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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
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Van Stockum, Charles A., Jr.; DeCaro, Marci S. – Journal of Problem Solving, 2014
Individual differences in working memory capacity (WMC) increase the ability and tendency to devote greater attentional control to a task--improving performance on a wide range of skills. In addition, recent research on enclothed cognition demonstrates that the situational influence of wearing a white lab coat increases controlled attention, due…
Descriptors: Problem Solving, Short Term Memory, Attention Control, Intuition
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Kwisthout, Johan – Journal of Problem Solving, 2012
When computer scientists discuss the computational complexity of, for example, finding the shortest path from building A to building B in some town or city, their starting point typically is a formal description of the problem at hand, e.g., a graph with weights on every edge where buildings correspond to vertices, routes between buildings to…
Descriptors: Problem Solving, Computation, Abstract Reasoning, Difficulty Level
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Chu, Yun; MacGregor, James N. – Journal of Problem Solving, 2011
The article provides a review of recent research on insight problem-solving performance. We discuss what insight problems are, the different types of classic and newer insight problems, and how we can classify them. We also explain some of the other aspects that affect insight performance, such as hints, analogs, training, thinking aloud, and…
Descriptors: Performance, Intuition, Problem Solving, Literature Reviews
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Taatgen, Niels A. – Journal of Problem Solving, 2011
The minimal control principle (Taatgen, 2007) predicts that people strive for problem-solving strategies that require as few internal control states as possible. In an experiment with the Abstract Decision Making task (ADM task; Joslyn & Hunt, 1998) the reward structure was manipulated to make either a low-control strategy or a high-strategy…
Descriptors: Problem Solving, Abstract Reasoning, Decision Making, Learning Strategies
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Yi, Sheng Kung M.; Steyvers, Mark; Lee, Michael – Journal of Problem Solving, 2009
Bandit problems provide an interesting and widely-used setting for the study of sequential decision-making. In their most basic form, bandit problems require people to choose repeatedly between a small number of alternatives, each of which has an unknown rate of providing reward. We investigate restless bandit problems, where the distributions of…
Descriptors: Performance, Decision Making, Problem Solving, Rewards
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Chronicle, Edward P.; MacGregor, James N.; Lee, Michael; Ormerod, Thomas C.; Hughes, Peter – Journal of Problem Solving, 2008
Results on human performance on the Traveling Salesman Problem (TSP) from different laboratories show high consistency. However, one exception is in the area of individual differences. While one research group has consistently failed to find systematic individual differences across instances of TSPs (Chronicle, MacGregor and Ormerod), another…
Descriptors: Individual Differences, Problem Solving, Performance, Research Problems
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Lee, Michael D.; Paradowski, Michael J. – Journal of Problem Solving, 2007
We consider group decision-making on an optimal stopping problem, for which large and stable individual differences have previously been established. In the problem, people are presented with a sequence of five random numbers between 0 and 100, one at a time, and are required to choose the maximum of the sequence, without being allowed to return…
Descriptors: Participative Decision Making, Problem Solving, Individual Differences, Comparative Analysis
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Burns, Nicholas R.; Lee, Michael D.; Vickers, Douglas – Journal of Problem Solving, 2006
Studies of human problem solving have traditionally used deterministic tasks that require the execution of a systematic series of steps to reach a rational and optimal solution. Most real-world problems, however, are characterized by uncertainty, the need to consider an enormous number of variables and possible courses of action at each stage in…
Descriptors: Individual Differences, Performance, Problem Solving, Intelligence