Category Archives: Situated Cognition

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

Knowledge, Mind, and Assessment

What is Knowledge?
Knowledge is socially negotiated, situated, and distributed.  It is what Sir Karl Popper would term a “World 3” artifact, it’s own entity, taking on a form of its own (what Scardamalia and Bereiter would call a “conceptual artifact”) within a knowledge community.

Knowledge is situated in the sense that concepts are situated within the context of the surrounding environment, and these concepts are progressively developed.  It is a product of the activity, context and culture in which it is learned and used.  Conceptual knowledge as a tool is only fully understood through its use.  Furthermore, its use changes the user’s world view, causing the user to adopt the belief system of the culture in which the conceptual knowledge tool is used (Brown, Collins, and Duguid; 1989).  Brown, et al. (1989) propose a “cognitive apprenticeship” model of education, which promotes learning through activity, tool, and culture.  Cognitive apprenticeship is supported by collaborative social interaction and social construction of knowledge.  It honours the situated nature of knowledge, embeds learning in activity, and makes deliberate use of the social and physical context.

Bereiter (1997) argues for the value of overcoming situatedness of cognitionby creating World 3 knowledge objects that are transferrable across different situations.  He points out that the problem with situatedness of cognition is that as one learns more about a phenomenon, one knows increasingly more about the phenomenon as framed within that situation, making this knowledge less likely to be generalizable to other situational contexts.  Furthermore, treating all knowledge as situated would make knowledge objects invisible.  Bereiter (1997) calls us to treat ideas as “objects of inquiry” (p. 18), requiring “Disciplined movement back and forth between (Popper’s) World 1 (the physical world) and World 3 (immaterial world of knowledge and abstract objects)” (p. 18), yielding the “hypothetico-deductive method” and endless possibility for theory development, problem solving, and design.  Incidentally, Sir Karl Popper’s philosophy of knowledge is based on his proposition of 3 worlds:

  1. World 1 – the physical world
  2. World 2 – the world of the mind (mental states, ideas, perceptions)
  3. World 3 – the immaterial world that is the product of the human mind (e.g. the concepts and ideas represented or expressed by books, papers, paintings, symphonies; but not physical books, papers, or paintings themselves)
What is Mind?  Where Does Knowledge Reside?
Sebastian Seung of MIT discusses his theory of mind:  “I Am My Connectome” at a TED Talk (July, 2010):

Nueroscientists since the 19th century have hypothesized that one’s memories, personality, and/or intellect also reside in the connections between one’s neurons.  This would imply that knowledge resides in our neural connections.  These connections form what Seung calls one’s “connectome“.  According to Seung, neural activity encodes our thoughts, feelings, and mental perceptions; but neural activity can also cause our own neural connections to change (hence changing our connectome).  Conversely, our experiences can change our connectome.  Thinking can change one’s connectome.  Neural activity constantly changes in our brain, but it is the brain’s neural connections (which make up the brain’s neural network) that determine the pathways along which this neural activity flows.  These neural pathways as a whole is the connectome.  The Seung Lab at MIT seeks to read memories from connectomes, and Seung is leading the new field of connectomics to test these hypotheses.

As I consider both Bereiter and Seung’s theories of mind, I see the one commonality is that they both see knowledge as residing in connections and composed of networks of connections.  In Seung’s case, these connections are of a physiological nature residing in the human brain.  In Bereiter’s case, these connections are conceptual in nature, residing in World 2 and World 3; with collaborative knowledge building as the vehicle by which individual learner’s conceptual connections combine and build upon those of other learners in the creation of a World 3 knowledge object.

The Nature of Knowledge:  Implications on Assessment
Bereiter (1997) points out that situativity theorists have not advanced any educational ideas due in part to their failure to define the purpose of education and to their confusion between process and product.  The collaborative knowledge building that I have witnessed in my experience as a graduate student, classroom teacher, and instructional leader aligns with Bereiter’s assertion that “knowledge implicit in the process” (p. 23) should be distinguished from “knowledge that is the product of the process” (p. 23); and yet, this distinction is not recognized in K-12 classroom practice, curriculum policy, or assessment and evaluation policy.  Our education system is still misguidedly preoccupied with learning goals and the embodiment of knowledge in the form of reports and presentations, failing to see knowledge taking a form that can be worked with or even packaged and sold (Bereiter, 1997).  This is decidedly antiquated thinking, considering our knowledge society’s wealth will come from knowledge work – no longer from manufacturing as in the industrial society of old.  “What distinguishes knowledge work is not using knowledge by creating or adding value to it” (Bereiter, 1997: p. 23).  This is not to say that we should do away with learning goals, merely that the focus should shift from these to learning for deeper understanding and the construction of knowledge through collaborative means supported by technology.

