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Carruthers, Sarah; Stege, Ulrike – Journal of Problem Solving, 2013
This article is concerned with how computer science, and more exactly computational complexity theory, can inform cognitive science. In particular, we suggest factors to be taken into account when investigating how people deal with computational hardness. This discussion will address the two upper levels of Marr's Level Theory: the computational…
Descriptors: Problem Solving, Computation, Difficulty Level, Computer Science
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MacGregor, James N.; Cunningham, John B. – Journal of Problem Solving, 2009
Insight problem solving is characterized by restructuring. We hypothesized that the difficulty of rebus puzzles could be manipulated by systematically varying the restructurings required to solve them. An experiment using rebus puzzles varied the number of restructurings (one or two) required to solve a problem and the level at which the…
Descriptors: Problem Solving, Numbers, Difficulty Level, Puzzles
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Ash, Ivan K.; Jee, Benjamin D.; Wiley, Jennifer – Journal of Problem Solving, 2012
Gestalt psychologists proposed two distinct learning mechanisms. Associative learning occurs gradually through the repeated co-occurrence of external stimuli or memories. Insight learning occurs suddenly when people discover new relationships within their prior knowledge as a result of reasoning or problem solving processes that re-organize or…
Descriptors: Intuition, Learning Processes, Metacognition, Associative Learning
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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