Why tutored problem solving may be better than example
Matsuda, N., Cohen, W. W., Sewall, J., Lacerda, G., & Koedinger, K. R.
(2008). Why tutored problem solving may be better than example
study: Theoretical implications from a simulated-student study. In
Proceedings of the International Conference on Intelligent Tutoring Systems.
Abstract: Is learning by solving problems better than learning
from worked-out examples? Using a machine-learning program that learns
cognitive skills from examples or by being taught, we have conducted a study
to compare three learning strategies: learning by solving problems with
feedback and hints from a tutor, learning by generalizing worked-out
examples exhaustively, and learning by generalizing worked-out examples only
for the skills that need to be generalized. The results showed that learning
by tutored problem solving outperformed other learning strategies on the
test scores that were measured on each problem solving step as the average
ratio of the correct to incorrect rule applications. The advantage of
tutored problem solving was mostly due to the error detection and correction
that was available only when skills were applied incorrectly. The current
study also suggested that learning certain kinds of conditions to apply
rules only for appropriate situations is quite difficult. That is, learning
how to perform mathematically valid operations is easier than learning
when to apply rules.
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