What is Cognitive Science

Revising cognitive style dimension: two types of visualizers

Maria Kozhevnikov

Thursday, March 27, 2003, 12:00pm - 07:00pm

Rutgers University, Department of Psychology, Newark

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Revising cognitive style dimension: two types of visualizers
Mar 27 Maria Kozhevnikov (Rutgers University, Department of Psychology, Newark)


In this study we propose and test a revision of the visualizer/verbalizer cognitive style dimension. One hundred and eighteen participants were administered a computerized battery of imagery tasks, standard paper-and pencil spatial and verbal ability tests, and a visualizer-verbalizer cognitive style questionnaire. Two orthogonal groups of visualizers were identified. While one group of visualizers (object imagers) scored lower than average on spatial imagery tasks (e.g., mental rotation), they scored higher than average on visual-pictorial imagery tasks (e.g., degraded picture task). In contrast, the other group of visualizers (spatial imagers) scored higher than average on spatial imagery tasks, but performed significantly lower on visual imagery tasks. Reaction time of the object imagers was significantly faster in all types of tasks. In addition we compared problem-solving strategies used by spatial imagers to those of object imagers. The students were presented with graphs of motion, and were asked to visualize and interpret the motion of an object. Whereas object imagers interpreted the graphs as pictures and mostly relied on visual pictorial imagery, spatial imagers constructed more schematic images and manipulated them spatially. The results provide evidence that dissociation between visual-pictorial and spatial imagery exists in individual differences in imagery and that visualizer/verbalizer dimension is not a unitary construct, but involves two qualitatively different types of visualizers.

Maria Kozhevnikov

"What is Cognitive Science?"

This lunchtime talks series is designed to introduce the University community to issues in Cognitive Science. Cognitive Science is one the the few fields where modern developments in computer science and artificial intelligence promise to shed light on classical problems in psychology and the philosophy of the mind. Ancient questions of how we see the world, understand language, and reason, and questions such as 'how a material system can know about the outside world', are being explored with the powerful new conceptual prosthetics of computer modeling.

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