Abstract
The hypothesis that attribute identification (AI) pretraining would reduce or eliminate rule effects in AI tasks was investigated. Ss were given 0, 4, or 8 AI problems based on the same rule prior to transfer to a final AI problem. Results indicated that familiarity with AI problems was not a key factor in eliminating rule effects in transfer. Implications for a two-component model of concept learning were discussed.
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