Learning the correlational structure of stimuli in a one-attribute classification task
In category learning experiments, participants typically do not learn within-category correlations unless the composition of the categories or the task demands compel them to do so. To determine if correlations among attributes could be learned without explicitly focusing the participants' attention on them, a task was designed that allowed stimuli to be classified on the basis of a single perfectly predictive attribute. Each training stimulus also included attributes that were either perfectly or partly correlated with the rule attribute. Then, in a test phase, the impact of eliminating the rule attribute on classification was evaluated. The experiment showed that some of the attributes that were perfectly correlated with the rule attribute were learned. These attributes could be used to classify the test exemplars even though the rule attribute had been removed. This experiment provides evidence that within-category correlations can be learned incidentally during classification tasks.
|Journal||European Journal of Cognitive Psychology|
Giguère, G. (Gyslain), Lacroix, G, & Larochelle, S. (Serge). (2007). Learning the correlational structure of stimuli in a one-attribute classification task. European Journal of Cognitive Psychology, 19(3), 457–469. doi:10.1080/09541440600926716