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MacGregor, James N.; Chu, Yun – Journal of Problem Solving, 2011
The article provides a review of recent research on human performance on the traveling salesman problem (TSP) and related combinatorial optimization problems. We discuss what combinatorial optimization problems are, why they are important, and why they may be of interest to cognitive scientists. We next describe the main characteristics of human…
Descriptors: Problem Solving, Mathematical Applications, Graphs, Performance
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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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Chu, Yun; Li, Zheng; Su, Yong; Pizlo, Zygmunt – Journal of Problem Solving, 2010
Isomorphs of a puzzle called m+m resulted in faster solution times and an easily reproduced solution path in a labeled version of the problem compared to a more difficult binary version. We conjecture that performance is related to a type of heuristic called direction that not only constrains search space in the labeled version, but also…
Descriptors: Heuristics, Problem Solving, Puzzles, Navigation
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Chu, Yun; Dewald, Andrew D.; Chronicle, Edward P. – Journal of Problem Solving, 2007
Three experiments investigated the effects of two hints derived from the Criterion for Satisfactory Progress theory (CSP) and Representational Change Theory (RCT) on the cheap necklace problem (insight problem). In Experiment 1, fewer participants given the CSP hint used an incorrect (maximizing) first move than participants given the RCT hint or…
Descriptors: Theories, Problem Solving, Prompting, College Students