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Hayes, Brett K.; Liew, Shi Xian; Desai, Saoirse Connor; Navarro, Danielle J.; Wen, Yuhang – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames - causal constraints that only allow certain types of instances to be sampled. Group data from both…
Descriptors: Logical Thinking, Inferences, Bias, Individual Differences
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Henry Markovits; Valerie A. Thompson – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Mental model (Johnson-Laird, 2001) and probabilistic theories (Oaksford & Chater, 2009) claim to provide distinct explanations of human reasoning. However, the dual strategy model of reasoning suggests that this distinction corresponds to different reasoning strategies, termed "counterexample" and "statistical,"…
Descriptors: Abstract Reasoning, Thinking Skills, Learning Strategies, Logical Thinking
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Wareham, Todd – Journal of Problem Solving, 2017
In human problem solving, there is a wide variation between individuals in problem solution time and success rate, regardless of whether or not this problem solving involves insight. In this paper, we apply computational and parameterized analysis to a plausible formalization of extended representation change theory (eRCT), an integration of…
Descriptors: Problem Solving, Schemata (Cognition), Intuition, Computation
Beghetto, Ronald A. – ECNU Review of Education, 2019
Purpose: This article, based on an invited talk, aims to explore the relationship among large-scale assessments, creativity and personalized learning. Design/Approach/Methods: Starting with the working definition of large-scale assessments, creativity, and personalized learning, this article identified the paradox of combining these three…
Descriptors: Measurement, Creativity, Problem Solving, Artificial Intelligence
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Hardman, Kyle O.; Cowan, Nelson – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Working memory (WM) is used for storing information in a highly accessible state so that other mental processes, such as reasoning, can use that information. Some WM tasks require that participants not only store information, but also reason about that information to perform optimally on the task. In this study, we used visual WM tasks that had…
Descriptors: Logical Thinking, Short Term Memory, Models, Individual Differences
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Navarro, Daniel J.; Dry, Matthew J.; Lee, Michael D. – Cognitive Science, 2012
Inductive generalization, where people go beyond the data provided, is a basic cognitive capability, and it underpins theoretical accounts of learning, categorization, and decision making. To complete the inductive leap needed for generalization, people must make a key "sampling" assumption about how the available data were generated.…
Descriptors: Logical Thinking, Generalization, Sampling, Learning
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Macpherson, Robyn; Stanovich, Keith E. – Learning and Individual Differences, 2007
This study examined the predictors of belief bias in a formal reasoning paradigm (a syllogistic reasoning task) and myside bias in two informal reasoning paradigms (an argument generation task and an experiment evaluation task). Neither cognitive ability nor thinking dispositions predicted myside bias, but both cognitive ability and thinking…
Descriptors: Thinking Skills, Cognitive Ability, Logical Thinking, Models
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Bouwmeester, Samantha; Vermunt, Jeroen K.; Sijtsma, Klaas – Developmental Review, 2007
Fuzzy trace theory explains why children do not have to use rules of logic or premise information to infer transitive relationships. Instead, memory of the premises and performance on transitivity tasks is explained by a verbatim ability and a gist ability. Until recently, the processes involved in transitive reasoning and memory of the premises…
Descriptors: Memory, Cognitive Development, Classification, Individual Differences
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Nosofsky, Robert M.; And Others – Psychological Review, 1994
A rule-plus-exception model (RULEX) of classification learning is proposed. According to RULEX, people learn to classify objects by forming simple logical rules and remembering occasional exceptions to these rules. Because the learning process is stochastic, people will vary in the rules formed and exceptions stored. (SLD)
Descriptors: Classification, Individual Differences, Learning, Logical Thinking
Tallmadge, G. Kasten; And Others – 1968
Two separate subject matter areas, which were felt to represent two distinct types of learning situations, were selected for investigation, namely, a kind of logico-mathematical procedure--the transportation technique, and a visual form discrimination task--aircraft recognition. Two separate courses were developed for each subject matter area. One…
Descriptors: Cost Effectiveness, Course Content, Discrimination Learning, Individual Differences
Lifton, Peter D. – 1981
This paper proposes a theoretical framework of moral and immoral development which considers not only reasoning, but also behavior and situational variables. Major theories of moral development proposed by Freud, Piaget, Kohlberg, Haan, and Hogan are used to illustrate the notion that, although empirical evidence shows that most individuals…
Descriptors: Adjustment (to Environment), Antisocial Behavior, Cognitive Processes, Cognitive Style
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection