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Neural basis of thinking: laboratory problems versus real-world problems
1Department of Psychology, York University, Toronto, Canada and University of Hull, UK.
Wiley Interdisciplinary Reviews. Cognitive Science
|August 15, 2015
Summary
Neuropsychological data support the distinction between well-structured and ill-structured problems. This difference may explain why neurological patients sometimes perform inconsistently in different problem-solving scenarios.
Area of Science:
- Cognitive psychology
- Neuropsychology
Background:
- Cognitive psychologists debate the distinction between well-structured and ill-structured problems.
- Laboratory problems are typically well-structured, while real-world problems often contain both types.
Purpose of the Study:
- To investigate how neuropsychological data support the distinction between well-structured and ill-structured problems.
- To explain discontinuous performance in neurological patients using this distinction.
Main Methods:
- Review of existing cognitive psychology literature.
- Analysis of neuropsychological data related to problem-solving.
- Theoretical integration of findings.
Main Results:
- Neuropsychological evidence reinforces the distinction between well-structured and ill-structured problems.
- The distinction offers a potential explanation for inconsistent patient performance across different problem types.
Conclusions:
- The difference between well-structured and ill-structured problems is supported by neuropsychological findings.
- This distinction is crucial for understanding cognitive deficits and performance variability in neurological conditions.
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