sme@ivax.doc.ic.ac.uk (Steve M Easterbrook) (11/01/88)
Hi. I am trying to recall the reference to a paper I read a while ago which discussed the use of analogies in learning. In particular this paper showed how different metaphors can be used to illustrate different features of the same concept. I think the example used was that of the behaviour of gas molecules, using such metaphors as crowded rooms, etc to help understand such concepts as pressure. Or it might have been the one which used an example of explaining how a variable works by comparing it to a box, amongst other things. However, I may be mixing these examples up with other papers on analogy. The reason I am trying to recall this paper is because I am studying how experts might use different abstractions of a concept when explaining it to a knowledge engineer, where the explanations at first appear to be in conflict, but the experts really agree with each other at a deep level. Any related references anyone can point me towards would be most useful. Ta. Steve
august@oahu.cs.ucla.edu (Stephanie August) (11/04/88)
In article <488@gould.doc.ic.ac.uk> sme@doc.ic.ac.uk (Steve M Easterbrook) writes: >Hi. I am trying to recall the reference to a paper I read a while ago >which discussed the use of analogies in learning. In particular this >paper showed how different metaphors can be used to illustrate different >features of the same concept. I think the example used was that of the >behaviour of gas molecules, using such metaphors as crowded rooms, etc >to help understand such concepts as pressure. The article you want is Gentner, Dedre, and Gentner, Donald R. (1983) Flowing Waters or Teeming Crowds: Mental Models of Electricity. In Dedre Gentner and Albert L. Stevens (Eds.), _Mental Models_. Hillsdale, N.J.: Lawrence Erlbaum Associates. p.99 >Or it might have been the >one which used an example of explaining how a variable works by >comparing it to a box, amongst other things. You might also be thinking of the programming examples in papers on the GRAPES simulation of John Anderson's ACT theory of learning. See: Anderson, John R. (1986) Knowledge compilation: the general learning mechanism. In R.S. Michalski, J.G. Carbonell, and T.M. Mitchell (Eds.), _Machine Learning: An Artificial Intelligence Approach_, Kaufmann, Los Altos CA. Anderson, John R., Farrell, Robert, and Sauers, Ron. (1984) Learning to Program in LISP. _Cognitive Science_, 8, 87-129. -- Stephanie E. August Computer Science Dept, UCLA <august@cs.ucla.edu>