"Incidental concept learning, feature frequency, and correlated properties": Correction to Wattenmaker.

Reports an error in "Incidental concept learning, feature frequency, and correlated properties" by William D. Wattenmaker (Journal of Experimental Psychology: Learning, Memory, and Cognition, 1993[Jan], Vol 19[1], 203-222). This article included three typographical errors in the statistics. The corrected statistics are provided in the erratum. (The following abstract of the original article appeared in record 1993-16363-001.) Four experiments examined sensitivity to feature frequencies and feature correlations as a function of intentional and incidental concept learning. Feature frequencies were encoded equally well across variations in learning strategies, and although classification decisions in both intentional and incidental conditions preserved correlated features, this sensitivity was achieved through different processes. With intentional learning, sensitivity to correlations resulted from explicit rules, whereas incidental encoding preserved correlations through a similarity-based analogical process. In incidental tasks that promoted exemplar storage, classification decisions were mediated by similarity to retrieval examples, and correlated features were indirectly preserved in this process. Results are discussed in terms of the diversity of encoding processes and representations that can occur with incidental category learning. [An erratum concerning this article appears in Journal of Experimental Psychology: Learning, Memory, and Cognition, 1993(Mar), Vol 19(2). The statistics on page 211 are corrected.] (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"Schema abstraction" in a multiple-trace memory model.

Applies a simulation model of episodic memory, MINERVA 2, to the learning of concepts, as represented by the schema-abstraction task. The model assumes that each experience produces a separate memory trace and that knowledge of abstract concepts is derived from the pool of episodic traces at the time of retrieval. A retrieval cue contacts all traces simultaneously, activating each according to its similarity to the cue, and the information retrieved from memory reflects the summed content of all activated traces responding in parallel. It is suggested that the MINERVA 2 model is able to retrieve an abstracted prototype of the category when cued with the category name and to retrieve and disambiguate a category name when cued with a category exemplar. The model successfully predicts basic findings from the schema-abstraction literature (e.g., differential forgetting of prototypes and old instances, typicality, and category size effects), including some that have been cited as evidence against exemplar theories of concepts. The model is compared with other classification models, and its implications regarding the abstraction problem are discussed. (63 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Origin of Exemplar Effects in Rule-Driven Categorization.

S. W. Allen and L. R. Brooks (1991) have shown that exemplar memory can affect categorization even when participants are provided with a classification rule. G. Regehr and L. R. Brooks (1993) argued that stimuli must be individuated for such effects to occur. In this study, the authors further analyze the conditions that yield exemplar effects in this rule application paradigm. The results of Experiments 1-3 show that interchangeable attributes, which are not part of the rule, influence categorization only when attention is explicitly drawn on them. Experiment 4 shows that exemplar effects can occur in an incidental learning condition, whether stimulus individuation is preserved or not. The authors conclude that the influence of exemplar learning in rule-driven categorization stems from the attributes specified in the rule or in the instructions, not from the stimulus gestalts. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Similarity-scaling studies of dot-pattern classification and recognition.

Classification performance in a dot-pattern, prototype-distortion paradigm (e.g., M. I. Posner and S. W. Keele, 1968) was modeled within a multidimensional scaling (MDS) framework. MDS solutions were derived for sets of dot patterns that were generated from prototypes. These MDS solutions were then used in conjunction with exemplar, prototype, and combined models to predict classification and recognition performance. Across 3 experiments, an MDS-based exemplar model accounted for the effects of several fundamental learning variables, including level of distortion of the patterns, category size, delay of transfer phase, and item frequency. Most important, the model quantitatively predicted classification probabilities for individual dot patterns in the sets, not simply general trends of performance. There was little evidence for the existence of a prototype-abstraction process that operated above and beyond pure exemplar-based generalization. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Category Representation for Classification and Feature Inference.

This research's purpose was to contrast the representations resulting from learning of the same categories by either classifying instances or inferring instance features. Prior inference learning research, particularly T. Yamauchi and A. B. Markman (1998), has suggested that feature inference learning fosters prototype representation, whereas classification learning encourages exemplar representation. Experiment 1 supported this hypothesis. Averaged and individual participant data from transfer after inference training were better fit by a prototype than by an exemplar model. However, Experiment 2, with contrasting inference learning conditions, indicated that the prototype model was mimicking a set of label-based bidirectional rules, as determined by the inference learning task demands in Experiment 1. Only the set of rules model accounted for all the inference learning conditions in these experiments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Classifying faces by race: The structure of face categories.

