Abstract:

Previous researches have showed that category learning by inference way can represent diagnostic information and nondiagnostic information, but learning by classifying way only can represent diagnostic information such as exemplar features information. However, recently studies show that learning partial exemplars by classifying also can represent nondiagnostic information (Taylor & Ross, 2009). Taylor & Ross (2009) offered an explanation of selective attention that there are comparably loose of attention resources in partial condition than entire condition. They left out the possibility that the subject might inference the missing features in the partial condition. In the real world, exemplars often appear with occluded features, but in laboratory research, they are almost always presented in their entirety. Two experiments were conducted to explore how partial classification leads to nondiagnostic features learning. Experiment 1 replicated the Taylor & Ross (2009) finding that learners who classified exemplars with missing features (the partial condition) processed nondiagnostic features. Experiment 2 explored how partial exemplars of classification learning could represent nondiagnostic (prototypical) information. Linearly separable category structures were used in this study. Experiment 1 used the “6 dimensions category” and experiment 2 used the “7 and 5 dimensions category”. During learning phase, an individual exemplar was presented, the participant was asked to infer and indicate which category (Deeger or Koozle) the exemplar belonged to, and feedback as to whether the subject was right or wrong was provided. After a number of such trials of inference and feedback, participants reached the learning criterion and were considered to have formed new category knowledge. During the transfer phase, different prototypical and diagnostic exemplars were presented, the participant was asked to estimate their categorical typicality. Experiment 1 replicate the finding of Taylor & Ross (2009) that the entire and the partial conditions both can represent diagnostic information, but only the partial condition can represent prototypical information. In other word, the entire condition only can represent diagnostic information, but partial condition not only can represent diagnostic information but also nondiagnostic information. The results of experiment 2 support the previous prediction that subject inference the missing features automatically but not adjust their attention in the partial learning condition.

Key words: category learning, classification learning, inference learning, diagnostic information, prototypical information