摘要 :
We examine whether reasoning is improved by evaluative feedback, i.e., the information of whether a reasoner's answer was correct or incorrect, and report two studies that show that evaluative feedback increases the chances that p...
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We examine whether reasoning is improved by evaluative feedback, i.e., the information of whether a reasoner's answer was correct or incorrect, and report two studies that show that evaluative feedback increases the chances that participants will produce normatively correct responses for deductive reasoning problems. In Experiment 1, participants who were given feedback about their performance did better on problems based on disjunctions that were designed to elicit illusory inferences. In Experiment 2, participants answered difficult syllogisms with more accuracy when they were provided with feedback. We conclude by contrasting the rule- , heuristics-, and model-based accounts of deduction on their ability to explain the effects of evaluative feedback.
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摘要 :
During the past several years, the senior investigator has been attempting to develop a unified theory of human reasoning. This research has proceeded along two major fronts, one involving the formulation of a subtheory of inducti...
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During the past several years, the senior investigator has been attempting to develop a unified theory of human reasoning. This research has proceeded along two major fronts, one involving the formulation of a subtheory of inductive reasoning, the other involving the formulation of a subtheory of deductive reasoning. This article discusses work done on deduction. Although the theory of deductive reasoning is not yet completely formulated or tested, work on the theory is far enough along to merit a progress report. So far, models of deduction for the three main kinds of syllogisms that have been investigated by students of human reasoning have been formulated and tested: categorical, conditional, and linear syllogisms. The theory and data for each of the three kinds of syllogisms are summarized and some conclusions are drawn.
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The present research sought to understand the components of syllogistic reasoning that are used in a syllogistic evaluation task. The research had two major goals. The first was to compare one particular model of syllogistic reaso...
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The present research sought to understand the components of syllogistic reasoning that are used in a syllogistic evaluation task. The research had two major goals. The first was to compare one particular model of syllogistic reasoning, the transitive-chain model of Guyote and Sternberg, to plausible alternative models that have been proposed in the past. Recent comparisons of the models using a response-selection task have provided convincing evidence of the superiority of the transitive chain model for this particular task, and the present research seeks to extend these findings to the response-evaluation task. The second goal was to separate experimentally the premise encoding and premise combination stages of syllogistic reasoning, thereby enabling (a) more direct tests of the various models' assumptions about each stage than has been possible in previous research, and (b) more direct inferences regarding the representations of relations between the subject and predicate of the premises as encoded and combined by subjects. This second goal was accomplished by a modified form of componential analysis whereby an information-processing task is decomposed into a series of nested subtasks that permit isolation of the elementary components of task performance.
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摘要 :
The transitive-chain theory of syllogistic reasoning proposes that: (1) information about set relations is represented in memory by pairs of informational components; and (2) information about set relations is integrated by applyi...
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The transitive-chain theory of syllogistic reasoning proposes that: (1) information about set relations is represented in memory by pairs of informational components; and (2) information about set relations is integrated by applying a small set of rules to transitive chains that are formed by rearranging informational components stored in memory. The method of rearranging informational components into transitive chains and the rules applied to these chains are specified. The transitive-chain theory is compared to several earlier theories, each of which is cast in terms of an information-processing model. Mathematical models that quantify each of these information-processing models are presented. In a series of five experiments, the transitive-chain theory provides a good account of the response-choice data for syllogisms with various types of content, quantifiers, and logical relations (categorical and conditional). Results of these experiments offer tentative answers to five major issues in syllogistic reasoning theory: (1) Generality of the processes used in syllogistic reasoning; (2) Relationship of syllogistic reasoning ability to intelligence; (3) Representation of and (4) Combination of premise information; and (5) Sources of difficulty in syllogistic reasoning.
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Students of reasoning have engaged in a vigorous debate regarding the representations and processes used by subjects solving linear syllogisms. Meaningful communication between proponents of the various positions has been hampered...
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Students of reasoning have engaged in a vigorous debate regarding the representations and processes used by subjects solving linear syllogisms. Meaningful communication between proponents of the various positions has been hampered by the appearance of curious conflicts in reported data sets for the linear syllogism problems. The present experiment was intended to isolate the source of these conflicts in the literature. Eighteen adult subjects received linear syllogisms under instructions designed to yield speeds commensurate with error rates of about 10%. Latency and error data were analyzed both separately (via multiple regression) and jointly (via canonical regression). These data were also analyzed via pseudo-deadlines, according to which responses were counted as correct if they were correct and fell below a given pseudo-deadline, and were counted as erroneous if they were incorrect or fell above a given pseudo-deadline. The analyses revealed that the source of the conflicts in the literature is the failure of researchers to appreciate the complex interrelationships between latency and error rate. When these interrelationships are taken into account, the conflicts disappear. (Author)
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摘要 :
Soar is an architecture for general intelligence that has been proposed as a unified theory of human cognition (UTC) (Newell, 1989) and has been shown to be capable of supporting a wide range of intelligent behavior. Polk & Newell (1988) showed that a Soar theory could account for human data in syllogistic reasoning. In this paper, we begin to generalize this theory into a unified theory of immediate reasoning based on Soar and some assumptions about subjects' representation and knowledge. The theory, embodied in a Soar system (IR-Soar), posits three basic problem spaces (comprehend, test-proposition, and build-proposition that construct annotated models and extract knowledge from them, learn (via chunking) from experience and use an attention mechanism to guide search. Acquiring task specific knowledge is modeled with the comprehend space thus reducing the degrees of freedom available to fit data. The theory explains the qualitative phenomena in four immediate reasoning tasks and accounts for an individual's responses in syllogistic reasoning. It represents a first step toward theory of immediate reasoning and moves Soar another step closer to being a unified theory of cognition. Keywords: Syllogisms; Wason ...
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Soar is an architecture for general intelligence that has been proposed as a unified theory of human cognition (UTC) (Newell, 1989) and has been shown to be capable of supporting a wide range of intelligent behavior. Polk & Newell (1988) showed that a Soar theory could account for human data in syllogistic reasoning. In this paper, we begin to generalize this theory into a unified theory of immediate reasoning based on Soar and some assumptions about subjects' representation and knowledge. The theory, embodied in a Soar system (IR-Soar), posits three basic problem spaces (comprehend, test-proposition, and build-proposition that construct annotated models and extract knowledge from them, learn (via chunking) from experience and use an attention mechanism to guide search. Acquiring task specific knowledge is modeled with the comprehend space thus reducing the degrees of freedom available to fit data. The theory explains the qualitative phenomena in four immediate reasoning tasks and accounts for an individual's responses in syllogistic reasoning. It represents a first step toward theory of immediate reasoning and moves Soar another step closer to being a unified theory of cognition. Keywords: Syllogisms; Wason task; Unified theories of cognition; Reasoning. (EDC)
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