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Mielicki, Marta K.; Wiley, Jennifer – Journal of Problem Solving, 2016
Successful algebraic problem solving entails adaptability of solution methods using different representations. Prior research has suggested that students are more likely to prefer symbolic solution methods (equations) over graphical ones, even when graphical methods should be more efficient. However, this research has not tested how representation…
Descriptors: Algebra, Problem Solving, Graphs, Equations (Mathematics)
MacGregor, James N. – Journal of Problem Solving, 2013
Most models of human performance on the traveling salesperson problem involve clustering of nodes, but few empirical studies have examined effects of clustering in the stimulus array. A recent exception varied degree of clustering and concluded that the more clustered a stimulus array, the easier a TSP is to solve (Dry, Preiss, & Wagemans,…
Descriptors: Problem Solving, Task Analysis, Testing, College Students
Carruthers, Sarah; Masson, Michael E. J.; Stege, Ulrike – Journal of Problem Solving, 2012
Recent studies on a computationally hard visual optimization problem, the Traveling Salesperson Problem (TSP), indicate that humans are capable of finding close to optimal solutions in near-linear time. The current study is a preliminary step in investigating human performance on another hard problem, the Minimum Vertex Cover Problem, in which…
Descriptors: Performance, Problem Solving, Graphs, Mathematics
Walwyn, Amy L.; Navarro, Daniel J. – Journal of Problem Solving, 2010
An experiment is reported comparing human performance on two kinds of visually presented traveling salesperson problems (TSPs), those reliant on Euclidean geometry and those reliant on city block geometry. Across multiple array sizes, human performance was near-optimal in both geometries, but was slightly better in the Euclidean format. Even so,…
Descriptors: Problem Solving, Mathematical Applications, Graphs, Geometry

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