Hutchins and his colleagues developed the distributed cognition approach in the 1980s as a way of understanding collaborative work practices, or “cognitive systems” – complex interactions between multiple people, artifacts to perform an activity, and technological systems (Rogers, 2006).  There are two levels of analysis:  (1) analysis of ‘the propagation of representational state across media’ and (2) analysis of human interactions (i.e. the problems, the breakdowns, distributed problem-solving, role of non/verbal behaviour, coordinating mechanisms, communication during collaboration, knowledge sharing/accessibility).

While I can see the value of having a distributed cognition framework with which to study the dynamics of collaborative work, I find that this approach emphasizes the interactions enacted to complete the task, and does little to examine closely how ideas/memes/theories evolve within and among a community.  Furthermore, the distributed cognition approach does not seem recognize knowledge as its own entity, as a ‘product’.  Rather, it acknowledges knowledge as a process but focuses on the knowledge community’s development of that process, not on the conceptual evolutionary process of knowledge in its own right.

This is especially problematic when one considers Carl Bereiter’s (2002) contentions that that the mind is not a container, knowledge and conceptual artifacts do not reside in learners’ minds,  and that the mind does not reside in the head of a person, nor does it necessarily reside within one person.  For Bereiter, knowledge objects and conceptual artifacts belong to World 3.

If distributed cognition analysis of a knowledge community can be used in such a way as to reveal how the community’s mind/cognition is distributed among the community, and hence, trace how the conceptual development of knowledge as a conceptual artifact is gradually constructed within the community; then distributed cognition could be a powerful approach to prove Bereiter’s theory of mind, and aid in the classroom assessment of collaborative knowledge building in asynchronous online environments.

In this regard, Activity Theory (Hew & Cheung, 2003), developed by Alexei N. Leont’ev and Sergei Rubinshtien, seems more promising.  Based on the premise that tools mediate between subject and object processes, rules mediate between subject and community processes, and roles mediate between community and object processes; one can use this framework to analyze several combinations of any three processes as illustrated by any three edges of the following triangles:

If the basis of our knowledge society’s economy is going to be knowledge work, then it stands to reason that schools must teach learners to be proficient knowledge workers.  Assessment is vital to this learning process, for teachers and learners alike.  Applying Gunawardena et al’s (1997) 5 phases of active knowledge construction and Henri’s (1992) 5 types of critical thinking (Hew & Cheung, 2003) to assess individual and community knowledge construction would be very useful in this regard.  In addition to being good knowledge workers, today’s learners will need to become excellent collaborators as well.  With this in mind, it would be helpful to apply Rourke et al’s (1999) 3 constructs of social presence and affective responses (Hew & Cheung, 2003) to assess social presence, and to apply Kirkley et al’s (1998) 7 means of moderator assistance (Hew & Cheung, 2003) to assess facilitation skills – or what I like to call “cognitive leadership” skills.  Of course, I do not mean to suggest that we implement the above mentioned frameworks in their pure form, but rather to reform our current assessment and evaluation policies and practices based upon a combination of these frameworks.

References:
Bereiter, C. (2002). Education and Mind in the Knowledge Age. Mahwah, NJ: Lawrence Erlbaum Associates. Online: https://portal.utoronto.ca/bbcswebdav/xid-1113981_1

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

Brown, A. L., & Campione, J. C. (1996). Communities of Learning and Thinking, or a Context By Any Other Name. Contemporary Issues in Teaching and Learning, 120-126.

Brown, J. S., Collins, A. & Duguid, P. Situated Cognition and the Culture of Learning (1989). Educational Researcher, Vol 18(1), 32-42  Available at:
https://portal.utoronto.ca/bbcswebdav/users/brettcla/Course%20readings/BrownDuguid.pdf

Cole, M. & Wertsch, J. V. (1996).  Beyond the Individual-Social Antimony in Discussions of Piaget and Vygotsky.  Online: http://www.massey.ac.nz/~alock/virtual/colevyg.htm

Hew, K. F. & Cheung, W. S. (2003). Models to evaluate online learning communities of asynchronous discussion forums. Australian Journal of Educational Technology 2003, 19(2), 241-259. Online: http://www.ascilite.org.au/ajet/ajet19/hew.html

