Effects of time pressure on context-sensitive property induction

Shafto, Patrick; Coley, John D.; Baldwin, David V.

doi:10.3758/bf03194117

Cited by 28 publications

(34 citation statements)

References 12 publications

(15 reference statements)

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“…These results are broadly similar to previous reports of selective induction driven by different types of familiar properties (e.g., Heit & Rubinstein, 1994;Shafto et al, 2007). However, our methods for examining inductive selectivity differed markedly from those used in previous studies.…”

Section: Discussionsupporting

confidence: 81%

“…In a new experiment, we sought to refine this conclusion by examining task conditions that promote or inhibit the use of more complex relations in induction. Previous work has shown that the use of complex forms of similarity in object comparisons and property induction is influenced by the time that is available for test decisions (Goldstone & Medin, 1994;Shafto et al, 2007). Shafto et al, for example, found that more complex forms of similarity (e.g., ecological relations between animals) were more likely to be used in induction when participants were forced to spend time deliberating about their judgments.…”

Section: Methodsmentioning

confidence: 99%

“…An important finding in the induction literature is that the use of familiar or meaningful properties can change the way that the similarity between base and target items is computed in induction (e.g., Heit & Rubinstein, 1994;Medin, Coley, Storms, & Hayes, 2003;Shafto, Coley, & Baldwin, 2007). Heit and Rubinstein, for example, found that people relied on taxonomic similarity when generalizing anatomical properties across animal triads (e.g., generalization was stronger from sparrows to hawks than from tigers to hawks), but relied on ecological similarity when generalizing behavioral properties across the same triads (e.g., generalization was stronger from tigers to hawks than from sparrows to hawks).…”

Section: The Relationship Between Recognition and More Complex Forms mentioning

confidence: 99%

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How similar are recognition memory and inductive reasoning?

Hayes

Heit

2013

Mem Cogn

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Conventionally, memory and reasoning are seen as different types of cognitive activities driven by different processes. In two experiments, we challenged this view by examining the relationship between recognition memory and inductive reasoning involving multiple forms of similarity. A common study set (members of a conjunctive category) was followed by a test set containing old and new category members, as well as items that matched the study set on only one dimension. The study and test sets were presented under recognition or induction instructions. In Experiments 1 and 2, the inductive property being generalized was varied in order to direct attention to different dimensions of similarity. When there was no time pressure on decisions, patterns of positive responding were strongly affected by property type, indicating that different types of similarity were driving recognition and induction. By comparison, speeded judgments showed weaker property effects and could be explained by generalization based on overall similarity. An exemplar model, GEN-EX (GENeralization from EXamples), could account for both the induction and recognition data. These findings show that induction and recognition share core component processes, even when the tasks involve flexible forms of similarity.

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Section: Discussionsupporting

confidence: 81%

Section: Methodsmentioning

confidence: 99%

Section: The Relationship Between Recognition and More Complex Forms mentioning

confidence: 99%

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How similar are recognition memory and inductive reasoning?

Hayes

Heit

2013

Mem Cogn

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“…In the speeded condition, in order to impose time pressure on responses we instructed participants to enter their response within 1.5 s of the presentation of each image. This restriction was based on previous work looking at the effect of time pressure on inferences (Shafto, Coley, & Baldwin, 2007) and on pretesting which suggested this was an interval at which participants experienced time pressure but could reliably respond. If they did not answer in time, they received an error message, and were prompted to respond more quickly.…”

Section: Designmentioning

confidence: 99%

Anthropocentric by Default? Attribution of Familiar and Novel Properties to Living Things

Arenson

Coley

2017

Cognitive Science

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Humans naturally and effortlessly use a set of cognitive tools to reason about biological entities and phenomena. Two such tools, essentialist thinking and teleological thinking, appear to be early developmental cognitive defaults, used extensively in childhood and under limited circumstances in adulthood, but prone to reemerge under time pressure or cognitive load. We examine the nature of another such tool: anthropocentric thinking. In four experiments, we examined patterns of property attribution to a wide range of living and non-living objects, manipulating time pressure, response type, and property (either novel or familiar) in a total of 471 participants. Results showed no tendency toward increased similarity-based attribution patterns indicative of anthropocentric thinking under time pressure. However, anthropocentric thinking was consistently observed for unfamiliar properties. These findings suggest that anthropocentric thinking is not a developmentally persistent cognitive default, but rather a cognitive strategy deliberately employed in situations of uncertainty.

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“…5 Shafto et al (2007) use a speeded induction task to show that some knowledge structures are easier to access than others, and a similar paradigm could be used to test the proposal that combining multiple structures is relatively demanding.…”

Section: When Are Knowledge Structures Combined?mentioning

confidence: 99%

An integrated account of generalization across objects and features

Kemp

Shafto

Tenenbaum

2012

Cognitive Psychology

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Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single feature that is unobserved for one or more objects. We explore problems where people must make inferences about multiple objects and features, and propose that people solve these problems by integrating knowledge about features with knowledge about objects. We evaluate three computational methods for integrating multiple systems of knowledge: the output combination approach combines the outputs produced these systems, the distribution combination approach combines the probability distributions captured by these systems, and the structure combination approach combines a graph structure over features with a graph structure over objects. Three experiments explore problems where participants make inferences that draw on causal relationships between features and taxonomic relationships between animals, and we find that the structure combination approach provides the best account of our data.

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Effects of time pressure on context-sensitive property induction

Cited by 28 publications

References 12 publications

How similar are recognition memory and inductive reasoning?

How similar are recognition memory and inductive reasoning?

Anthropocentric by Default? Attribution of Familiar and Novel Properties to Living Things

An integrated account of generalization across objects and features

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