This article explored the finding that cross-race (CR) faces are more quickly classified by race than same race (SR) faces. T. Valentine and M. Endo (1992) modeled this effect by assuming that face categories can be explained on the basis of node activations in a multidimensional exemplar space. Therefore, variations in exemplar density between and within face categories explain both facilitated classification of CR faces and the relationship between typicality and classification RT within face categories. The present findings from classification and visual search tasks suggest that speeded classification of CR faces is instead caused by a quickly coded race feature that marks CR but not SR faces. Also, systematic manipulations of facial typicality cause no variation in classifiability aside from slowed classification of very distinctive faces. These results suggest that the exemplar model cannot explain important aspects of face classification. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Short-term memory scanning viewed as exemplar-based categorization.

Exemplar-similarity models such as the exemplar-based random walk (EBRW) model (Nosofsky & Palmeri, 1997b) were designed to provide a formal account of multidimensional classification choice probabilities and response times (RTs). At the same time, a recurring theme has been to use exemplar models to account for old–new item recognition and to explain relations between classification and recognition. However, a major gap in research is that the models have not been tested on their ability to provide a theoretical account of RTs and other aspects of performance in the classic Sternberg (1966) short-term memory-scanning paradigm, perhaps the most venerable of all recognition-RT tasks. The present research fills that gap by demonstrating that the EBRW model accounts in natural fashion for a wide variety of phenomena involving diverse forms of short-term memory scanning. The upshot is that similar cognitive operating principles may underlie the domains of multidimensional classification and short-term old–new recognition. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Rule-plus-exception model of classification learning.

Proposes a rule-plus-exception model (RULEX) of classification learning. According to RULEX, people learn to classify objects by forming simple logical rules and remembering occasional exceptions to those rules. Because the learning process in RULEX is stochastic, the model predicts that individual Ss will vary greatly in the particular rules that are formed and the exceptions that are stored. Averaged classification data are presumed to represent mixtures of these highly idiosyncratic rules and exceptions. RULEX accounts for numerous fundamental classification phenomena, including prototype and specific exemplar effects, sensitivity to correlational information, difficulty of learning linearly separable vs nonlinearly separable categories, selective attention effects, and difficulty of learning concepts with rules of differing complexity. RULEX also predicts distributions of generalization patterns observed at the individual S level. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"Selective attention and the formation of linear decision boundaries": Erratum.

Reports an error in the original article by S. C. McKinley and R. M. Nosofsky (Journal of Experimental Psychology: Human Perception & Performance, 1996[Apr], Vol 22[2], 294–317). In each row of Table 2, the Akaike's information criterion (AIC) fits for the models are in error by a roughly constant amount. (When calculating the fits, the constant portion of the log-likelihood function that enters into the AIC computation was inadvertently deleted.) The relative AIC fits of the models, the proportion of variance accounted for, as well as all conclusions based on these fits, remains the same. The corrected table appears here. (The following abstract of this article originally appeared in record 1996-03036-003.) Classification experiments were designed to compare the predictions of a linear decision bound model with those of an exemplar-similarity model incorporating an explicit selective attention mechanism. Linear boundaries could account for the data only in tasks involving separable dimension stimuli and where the boundary separating the categories was orthogonal to the psychological dimensions. Linear boundaries provided poor fits to the classification data in situations involving integral dimensions or when the boundary needed to be oriented in oblique directions in the space. The results were consistent with the selection-attention assumptions embodied in the exemplar model. It was argued that similar assumptions about selective attention need to be incorporated within decision bound models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Memory storage and retrieval processes in category learning.

Studied the detailed course of learning for categorization tasks defined by independent or contingent probability distributions over the features of category exemplars in 2 experiments with 72 college-age Ss. Ss viewed sequences of bar charts that simulated symptom patterns and responded to each chart with a recognition and a categorization judgment. Fuzzy, probabilistically defined categories were learned relatively rapidly when individual features were correlated with category assignment, more slowly when only patterns carried category information. Limits of performance were suboptimal, evidently because of capacity limitations on judgmental processes as well as limitations on memory. Categorization proved systematically related to feature and exemplar probabilities, under different circumstances, and to similarity among exemplars of categories. Unique retrieval cues for exemplar patterns facilitated recognition but entered into categorization only at retention intervals within the range of short-term memory. Findings are interpreted within the framework of a general array model that yields both exemplar-similarity and feature-frequency models as special cases and provides quantitative accounts of the course of learning in each of the categorization tasks studied. (46 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"Learning myopia: An adaptive recency effect in category learning": Correction to Jones and Sieck (2003).

