Posts Tagged ‘semantic’

Curriculum design and a Neurosemantic taxonomy

January 20th, 2010 | By David in Brain-based learning, Instructional design | No Comments »

A team of scientists from Carnegie Mellon University has uncovered how the brain organises concrete nouns like ‘apple’ using fMRI and developed a consistent model that has major implications for how we organise information for learners (taxonomies).

Subjects heard 60 different concrete nouns whilst being imaged and a computer analysed the results looking for patterns. What they discovered were three main semantic factors underpinning the neural representation:

  1. Manipulation – how you physically interact with the object (how you hold it, kick it, twist it, etc.)
  2. Eating – how it is related to eating (biting, sipping, tasting, swallowing)
  3. Shelter – how it is related to shelter or enclosure.

Whilst the study did not examine any benefits to learning from presenting information in a form consistent with this model, it does remind me of the good old model used in learning for many years of how, what and where. I would speculate that aligning a learning taxonomy or curriculum to this model, would enhance its encoding within the brain or at the very last minimise cognitive barriers and the chance of misunderstanding or misreprsentation.

For example, if you were training learners on making coffee, one obvious curriculum would be natural sequencing, where you tackle the task in order of the steps you would actually take to make a cup of coffee. But perhaps we should be chunking the learning based on what you do with the bits of equipment, what the various qualities and tastes of different coffes are and where people like to drink/serve coffee.

Anyway, I know its all a bit speculative, but it’s really intersting to discover that our brain has a consistent, simple survival based taxonomy of its own and we should certainly be mindful of it when sequencing training. As a side note, this researchrs showed that what you were thinking from those 60 concrete nouns could also be predicted, so at least for simple conrete nouns, machine based mind reading is now a reality.

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