Sunday, January 22, 2006

The Coordination Class Model for Concepts

• The original coordination class model for concepts does:
o Define certain concepts at the levels of form and function
ß Allows researchers to study the “shape” and “components” of concepts
• We really like to build graphs – we can use this model to generate images(imagination!) of concepts so that we can think of them as actual things, as real objects
• This gives some justification to the concept v. misconception dichotomy a la McDermott / UW physics research – as in, if it looks like a duck … it’s a duck, and if it doesn’t look like a duck … it’s not a duck.
ß Allows researchers to study the performance of concepts
• We really like to experiment with new curriculum, and a great way to test the success of new teaching methods is to use pre- and post-tests that focus on a (relatively) limited amount of knowledge (one concept or a few related concepts)
• This gives some justification to pre- and post-test based research that indicates that dichotomous conceptual modeling doesn’t give us the whole story – there is a significant amount of “middle ground” between expert-level “CONCEPT” and novice-level “MISCONCEPTION”
o When modeling concepts as functions we can include context sensitivity as an influence on concept performance
ß Helps teachers to understand why students will provide different answers in different situations when the intent is to probe the same concept
ß Gives teachers a target for the learning process: how do we get students to recognize the same type of information in different situations? Developing and implementing curricula works best when there is a clear, understandable, and reachable goal (zone of proximal development applies even to teachers?). With that the student’s concept can perform stable read-outs of a particular “class” of information from their “causal networks” in environments that do not always provide the same quantity or quality of stimuli
o When modeling concepts as objects we can dissect concepts into discrete constituent parts
ß read-out from environment
ß causal network
ß read-out from causal network

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