Reports an error in "Learning myopia: An adaptive recency effect in category learning" by Matt Jones and Winston R. Sieck (Journal of Experimental Psychology: Learning, Memory, and Cognition, 2003[Jul], Vol 29[4], 626-640). On page 633, Table 2, the values in columns (T, P) and (P, T) in the dual condition row incorrectly read .10 and .90, respectively. The correct values are .90 and .10, respectively. (The following abstract of the original article appeared in record 2003-06626-013.) Recency effects (REs) have been well established in memory and probability learning paradigms but have received little attention in category learning research. Extant categorization models predict REs to be unaffected by learning, whereas a functional interpretation of REs, suggested by results in other domains, predicts that people are able to learn sequential dependencies and incorporate this information into their responses. These contrasting predictions were tested in 2 experiments involving a classification task in which outcome sequences were autocorrelated. Experiment 1 showed that reliance on recent outcomes adapts to the structure of the task, in contrast to models' predictions. Experiment 2 provided constraints on how sequential information is learned and suggested possible extensions to current models to account for this learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On "the science of prevention."

Comments on the article by J. D. Coie et al (see record 1994-09654-001) regarding the conceptual framework for a national research program based on the science of prevention. Although a national agenda for research into the primary prevention of mental and emotional problems is needed, it is argued that the agenda should be developed independent of a model committed to individual defect over social injustice, biogenetic causes over social learning, micro- over macrointerventions, and traditional processes over positive outcomes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Incidental concept learning, feature frequency, and correlated properties.

[Correction Notice: An erratum for this article was reported in Vol 19(2) of Journal of Experimental Psychology: Learning, Memory, and Cognition (see record 2008-10487-001). This article included three typographical errors in the statistics. The corrected statistics are provided in the erratum.] Four experiments examined sensitivity to feature frequencies and feature correlations as a function of intentional and incidental concept learning. Feature frequencies were encoded equally well across variations in learning strategies, and although classification decisions in both intentional and incidental conditions preserved correlated features, this sensitivity was achieved through different processes. With intentional learning, sensitivity to correlations resulted from explicit rules, whereas incidental encoding preserved correlations through a similarity-based analogical process. In incidental tasks that promoted exemplar storage, classification decisions were mediated by similarity to retrieval examples, and correlated features were indirectly preserved in this process. Results are discussed in terms of the diversity of encoding processes and representations that can occur with incidental category learning. [An erratum concerning this article appears in Journal of Experimental Psychology: Learning, Memory, and Cognition, 1993(Mar), Vol 19(2). The statistics on page 211 are corrected.] (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Understanding of the concept of numerically "less" by bottlenose dolphins (Tursiops truncatus).

In 2 experiments, bottlenose dolphins (Tursiops truncatus) judged the ordinal relationship between novel numerosities. The dolphins were first trained to choose the exemplar with the fewer number of items when presented with just a few specific comparisons (e.g., 2 vs. 6, 1 vs. 3, and 3 vs. 7). Generalization of this rule was then tested by presenting the dolphins with all possible pairwise comparisons between 1 and 8. The dolphins chose the exemplar with the fewer number of items at levels far above chance, showing that they could recognize and represent numerosities on an ordinal scale. Their pattern of errors was consistent with the idea of an underlying analog magnitude representation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"How good is the evidence for a production deficiency among learning disabled students?": Correction to Shepherd et al.

Reports an error in "How good is the evidence for a production deficiency among learning disabled students" by Margaret J. Shepherd, Lynn M. Gelzheiser and Roberta A. Solar (Journal of Educational Psychology, 1985[Oct], Vol 77[5], 553-561). Figures 1 and 2 (p. 557 and 559, respectively) are reversed. The captions are correct, but Figure 1 should be above the caption for Figure 2 and Figure 2 should be above the caption for Figure 1. (The following abstract of the original article appeared in record 1986-14779-001.) Investigated the spontaneous use of mnemonic strategies by learning disabled (LD) and non-LD children and adolescents to examine whether LD Ss can be distinguished from their non-LD peers on the basis of strategy use and recall. In Exp I, 105 LD and 105 non-LD 9-15 yr olds were administered a picture study/recall task, in which the strategies of interest were categorical organization during study and clustering during recall. In Exp II, 140 LD and 140 non-LD 11-17 yr olds were administered a paired-associate recall task, in which the strategy of interest was elaboration. In both studies, LD Ss earned lower mean recall scores than did the non-LD Ss. As a group, LD Ss did not differ from non-LD Ss in the use of categorical organization during study but showed less categorical clustering at recall. Fewer LD Ss used elaboration. Despite these differences, recall and strategy use were not useful predictors of classification as LD or non-LD and were only weak to moderate correlates of academic achievement. (24 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"Token" learning programs.

Emphasizes F. M. Levine and G. Fasnacht's (see record 1975-07966-001) statement that a distinction must be made between operant techniques in motivational applications vs those in learning applications. Thus, there is a difference between what clients cannot do and what they do not do. (PsycINFO Database Record (c) 2010 APA, all rights reserved)