Memory for individual events in concept identification

Bourne, Lyle E.; O'Banion, Katy

doi:10.3758/bf03336642

Cited by 16 publications

(11 citation statements)

References 2 publications

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“…However, the probability of recall of the first instance is 0.68 for both initial true and false hypotheses and this is the most frequently recalled instance for both types of hypotheses. Examination of these data shows a clear serial position curve with both primacy and recency effects in recall, which confirms the estimations of Levine (1969), Trabasso and Bower (1964), and Bourne and O'Banion (1969). Partial support is also obtained for Williams's (1971) model from an analysiswhich shows that a number of instances are incompletely recalled such that an attribute value is changed from the original instance selected.…”

Section: Discussionsupporting

confidence: 68%

“…Although complete TAPLIN agreement on the role of memory has not been reached, recent investigations (e.g., Levine, 1969) suggest that, while the S's hypothesis is never perfectly consistent with any previous trial, greatest consistency occurs with the first stimulus presented (i.e., primacy effect) and with the trial immediately prior to the hypothesis (i.e., recency effect). Trabasso and Bower (1964) and Bourne and O'Banion (1969) have also obtained evidence of primacy and recency effects in the immediate recall of st imuli and associated feedback. In the latter experiment, however, recall was only slightly better than chance.…”

Section: Experiments IImentioning

confidence: 99%

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Evaluation of hypotheses in concept identification

Taplin

1975

Memory & Cognition

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The aim of this paper is to investigate the nature of hypothesis evaluation in conceptual tasks, especially in the identification of bidimensional concepts. In such tasks, hypothesis testing is seen as being composed of sampling and evaluation stages. With complex problems only one hypothesis seems likely to be sampled on each trial, and it is suggested that this hypothesis is evaluated according to a statistical decision-making process. In Experiment I, Ss were given an initial hypothesis involving one of eight rules and required to test it in an attempt to find a concept. When this given hypothesis was true (i.e., the concept), no difference was found between rules for the number of instances selected to the criterion of solution. Moreover, there was a tendency for Ss to choose instances which were predicted to be positive according to the hypothesis under test. Experiment II examined the role of memory in hypothesis testing. Immediate recall of instances selected revealed no difference between true and false hypotheses. Both primacy and recency effects were evident in recall. The number of instances correctly recalled was more than expected by models of hypothesis sampling and evaluation, and this was attributed to Ss having a low criterion for recall without intrusions. Examination of intrusions suggested that Ss may have retained some, but not all, of the features of the stimuli selected. Some differences were found between rules and between positive and netative instances on recall. These effects werẽ uggested to be due to different amounts of information processing when classifying each type of Instance for each rule; the results of Experiment III supported this suggestion.

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Section: Discussionsupporting

confidence: 68%

Section: Experiments IImentioning

confidence: 99%

Evaluation of hypotheses in concept identification

Taplin

1975

Memory & Cognition

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“…As a result, the effective similarity of two size or two form cues might be greater than usual, and the effective similarity of red and green would be expected to be less than otherwise. For tests that can be solved by attending to a single dimension, subjects may have only minimal information to distinguish the individual exemplars (see Bourne & O'Banion, 1969;Calfee, 1969).…”

Section: R(context) K(event)mentioning

confidence: 99%

Context theory of classification learning.

Medin¹,

Schaffer²

1978

Psychological Review

2,709

2,637

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Most theories dealing with ill-defined concepts assume that performance is based on category level information or a mixture of category level and specific item information. A context theory of classification is described in which judgments are assumed to derive exclusively from stored exemplar information. The main idea is that a probe item acts as a retrieval cue to access information associated with stimuli similar to the probe. The predictions of the context theory are contrasted with those of a class of theories (including prototype theory) that assume that the information entering into judgments can be derived from an additive combination of information from component cue dimensions. Across four experiments using both geometric forms and schematic faces as stimuli, the context theory consistently gave a better account of the data. The relation of the context theory to other theories and phenomena associated with ill-defined concepts is discussed in detail. One of the major components of cognitive behavior concerns abstracting rules and forming concepts. Our entire system of naming objects and events, talking about them, and interacting with them presupposes the ability to group experiences into appropriate classes. Young children learn to tell the difference between dogs and cats, between clocks and fans, and between stars and street lights. Since few concepts are formally taught, the evolution of concepts from experience with exemplars must be a fundamental learning phenomenon. The focus of the present article is to explore how such conceptual achievements emerge from individual instances. Structure of Concepts An early step in analyzing task demands involved in conceptual behavior is to ask how

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“…) In the context model the parameter reflecting the similarity of two values on an attribute is assumed to be less when that attribute is attended to, or forms part of a hypothesis, than when it is not so salient. If instructions encourage the belief that there is only one critical attribute, many attributes of the item will not be encoded in any detail at all, and the resulting representations will not be sufficient to distinguish the individual exemplars (e.g., Bourne & O'Banion, 1969;Calfee, 1969). In other words, it is not necessarily assumed that a distinct representation is set up for each individual exemplar.…”

Section: A Note On Stimuli and Category Structure In Relation To The mentioning

confidence: 99%

Strategies and classification learning.

Medin¹,

Smith²

1981

Journal of Experimental Psychology: Human Learning and Memory

155

200

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How do strategies affect the learning of categories that lack necessary and sufficient attributes? The usual answer is that different strategies correspond to different models. In this article we provide evidence for an alternative viewStrategy variations induced by instructions affect only the amount of information represented about attributes, not the process operating on these representations. The experiment required subjects to classify schematic faces into two categories. Three groups of subjects worked with different sets of instructions: roughly, form a prototype of each category, learn each category as a rule-plus-exception, or standard neutral instructions. In addition to learning the faces (Phase 1), subjects were given transfer tests on learned and novel faces (Phase 2) and speeded categorization tests on learned faces (Phase 3). There were performance differences in all three phases due to instructions, but these results were readily accounted for by specific changes in the representations posited by the context model of Medin and Schaffer; that is, strategies seemed to affect only the amount of information stored about each exemplar's attributes.The recent upsurge of interest in natural categories such as bird, tree, and fruit has been accompanied by parallel investigations of representations and processing of artificial categories. In this article we are primarily concerned with the role of strategies in learning the attribute structure of artificial categories. But since the effects of strategies can best be understood in terms of specific categorization models, we first provide a brief overview of models and then take up the strategy issue. Category Learning ModelsOne idea growing out of research with artificial categories is that based on experience with exemplars, people abstract some measure of the central tendency of a category and base their categorical judgments on this central tendency, or prototype (e.g., Posner & Keele, 1968). A contrasting view

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Memory for individual events in concept identification

Cited by 16 publications

References 2 publications

Evaluation of hypotheses in concept identification

Evaluation of hypotheses in concept identification

Context theory of classification learning.

Strategies and classification learning.

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