- Just like last week, this week we focused on understanding cognitive architecture. To summarize the discussion, cognitive architecture is a theory and we can claim that a system has cognitive architecture if it can behave like a human mind.
- The article considers learning to be on a continuum with novice learners being on the left side of the spectrum and experts on the right side.
- When we presented with a new set of information, it first goes in our working memory which is short term and has relatively smaller storage capacity. Adding more information in the working memory causes cognitive overload which results in low level learning/understanding of the concepts.
- In order to truly understand how ‘learning’ and ‘understanding’ takes place and how a learner can shift from the left side of the continuum to the right side, we need to look at the level of interactivity. Whenever we are introduced with a new set of information, if it has high interactive elements then the working memory will not be able to process it properly. The ideal situation would be to look at the information in isolated and non-interactive manner first.
- Schemas were also discussed at length because it is due to schemas the cognitive load on the working memory is decreased. If there are proper schemas built then the mind can process information rapidly in the working memory even if the information has high interactive elements.
- Transfer of knowledge is also very important because if a learner is able to efficiently transfer his learning in different settings, then it shows that there are central executives formed in his/her long term memory.
- If the information is new, then there will be fewer schemas available in the memory due to which a learner might find it difficult to understand the concept.
- Expertise is dependent upon automation, which implies that a learner can process information without causing cognitive overload in the working memory.
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