Biomedical subjects

Brian H Ross

Publications and source records attributed to Brian H Ross.

5 recordsLinked to original sources

PubMed2003

Category use and category learning.

Categorization models based on laboratory research focus on a narrower range of explanatory constructs than appears necessary for explaining the structure of natural categories. This mismatch is caused by the reliance on classification as the basis of laboratory studies. Category representations are formed in the process of interacting with category members. Thus, laboratory studies must explore a range of category uses. The authors review the effects of a variety of category uses on category learning. First, there is an extensive discussion contrasting classification with a predictive inference task that is formally equivalent to classification but leads to a very different pattern of learning. Then, research on the effects of problem solving, communication, and combining inference and classification is reviewed.

Classification↗

PubMed2002

Alignment effects on learning multiple, use-relevant classification systems.

People often learn multiple classification systems that are relevant to some goal or use. We compared conditions in which subclassification within a category hierarchy was predicted by values on either the same (alignable) or different (nonalignable) dimensions between category hierarchies. The results indicated that learning in alignable conditions occurred in fewer blocks and with fewer errors than did learning in nonalignable conditions. This facilitation was not the result of differences between conditions in the representations learned by the participants, the number of dimensions needed for subclassification (Experiment 1), or the objective complexity of the learning task (Experiment 2). The facilitated learning in the alignable conditions appears to reflect a commitment on the part of the learner to alignment: the belief that the structure relevant to the use of one category system will also be relevant to the use of a comparable system.

Decision Making↗

PubMed2002

The effect of category learning on sensitivity to within-category correlations.

A salient property of many categories is that they are not just sets of independent features but consist of clusters of correlated features. Although there is much evidence that people are sensitive to between-categories correlations, the evidence about within-category correlations is mixed. Two experiments tested whether the disparities might be due to different learning and test tasks. Subjects learned about categories either by classifying items or by inferring missing features of items. Their knowledge of the correlations was measured with classification, prediction, typicality, and production tests. The inference learners, but not the classification learners, showed sensitivity to the correlations, although different tests were differentially sensitive. These results reconcile some earlier disparities and provide a more complete understanding of people's sensitivities to within-category correlations.

Auditory Perception↗

PubMed2002

A further investigation of category learning by inference.

Categories are learned in many ways besides by classification, for example, by making inferences about classified items. One hypothesis is that classifications lead to the learning of features that distinguish categories, whereas inferences promote the learning of the internal structure of categories, such as the typical features. Experiment 1 included single-feature and full-feature classification tests following either classification or inference learning. Consistent with predictions, inference learners did better on the single tests but worse on the full tests. Experiment 2 further showed that inference learners, unlike classification learners, were no better at classifying items that they had seen at study compared with equally typical items they had not seen at study. Experiment 3 showed that features queried about during inference learning were classified better than ones not queried about, although even the latter features showed some learning on single-feature tests. The discussion focuses on how different types of category learning lead to different category representations.

Adult↗

PubMed2002

Learning abstract relations from using categories.

When people learn categories, the importance of the features and relations in the category representation reflects both their diagnosticity for classification and their relevance to the use of the category. In earlier work in which the influence of category use on the representation has been shown, only cases in which the features and relations were simple, observable, and very specific were examined. Learners may begin to understand the underlying similarities of category members by using the categories. In the four experiments presented here, learners applied a simple category-specific formula to category members. The test results showed that the learners had incorporated relations among features from this use, including cases in which the relations were abstract. This learning occurred even though the relations were actually not predictive of category membership but just perceived to be so as a function of the use.

Adult↗