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Related Concept Videos

Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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Strategy generalization across orientation tasks: testing a computational cognitive model.

Glenn Gunzelmann1

  • 1Air Force Research Laboratory, Mesa, Arizona.

Cognitive Science
|June 4, 2011
PubMed
Summary
This summary is machine-generated.

Humans flexibly adapt general spatial strategies for different tasks like map reading and scene navigation. A computational model showed this adaptability, highlighting individual differences in spatial reasoning.

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Area of Science:

  • Cognitive Psychology
  • Spatial Cognition
  • Computational Modeling

Background:

  • Human spatial information processing is crucial for problem-solving and decision-making.
  • Understanding how general strategies are applied to diverse spatial tasks is key.

Purpose of the Study:

  • To investigate if a general spatial strategy can be adapted for distinct spatial orientation tasks.
  • To test predictions of a computational cognitive model for map-based and scene-based spatial tasks.

Main Methods:

  • Developed a computational cognitive model based on a 'find-on-map' task.
  • Adapted the model to predict performance on both 'find-on-map' and 'find-in-scene' tasks.
  • Collected human performance data for comparison with model predictions.

Main Results:

  • The model qualitatively fit human data, suggesting a generalizable spatial strategy.
  • Quantitative differences revealed individual variations in spatial task performance.
  • The model successfully accounted for individual differences.

Conclusions:

  • Humans can tailor a general spatial strategy to specific task demands.
  • Computational models offer a framework for understanding spatial abilities in naturalistic tasks.
  • Individual differences in spatial reasoning are significant and can be modeled.