Computer
application to error factor analysis in learning
M. Matsuda & F. Matsuda |
We
have tried to analyze error factors such as Alternation, Repetition,
Win-stay-Lose-shift, and Lose-stay-win-shift, in the single discrimination
learning. Besides application of the model has no restriction on
subjects because of no need of verbal reports of subjects and has
no limitation to number of dimensions or values of discrimination
learning, the model can be applied to maze learning or classification
learning. In order to settle one of the demerits of the model, that
is, taking time for analysis, application of electric computer to
the analysis was tried. Two kinds of FORTRAN programs were made.
One of them needs reward sequences and response sequences as data
and the other needs reward sequences and outcome sequences as data.
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