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Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
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Giving up problem solving.

Stephen J Payne1, Geoffrey B Duggan

  • 1University of Bath, Bath, United Kingdom. s.j.payne@bath.ac.uk

Memory & Cognition
|January 26, 2011
PubMed
Summary
This summary is machine-generated.

People abandon problems based on how likely they seem to be solvable and their complexity. Higher solvability probability and more possible states increase problem-solving effort and time before giving up.

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Area of Science:

  • Cognitive Psychology
  • Decision Making
  • Problem Solving

Background:

  • Understanding how individuals make decisions to cease problem-solving efforts is crucial in cognitive psychology.
  • Previous research has explored factors influencing persistence, but the interplay of prior solvability and problem complexity requires further investigation.

Purpose of the Study:

  • To investigate how the prior probability of a problem's solvability and its size (number of states) influence an individual's decision to abandon the problem.
  • To examine the relationship between these factors and measures of effort and confidence during problem-solving.

Main Methods:

  • Three experiments were conducted using unsolvable water jar problems.
  • Participants were informed of the prior probability of solvability for each problem.
  • Effort (time spent) and confidence were measured as key outcomes.

Main Results:

  • A significant effect of the prior probability of solvability on effort was observed; higher probability led to longer engagement.
  • Problem size, defined as the number of distinct problem states, also influenced effort, with larger problems eliciting more sustained effort.
  • Giving-up decisions were found to align with rational models, considering perceived success probability and solution costs.

Conclusions:

  • The decision to abandon a problem is not arbitrary but is systematically influenced by the perceived likelihood of success and the problem's inherent complexity.
  • Effort and persistence in problem-solving are modulated by both external information (prior probability) and internal problem characteristics (size/states).
  • These findings support rational models of decision-making, suggesting that problem-solving termination follows similar principles to other choice behaviors.