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62
Attention in learning
- Current Directions in Psychological Science
, 2003
"... explaining many phenomena in learning. The mechanism of selective attention in learning is also well motivated by its ability to minimize proactive interference and enhance generalization, thereby accelerating learning. Therefore, not only does the mechanism help explain behavioral phenomena, it mak ..."
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explaining many phenomena in learning. The mechanism of selective attention in learning is also well motivated by its ability to minimize proactive interference and enhance generalization, thereby accelerating learning. Therefore, not only does the mechanism help explain behavioral phenomena, it makes sense that it should have evolved (Kruschke & Hullinger, 2010). The phrase “learned selective attention ” denotes three qualities. First, “attention ” means the amplification or attenuation of the processing of stimuli. Second, “selective” refers to differentially amplifying and/or attenuating a subset of the components of the stimulus. This selectivity within a stimulus is different from attenuating or amplifying all aspects of a stimulus simultaneously (cf. Larrauri & Schmajuk, 2008). Third, “learned ” denotes the idea that the allocation of selective processing is retained for future use. The allocation may be context sensitive, so that attention is allocated differently in different contexts. There are many phenomena in human and animal learning that suggest the involvement of learned selective attention. The first part of this chapter briefly reviews some of those phenomena. The emphasis of the chapter is not the empirical phenomena, however. Instead, the focus is on a collection of models that formally express theories of learned attention. These models will be surveyed subsequently. Phenomena suggestive of selective attention in learning There are many phenomena in human and animal learning that suggest that learning involves allocating attention to informative cues, while ignoring uninformative cues. The following subsections indicate the benefits of selective allocation of attention, and illustrate the benefits with particular findings.
Necessity and Natural Categories
, 2001
"... Our knowledge of natural categories includes beliefs not only about what is true of them but also about what would be true if the categories had properties other than (or in addition to) their actual ones. Evidence about these beliefs comes from three lines of research: experiments on category-based ..."
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Our knowledge of natural categories includes beliefs not only about what is true of them but also about what would be true if the categories had properties other than (or in addition to) their actual ones. Evidence about these beliefs comes from three lines of research: experiments on category-based induction, on hypothetical transformations of category members, and on definitions of kind terms. The 1st part of this article examines results and theories arising from each of these research streams. The 2nd part considers possible unified theories for this domain, including theories based on ideals and norms. It also contrasts 2 broad frameworks for modal category information: one focusing on beliefs about intrinsic or essential properties, the other focusing on interacting causal relations.
CONCEPTS AND CATEGORIZATION
"... Issues related to concepts and categorization are nearly ubiquitous in psychology because of people’s natural tendency to perceive a thing as something. We have a powerful impulse to interpret our world. This act of interpretation, an act of “seeing something as X ” rather than simply seeing it (Wit ..."
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Issues related to concepts and categorization are nearly ubiquitous in psychology because of people’s natural tendency to perceive a thing as something. We have a powerful impulse to interpret our world. This act of interpretation, an act of “seeing something as X ” rather than simply seeing it (Wittgenstein, 1953), is fundamentally an act of categorization. The attraction of research on concepts is that an extremely wide variety of cognitive acts can be understood as categorizations. Identifying the person sitting across from you at the breakfast table involves categorizing something as (for example) your spouse. Diagnosing the cause of someone’s illness involves a disease categorization. Interpreting a painting as a Picasso, an artifact as Mayan, a geometry as non-Euclidean, a fugue as baroque, a conversationalist as charming, a wine as a Bordeaux, and a government as socialist are categorizations at various levels of abstraction. The typically unspoken assumption of research on concepts is that these cognitive acts have something in common. That is, there are principles that explain many or all acts of categorization. This assumption is controversial (see Medin, Lynch, & Solomon, 2000), but is
Diversity-Based Reasoning in Children
- Cognitive Psychology
, 2001
"... this article is whether children can incorporate this information into inductive reasoning ..."
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this article is whether children can incorporate this information into inductive reasoning
The importance of being coherent: category coherence, cross-classification and reasoning
- Journal of memory and language
"... Category-based inference is crucial for using past experiences to make sense of new ones. One challenge to inference of this kind is that most entities in the world belong to multiple categories (e.g., a jogger, a professor, and a vegetarian). We tested the hypothesis that the degree of coherence of ..."