Hung, D. & Chen, D. T. (2001). Situated Cognition, Vygotskian Thought, and Learning from the Communities of Practice Perspective: Implications for the design of Web-based E-Learning.  Educational Media Internaitonal, 38(1), 3-12. Online: https://portal.utoronto.ca/bbcswebdav/users/brettcla/Course%20readings/SitCogWebDesign.pdf

Lave, J., & Wenger, E. (1990). Chapter 1 in Situated Learning: Legitimate Peripheral Participation. Cambridge, UK: Cambridge University Press. Online: https://portal.utoronto.ca/bbcswebdav/users/brettcla/Course%20readings/LaveLPP.pdf

Vygotsky, L. (1934) 2. Piaget’s Theory Child Language and Thought.  Online:  http://www.marxists.org/archive/vygotsky/works/words/ch02.htm

Rogers, Y. (2006) Distributed Cognition and Communication. In The Encyclopedia of Language and Linguistics 2nd Edition. Edited by Keith Brown Elsevier: Oxford. 181-202. Online: http://research.oise.utoronto.ca/~jhewitt/okc/UploadedFiles/dbii97/4/RogersDistrCog.pdf

Russell, R. (?). Experience based learning theories.  The Informal Learning Review. Online: http://www.informallearning.com/archive/1999-0304-a.htm

Scardamalia, M. (2002). Collective Cognitive Responsibility for the Advancement of Knowledge. Liberal Education in a Knowledge Society, 67-98.

Scardamalia, M. (2000). Social and Technological Innovations for a Knowledge Society. In S. S-C. Young, J. Greer, H. Maurer, & Y.S. Chee (Eds.). Proceedings of the ICCE/ICCAI 2000: Volume 1. Learning Societies in the New Millennium: Creativity, Caring & Commitments. (pp. 22-27). National Tsing Hua University, Taiwan: Taipei. Online: https://portal.utoronto.ca/bbcswebdav/xid-1113975_1

Scardamalia, M., & Bereiter, C. (1996). Student Communities for the Advancement of Knowledge. Communications of the ACM, 39(4), 36-37.

Smith, M.K. (2002). ‘Jerome S. Bruner and the process of education’, the Encyclopedia of Informal Education. Online: http://www.infed.org/thinkers/bruner.htm

Video Games & Augmented Reality As Situated Learning Spaces

Quest To Learn is a 1-year old public middle school in New York City based on a curriculum of educational video gaming and digital media.

“Games as learning spaces” – learning at Quest to Learn is structured in a game-like way. Students modify and create video games to demonstrate their learning, and assume defined roles during this process. “Systems thinking” is the theoretical framework on which the school’s methodology is based.

As I ponder about situated cognition (i.e. learning is inseparable from doing), it seems to me that educational video gaming and creation is the ultimate situatedness for learners – short of immersing them in real domain under study!  What I find particularly interesting, is that these students are potentially simultaneously being immersed in 2 cultures – the culture of the subject area content which the video game addresses, and the culture of gamers and gamer creators.  Thus achieving “double situatedness” (if these is such a term)!

My classmate, Jillian A. writes:  “The theory of legitimate peripheral participation (LPP) states that  a newcomer to a community plays an authentic role (or set of roles) on the ‘periphery’ of community activity, participating ‘in the actual practice of an  expert, but only to a limited degree and with limited responsibility for the ultimate  product as a whole’ (Lave & Wenger, 1990; p. 14)”.  So while these learners may be on the periphery of the subject matter community for which they are creating their video games, their game modification and creation processes place them at the very centre of the gaming community.

Dr. Jennifer Jenson and Dr. Suzanne de Castell have done a lot of research on educational gaming.  Recalling a paper I read of theirs last year, I remember their distinction between “as if” and “just like”.  I believe they were arguing that while simulations gave learners an experience “as if” they were completing an authentic task in a given subject domain, educational video games could give learners an experience “just like” they were doing the real thing.  The “just like” experience was deemed a more effective learning experience.  I’ll have to dig up that paper…

An incredible development in the gaming world – Project Natal’s “Milo” – has exciting implications for further and deeper situatedness that promises to blur the line between the virtual and real world:

Pranav Mistry of MIT has created SixthSense technology, using gestures and digital media to further blur the distinction between the physical and the virtual world:

If situatedness closely approximates reality, would this necessarily lead to deeper and more meaningful learning? Why or why not?

I will continue to think about this.  My initial thoughts are 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.  This may be due to a heightened sensory experience afforded by the technology contributing to the realism of the learning context.

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.

