Affordance as the 'what' of learning
A critique that has been levelled against affordance by some is that it is too simplistic. Oliver, for example, recognises that there exists “a tension between recognising the complexity of the concept and having a language simple enough [for it] to be useful.” (Oliver, 2005, p. 410). However whilst it is true that an affordance can be simplistic, it is not true that affordance is simplistic. It is perhaps easy to forget that the theory of affordances formed the culmination of a lifetimes work by one of the most prominent psychologists of the 20th Century. It’s adoption by multiple disciplines, and the Human Computer Interaction discipline in particular, has certainly led some to interpret it simply. Norman, for example, made the term immensely popular through his book “The Design of Everyday Things”, but as he himself has publicly acknowledged “the concept has caught on, but not always with true understanding” (Norman, 1999, p. 39). As my own research progressed, and I've become more embroiled in what it means to think in terms of affordances, so the power of the concept has become clearer to me. I've come to believe that potentially what affordances theory could provide is a general theory of what it is that is learned that could even underpin other theories of learning.
Dewey (1938) argued that individuals learn through experience, through an interaction between an individual learner and the objects and other people in their environment. He argued that the experience is what is is because of the transactions between that individual and what constitutes their environment. If affordances can be recast as transaction possibilities, as I've written in my doctoral thesis, potentially what it is therefore that individuals learn are the affordances of their environment, what transactions with the environment provide for them. Affordances become nothing less than that which is learned. Through direct experience in the environment, invariants are picked-up and their meaning is internalised through observation and interaction. What it is possible to learn is what is invariant in the world around us, and this is internalised in the form of an affordance, in terms of a transaction possibility. We are stimulated to attend to what is variant, things that change in the world, things which appear unusual make us attend to them, but it is in the attempt to understand what it is invariant about them that we actually learn something.
There may be neurobiological support for this notion. Some neurobiological research has suggested that one single biological mechanism may underlie learning in the brain, as regions of the brain previously thought to be specialised to a single task appear to be able to adapt their function (e.g. von Melchner et al, 2000; Metin, 1989). This raises the intriguing prospect that there is potentially a single algorithm that neurons and neurological structures develop according to (Ng, 2013). Affordances theory could provide a theoretical description of how this algorithm works in practice. What we can learn, on a purely conceptual level, is what is invariant in the world around us. It is this invariance, mapped through into our own brains in the form of neurophysical and neurochemical change, that may be at the heart of learning. Information pick-up through invariants, combined by the perceptual system working in an holistic manner, which is internalised in the form of an individual meaning, i.e. affordance. As these affordances build cumulatively they produce and support the complex behaviours that humans are able to develop throughout their lives.
This notion of affordance as the what of learning does not explain the how of learning, it does not explain how affordances come to be learned, how invariants in the world might lead to meaning in the individual. But an updated understanding of affordances as transaction possibilities, as outlined in my doctoral thesis, could perhaps provide a potential point of agreement between disparate groups, and as such could be a powerful aligning mechanism to bring together more complex and broader learning theories. It's certainly something I intend to pursue further, and I'm sure I'll return to in a future blog post.
Métin, C., & Frost, D. O. (1989). Visual responses of neurons in somatosensory cortex of hamsters with experimentally induced retinal projections to somatosensory thalamus. Proceedings of the National Academy of Sciences of the United States of America, 86 (1), 357-361.
Ng, A. (2013). The man behind the google brain: Andrew ng and the quest for the new AI. Http://www.wired.com/2013/05/neuro-artificial-intelligence.
Norman, D. A. (1988). The Psychology Of Everyday Things. New York: Basic Books.
Oliver, M. (2005). The problem with affordance. E-Learning, 2 (4), 402-413.
von Melchner, L., Pallas, S. L., & Sur, M. (2000). Visual behaviour mediated by retinal projections directed to the auditory pathway. Nature, 404 (6780), 871-876.
Dewey (1938) argued that individuals learn through experience, through an interaction between an individual learner and the objects and other people in their environment. He argued that the experience is what is is because of the transactions between that individual and what constitutes their environment. If affordances can be recast as transaction possibilities, as I've written in my doctoral thesis, potentially what it is therefore that individuals learn are the affordances of their environment, what transactions with the environment provide for them. Affordances become nothing less than that which is learned. Through direct experience in the environment, invariants are picked-up and their meaning is internalised through observation and interaction. What it is possible to learn is what is invariant in the world around us, and this is internalised in the form of an affordance, in terms of a transaction possibility. We are stimulated to attend to what is variant, things that change in the world, things which appear unusual make us attend to them, but it is in the attempt to understand what it is invariant about them that we actually learn something.
There may be neurobiological support for this notion. Some neurobiological research has suggested that one single biological mechanism may underlie learning in the brain, as regions of the brain previously thought to be specialised to a single task appear to be able to adapt their function (e.g. von Melchner et al, 2000; Metin, 1989). This raises the intriguing prospect that there is potentially a single algorithm that neurons and neurological structures develop according to (Ng, 2013). Affordances theory could provide a theoretical description of how this algorithm works in practice. What we can learn, on a purely conceptual level, is what is invariant in the world around us. It is this invariance, mapped through into our own brains in the form of neurophysical and neurochemical change, that may be at the heart of learning. Information pick-up through invariants, combined by the perceptual system working in an holistic manner, which is internalised in the form of an individual meaning, i.e. affordance. As these affordances build cumulatively they produce and support the complex behaviours that humans are able to develop throughout their lives.This notion of affordance as the what of learning does not explain the how of learning, it does not explain how affordances come to be learned, how invariants in the world might lead to meaning in the individual. But an updated understanding of affordances as transaction possibilities, as outlined in my doctoral thesis, could perhaps provide a potential point of agreement between disparate groups, and as such could be a powerful aligning mechanism to bring together more complex and broader learning theories. It's certainly something I intend to pursue further, and I'm sure I'll return to in a future blog post.
References
Dewey, J. (1938). Experience and education. New York, NY: Kappa Delta Pi.Métin, C., & Frost, D. O. (1989). Visual responses of neurons in somatosensory cortex of hamsters with experimentally induced retinal projections to somatosensory thalamus. Proceedings of the National Academy of Sciences of the United States of America, 86 (1), 357-361.
Ng, A. (2013). The man behind the google brain: Andrew ng and the quest for the new AI. Http://www.wired.com/2013/05/neuro-artificial-intelligence.
Norman, D. A. (1988). The Psychology Of Everyday Things. New York: Basic Books.
Oliver, M. (2005). The problem with affordance. E-Learning, 2 (4), 402-413.
von Melchner, L., Pallas, S. L., & Sur, M. (2000). Visual behaviour mediated by retinal projections directed to the auditory pathway. Nature, 404 (6780), 871-876.
Comments
Post a Comment