A model of eye movements and visual working memory during problem solving in geometry.
The Oculomotor Geometry Reasoning Engine (OGRE) was proposed to model eye movements and visual working memory during problem solving in geometry. OGRE postulates that geometrical elements from diagrams are added to visual working memory when they are scanned. Newly-added elements overwrite elements already in memory. The model was applied to eye-movement patterns of three subjects: two geometry experts and one non-expert. Their eye movements and verbal protocols were recorded as they solved geometry problems posed with diagrams. Subjects used highly redundant eye-movement patterns with multiple rescans of the same geometrical elements. OGRE's model of visual memory provided a good fit for the distribution of times between rescans. The model was used to estimate the size of visual working memory used in geometry. The estimates varied as a function of both problems and subjects, with means and standard deviations for each subject being: 5.3+/-1.4, 4.0+/-0.9 and 4.7+/-1.6.
Epelboim
J
J
Center for the Study of Language and Information, Stanford University, Stanford, CA 94305-4115, USA.
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D005133:Eye Movements / Q000502:physiology*; D006801:Humans; D008433:Mathematics; D008568:Memory / Q000502:physiology*; D008954:Models, Biological; D016012:Poisson Distribution; D011340:Problem Solving / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*