How might a “Teacher B.C” model work?

While it is nice to dream up how we might make systemic and policy changes, I am more interested in how we can make KB work within our existing reality.  Anyone have any other suggestions for implementing KB in classrooms?

Assessment of Knowledge Building
Page 31 of the Ministry of Education’s 2010 Growing Success document on assessment and evaluation (A & E) has a nice summary table of assessment for/of/as learning.
I would agree that assessment as learning (a.k.a. formative assessment) is key in helping students develop their collaborative knowledge building skills, as well as developing their metacognition of this.  It is unfortunate that under current A & E policy, formative assessment is not something that can be quantified and reported upon formally on a student report card.  Since Scardamalia and Bereiter emphasize the importance of these skills for success in the knowledge society, I think it is problematic that this is not addressed in the report card.
Page 11 of the Growing Success document defines “learning skills work habits”, and are part of the student report card.  I think that the Ontario report card should also have a “Collaborative Knowledge Construction” section, much like the Learning Skills section, in which various component skills related to collaborative knowledge building are listed, and teachers may assign qualitative “grades” to each skill.
My classmate, Vincent A. asks:  “How can educators effectively and authentically assess knowledge building, especially if there is no final tangible product?”
I’m quite sure that Scardamalia and Bereiter would disagree that “there is no final tangible product” in knowledge building.  As a member of a knowledge building community, once you put forth an idea, that idea becomes an artifact – its own entity, and belongs to the community collective (not to the person who contributed the idea).  In other words, the community collective is made up of tangible ideas.  The final tangible product would be the community’s Rise Above.
Knowledge Building in Wikis?
I like the idea of a class/group wiki.  Though I’m not sure about 2 things:
  1. Is there community knowledge building occurring, and if so, how might we track it?  I ask this because a wiki is usually a piece of work that demonstrates a group/community’s understandings.  It doesn’t actually show the discussion around it (unless the students use the discussion forum within the wiki), and hence, we can’t see the conjectures, the theorizing, etc.  We just see the factual information that the group has come up with via various resources.
  2. How do we assess wiki work?  Provincial A & E policy states that we can only evaluate students on an individual basis, not on a group-by-group basis.  So how do we evaluate individual students’ wiki work?  Going back and analyzing various iterations of wiki pages for each student is tedious and unrealistic.  Is there a better way?  How do you evaluate this?
Another Way for Knowledge Building Communities to Use Wikis
Prof. James Slotta of OISE (my PhD supervisor) has created a framework called Knowledge Community and Inquiry (KCI), in which groups of students work within a science inquiry model and contribute to a community wiki, then are challenged to solve an authentic problem in which they use the wiki as a resource to do so.