Chinese Journal of Psychology 2016, Vol.58, No.2, 109-126
Category Variability Effect in Perceptual Category Learning with Auditory Stimuli
Yueh-Hsun Wu（Department of Psychology, National Chengchi University）；Lee-Xieng Yang（Research Center for Mind, Brain and Learning, National Chengchi University）
Category variability effect is referred to that the item at the mid position between two categories is more likely to be classified as the category with a larger variability. This effect is often regarded as evidence against the exemplar-based model, which would always classify the middle item as the low-variability category, due to a larger similarity between the mid-position item and that category. In contrast, the rule-based model is able to account for category variability effect, as it is sensitive to category distribution. Although category variability effect has been reported in several studies, it is still unknown under what circumstance this effect would occur, due to the diversity on methodology of the past studies. Thus, the purpose of this study is to examine in what condition, category variability effect would be induced. To this end, the stimuli adopted in this study were single tones of different frequencies, which were transferred to mel, an interval psychological scale of frequency. In Experiment 1, we examined category variability effect via giving the participants a hint or not about the difference on variability between two categories. The results showed no category variability effect, no matter a hint is given to participants or not. In Experiment 2, low-variability category was made more condensed or even having only one exemplar. The results showed a clear category variability effect in these two conditions. Also, in
Experiment 3, this effect was observed, when the high-variability category was made more diverse. To summarize our findings, an index D was developed to display the ratio on logarithmized variability between two categories. According to D, when D > 1, category variability effect occurs and disappears otherwise. Also, this index can be applied to predicting which of the past studies would find this ef fect and which would not.
Keywords: feedback learning, category learning, category variability effect