Abstract
When we trace the history of mind and learning theories we clearly see a transitioning course that traverses Cartesianism, Behaviorism, and finally Functionalism. Current advances in computer scanning technologies reinforce the view that learning should also be examined under the prism of brain-centered materialist theories. Adaptive learning systems are instructional technologies that try to minimize the mismatch between learner needs and the learning environment. Currently, they try to elicit the learner needs with performance measures but they ignore learner differences at the brain level. This paper offers a shift of viewpoint in thinking about future adaptive learning systems. If we want education to be precisely tailored to the needs of learners then instructional technologies must take advantage of known individual differences in brain processing. The paper offers the justification of such an approach, analyzes its implications, proposes an implementation model, reviews related work, and outlines future challenges.
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Keywords
- Positron Emission Tomography
- Single Photon Emission Compute Tomography
- Diffusion Tensor Imaging
- Instructional Technology
- Teaching Machine
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Karamouzis, S.T. (2006). The Use of Psychophysiological Measures for Designing Adaptive Learning Systems. In: Maglogiannis, I., Karpouzis, K., Bramer, M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2006. IFIP International Federation for Information Processing, vol 204. Springer, Boston, MA . https://doi.org/10.1007/0-387-34224-9_48
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DOI: https://doi.org/10.1007/0-387-34224-9_48
Publisher Name: Springer, Boston, MA
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