Piaget, Vygotsky, Situated Cognition Vs. Mitra’s SOLE & Granny Clouds

I’ve been reading about social and cultural influences on learning, as well as Situated Learning:

Piaget, Vygotsky, Situated Cognition
Where Piaget asserted that children developed from the individual to the socialized (i.e. nonverbal autistic thought –> egocentric thought & speech –> logical thinking & socialized speech), Vygotsky argued that children developed from the socialized to the individual (i.e. social –> egocentric –> inner speech).

In situated cognition theory, activity and situations are integral to cognition and learning.

Vygotsky’s developmental theory and Situated Cognition theory can indeed work in tandem!  These theories imply that:

  1. Learners need to be situated within a collaborative learning context so they may co-investigate socially, eventually leading to internalized learning for each individual.
  2. These co-investigation activities must be authentic tasks, situated within the context of the subject domain of study, such that learners see themselves as practitioners of that domain.

Both #1 & #2 can be done face-to-face (F2F) or online, but I always think that a blended model (e.g., F2F + online) works best.

Mitra’s SOLE and Granny Clouds
Having read about Piaget and Vygotsky’s somewhat opposite theories of child development, it has made me give more thought to Sugata Mitra’s TED talk about The Child-Driven Education:

The idea that children will collaboratively learn with digital tools they’ve never used, heard of, or seen before; inspite of purposeful lack of instruction and scaffolding – is evidence to me that collaborative learning is natural to the human condition.  This is incredibly profound!  Furthermore, Sugata Mitra’s work seems to support Vygotsky’s developmental theory, rather than Piaget’s; as it seems that the children in his studies developed their skills and knowledge socially before the new knowledge became internalized within each individual child.

In his TED talk, Mitra mentions 2 quotes from Sir Arthur Charles Clarke, that I find very profound:
“A teacher that can be replaced by a machine, should be.”
“If children have interest, then education happens.”

The second half of this TED talk is particularly intriguing.  Sugata Mitra’s work on Self Organizing Learning Environments (SOLE) and the Granny Cloud.  He informally organized children into small groups and gave each group a set of questions, as well as the freedom to access the internet with 1 laptop,  discuss amongst their group, drop in on other groups, and no other scaffolding.  He’s found that such informal groupings and vague scaffolding sets the stage for children to self-organize as a learning community, producing deep learning.  His Granny Cloud work involved 200 volunteer English grandmothers who regularly taught English to children in India via Skype.

Mitra Vs. Situated Cognition
Mitra’s SOLE work is in sharp contrast to my classmates’ (Scott J.’s KEC note #1286 and Chad L.’s KEC note #1310) and my own thinking (KEC note #1404), that collaboration skills need to be explicitly taught.  In Mitra’s SOLE work, this is clearly not the case!  Is it possible, that by explicitly teaching collaboration, we stifle the degree to which children can collaborate effectively and learn deeply?  It also interesting to note the absence of any situatedness in Mitra’s SOLE work.  In fact, all of the learning tasks that he presented to various populations of children in various countries (India, Italy, England) were intentionally out of context and in some cases, not even in a language that the children knew!  Perhaps then, situated cognition is not a necessary component of effective/deep learning, merely an enhancing component?

Mitra’s speculation:  “Education is a self organising system, where learning is an emergent phenomenon…”.  He estimates that it will take 5 years and under $1 million to prove this experimentally, and that’s what he intends to do.  Mitra’s theory is a direct contradiction to Brown, Collins, and Duguid’s “cognitive apprenticeship” model (1989), where learning is embedded in activity and deliberate use is made of the social and physical context to immerse learners in the culture of the knowledge domain under study.  The one idea that Mitra’s work and the Cognitive Apprenticeship model have in common is that learning is supported by collaborative social interaction and social construction of knowledge.  As previously noted, Mitra’s work also contradicts the notion of “situated cognition“, in which activity and situations are integral to cognition and learning.

So who’s right?  There seems to be supporting evidence for all arguments!  Perhaps it’s a question of efficiency.  If we leave learners to collaboratively self-organize, they will learn deeply if given enough time.  If we situate (via cognitive apprenticeship) and scaffold learners’ collaborative learning, they will learn deeply, perhaps in less time?

Finally, Mitra emphasizes that the future of educational change is “A question of attitude, not technology”, and breaks down “The Arithmetic of Change” for us:
1 billion children
100 million mediators
10 million SOLEs
$180 billion
10 years

This indeed is an exciting and optimistic outlook for education!  Perhaps there is hope yet of rocketing the education dinosaur into the 21st century…

Note:  Sugata Mitra’s papers regarding the studies he mentioned in his TED talk can be found here (UTORid needed).