Embodied cognition – Representations of Knowledge
Based on diverging thoughts on my inquiry in embodied independence/dependence on technology I focused on Dr. Tim Thornton’s discussion of combined discourse of Dreyfus and Martin Heidegger that considers ‘ a reorientation of philosophical approaches to knowledge, a reorientation which places embodied practical know-how rather than disinterested context-free ‘knowledge-that’ at the heart of the analysis’ (https://sites.google.com/site/drtimthornton/courses/tacit-knowledge/dreyfus). I was drawn to look at embodied cognition as providing that ‘embodied practical know-how’.
Michael Anderson’s discussion of Embodied Cognition within the capacity of Artificial Intelligence (AI) made brought to mind our discussion in Module C on representation of Knowledge and Knowledge diffusion. Anderson notes a new approach to AI which ‘instead of emphasizing formal operations on abstract symbols, this new approach focuses attention on the fact that most real-world thinking occurs in very particular (and often very complex) environments, and is employed for very practical ends, and exploits the possibility of interaction with and manipulation of external props. It thereby foregrounds the fact that cognition is a highly embodied or situated activity’.
Three aspects stand out to me: the real and authentic design or representation of the environment (is this possible in virtual environments, the interaction with external props (a place for simulations, computers and other digital tools) and the ‘situated’ nature of that embodiment: how can that embodiment occur within technology? (second life? )
In Pranav Mistry’s Presentation of sixth sense we see an intuitive and interactive technology that reduces separation and offers a new paradigm for embodiment in technology.
Lessons from AI
AI focuses on understanding Intelligence from understanding how representations are created. I think this would be a useful method for me particularly when addressing remedial work. The central focus of higher order thinking (Bloom’s taxonomy) is also another lesson that can be transported in that there is a large focus on ‘the deployment of high-level cognitive skills such as planning and problem solving.’ These are essential skills as identified as central to mathematics and science. However on the other end Brooks, advocates studying intelligence from the bottom up, focusing on processes et al. that ‘meet our needs in, and generally coping with a given environment. p. 95
‘ From such considerations follows the perhaps reasonable, but decidedly un-Cartesian thought: “The study of that substrate may well provide constraints on how higher level thought in humans could be organized” (p. 135, emphasis in original). As we will see, this tendency to emphasize, on evolutionary grounds, the continuity between humans and other animals, and the converse willingness to see in animals instances of intelligent behavior, is an extremely important motivation for the study’ p. 95-96. How does technology fit here?
‘(C) When we examine very simple level intelligence we find that explicit representations and models of the world simply get in the way. In turns out to be better to use the world as its own model. (H) Representation is the wrong unit of abstraction in building the bulkiest parts of intelligent systems (pp. 80–81).
Dourish purports that we need “new ways of interacting with computers, ways that are better tuned to our needs and abilities” (p. 2). What are thses abilities? Do we then transport technology regardless? What of cultural models?
Anderson puts forward Dourish’s basic question as ‘how we might more fruitfully employ all this largely unused computer power [particularly give the ubiquity of technology]. More precisely, he asks which sets of human skills computing devices should be designed to exploit, for he sees the history of computing in terms of a succession of answers to this question. My question therefore is what are the social and cognitive affordances? Dourish looked at the history of AI in six eras, that are useful for education technology four past: Electrical; Symbolic; Textual; and Graphical and two, he hopes, future: Tangible and Social computing; and Embodied Interaction. I believe the latter two should be the focus on education technology.
Embodied cognition in AI is pushing for more than just mental representation but rather a repeated interaction in the environment. Given abstract concepts and lack of opportunities to always have real/situated contexts is there scope for virtual realities and for interactivity as seen within IWB use? The point noted that I still find lacking, particularly in the relevcance of the Mathematics curriculum is that of cognition being ‘ oriented toward the specific needs of a given agent.’ Thus technology that generates relevance/situational applications are paramount .
Embodied cognition (EC) also looks at the collaboratories shown in Module C and the dynamic interaction of multiple perspectives in creating EC. What of models and technology that foster collaborative discourse, exchange and creation (modification et al)?
References
Michael L. Anderson. Field Review, Embodied Cognition: A field guide http://www.agcognition.org/papers/AI_Review.pdf . Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742, USA
Dr. Tim Thornton. https://sites.google.com/site/drtimthornton/courses/tacit-knowledge/dreyfus
TEDtalksDirector .(2009, November 18). Pranav Mistry: The thrilling potential of SixthSense technology. [Video file] Retrieved from