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Related Concept Videos

Problem-Solving01:29

Problem-Solving

158
Effective problem-solving consists of two steps: 1. identifying the problem and 2. selecting the appropriate problem-solving strategy (i.e., a plan of action used to find a solution). Humans use four problem-solving strategies:
158
Cognitive Learning01:21

Cognitive Learning

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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Normal and Tangetial Components: Problem Solving01:24

Normal and Tangetial Components: Problem Solving

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Consider a man with a mass of 70 kg seated in a chair connected to a pin support through a member BC. If the man maintains an upright position, the task is to determine the horizontal and vertical reactions of the chair on the man when the member makes a 45° angle with the horizontal. At this moment, the man has a speed of 5 m/s, increasing at a rate of 1 m/s².
177
Theorems of Pappus and Guldinus: Problem Solving01:12

Theorems of Pappus and Guldinus: Problem Solving

730
Pappus and Guldinus's theorems are powerful mathematical principles that are used for finding the surface area and volume of composite shapes. For example, consider a cylindrical storage tank with a conical top. Finding the surface area or volume can be challenging for such complex shapes. These theorems are particularly useful in calculating the volume and surface area of such systems. Here, the cylindrical storage tank with a conical top can be broken down into two simple shapes: a...
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Weir: Problem Solving01:26

Weir: Problem Solving

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Water flow in open channels is often measured using hydraulic structures such as weirs, which allow precise calculation of discharge. In a rectangular channel, flow rates are measured using three types of weirs: rectangular sharp-crested, triangular sharp-crested, and broad-crested. The weir head is set at a fixed height above the channel bottom, simplifying calculations and enabling the relationship between depth and flow rate to be analyzed.For the rectangular sharp-crested weir, the flow...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Problem solving is embedded in context… so how do we measure it?

Katherine T Rhodes1, Lindsey E Richland2, Lucia Alcalá3

  • 1Language Variation and Academic Success (LVAS) Lab, School of Education, University of California, Irvine, Irvine, CA, United States.

Frontiers in Psychology
|June 3, 2024
PubMed
Summary
This summary is machine-generated.

Understanding problem solving requires considering the solver's experiences and context. This study proposes a framework for ecologically valid measurement, integrating individual and environmental factors for accurate information relevance research.

Keywords:
cultural relevanceecological validityinformation relevancemeasurementproblem solving

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Area of Science:

  • Cognitive Psychology
  • Human-Computer Interaction
  • Ecological Psychology

Background:

  • Problem solving is a complex, goal-directed behavior.
  • Traditional decontextualized tasks may not fully capture real-world problem-solving abilities.
  • Information relevance is crucial but often studied without considering ecological factors.

Purpose of the Study:

  • To review the ecological facets of information relevance in problem solving.
  • To propose a framework for ecologically valid measurement of problem solving.
  • To provide examples of culturally relevant measurement approaches.

Main Methods:

  • Literature review of ecological psychology and information relevance in problem solving.
  • Conceptual framework development.
  • Case study examples of ecologically valid measurement.

Main Results:

  • Problem solving is deeply embedded in solver experiences and contexts.
  • Ignoring ecological factors can lead to biased research on information relevance.
  • A framework integrating solver, context, and researcher perspectives is proposed.

Conclusions:

  • Ecologically valid measurement is essential for accurate understanding of problem solving.
  • The proposed framework enhances the study of information relevance by incorporating contextual factors.
  • Culturally relevant and situated measurement practices are recommended for future research.