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Category-based inference is crucial for using past experiences to make sense of new ones. One challenge to inference of this kind is that most entities in the world belong to multiple categories (e.g., a jogger, a professor, and a vegetarian). We tested the hypothesis that the degree of coherence of a category—the degree to which category features go together in light of prior knowledge—influences the extent to which one category will be used over another in property inference. The first two experiments demonstrate that when multiple social categories are available, high coherence categories are selected and used as the basis of inference more often than less coherent ones. The second two experiments provide evidence that ease of category-based explanation of properties is a viable account for coherence differences. We con-clude that degree of coherence meaningfully applies to natural social categories, and is an important influence on cat-egory use in reasoning.
Categories and causality: the neglected direction
- Cognitive Psychology
, 2006
"... www.elsevier.com/locate/cogpsych ..."
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Are there two kinds of reasoning
- In Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society
, 2005
"... Two experiments addressed the issue of how deductive reasoning and inductive reasoning are related. According to the criterion-shift account, these two kinds of reasoning assess arguments along a common scale of strength, however there is a stricter criterion for saying an argument is deductively co ..."
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Two experiments addressed the issue of how deductive reasoning and inductive reasoning are related. According to the criterion-shift account, these two kinds of reasoning assess arguments along a common scale of strength, however there is a stricter criterion for saying an argument is deductively correct as opposed to just inductively strong. The method, adapted from Rips (2001), was to give two groups of participants the same set of written arguments but with either deduction or induction instructions. Signal detection and receiver operating characteristic analyses showed that the difference between conditions could not be explained in terms of a criterion shift. Instead, the deduction condition showed greater sensitivity to argument strength than did the induction condition. Implications for two-process and one-process accounts of reasoning, and relations to memory research, are discussed.
Modeling the effects of argument length and validity on inductive and deductive reasoning. Journal of Experimental Psychology
- Psychological Review
, 2009
"... In an effort to assess models of inductive reasoning and deductive reasoning, the authors, in 3 experiments, examined the effects of argument length and logical validity on evaluation of arguments. In Experiments 1a and 1b, participants were given either induction or deduction instructions for a com ..."
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In an effort to assess models of inductive reasoning and deductive reasoning, the authors, in 3 experiments, examined the effects of argument length and logical validity on evaluation of arguments. In Experiments 1a and 1b, participants were given either induction or deduction instructions for a common set of stimuli. Two distinct effects were observed: Induction judgments were more affected by argument length, and deduction judgments were more affected by validity. In Experiment 2, fluency was manip-ulated by displaying the materials in a low-contrast font, leading to increased sensitivity to logical validity. Several variants of 1-process and 2-process models of reasoning were assessed against the results. A 1-process model that assumed the same scale of argument strength underlies induction and deduction was not successful. A 2-process model that assumed separate, continuous informational dimensions of apparent deductive validity and associative strength gave the more successful account.
Modeling induction as conditional probability judgment
- Dissertation Abstracts International
, 2004
"... Existing research on category-based induction has primarily focused on reasoning about blank properties, or predicates that are designed to elicit little prior knowledge. Here, we address reasoning about nonblank properties. We introduce a model of conditional probability that assumes that the concl ..."
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Existing research on category-based induction has primarily focused on reasoning about blank properties, or predicates that are designed to elicit little prior knowledge. Here, we address reasoning about nonblank properties. We introduce a model of conditional probability that assumes that the conclusion prior probability is revised to the extent warranted by the evidence in the premise. The degree of revision is a function of the relevance of the premise category to the conclusion and the informativeness of the premise statement. An algebraic formulation with no free parameters accurately predicted conditional probabilities for single- and two-premise conditionals (Experiments 1 and 3), as well as problems involving negative evidence (Experiment 2). Studies of inductive inference are usually framed in terms of projecting an unfamiliar (blank) property from one category to another, as in 1. Wolves have sesamoid bones, therefore bears have sesamoid bones. Participants are typically asked to evaluate arguments like the one above with respect to the extent to which the premise supports the conclusion. Several models of induction
From universal laws of cognition to specific cognitive models
, 2008
"... The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which sp ..."
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The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision making might be modelled? Following Shepard (e.g., 1987), it is argued that some universal principles may be attainable in cognitive science. Here we propose two examples: The simplicity principle (which states that the cognitive system prefers patterns that provide simpler explanations of available data); and the scale-invariance principle, which states that many cognitive phenomena are independent of the scale of relevant underlying physical variables, such as time, space, luminance, or sound pressure. We illustrate how principles may be combined to explain specific cognitive processes by using these principles to derive SIMPLE, a formal model of memory for serial order (Brown, Neath & Chater, in press), and briefly mention some extensions to models of identification and categorization. We also consider the scope and limitations of universal laws in cognitive science.
