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SumptuousFluorite7652

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Università Cattolica del Sacro Cuore - Milano (UCSC MI)

2024

Prof. Federica Biassoni

Tags

psychology problem solving cognitive psychology thought processes

Summary

This document provides lecture notes on problem solving, covering various strategies and concepts in psychology. The notes are from an Experimental Psychology course taught by Prof. Federica Biassoni in the academic year 2024/2025. The document discusses concepts like difference reduction, means-end analysis and working backward, and representations in problem solving.

Full Transcript

Thought – Problem solving Experimental Psychology Course Prof. Federica Biassoni A.Y. 2024/2025 Thought in Action: Problem Solving Four Stages in Problem Solving: 1. Representing (framing) and interpreting (understanding) the problem 2. Generating hypothe...

Thought – Problem solving Experimental Psychology Course Prof. Federica Biassoni A.Y. 2024/2025 Thought in Action: Problem Solving Four Stages in Problem Solving: 1. Representing (framing) and interpreting (understanding) the problem 2. Generating hypotheses or possible solutions 3. Testing the solutions or hypotheses, seeking to disconfirm one or more of them 4. Evaluating the results and, if necessary, revising the previous steps Thought in Action: Problem Solving In problem solving there is an initial state & a goal state; we need to break problem down into subgoals that can be more easily obtained. Problem Solving strategies: weak methods Difference-reduction method à to reduce the difference between our current state in the problem & the goal state: we set up subgoals that, when obtained, put us in a state that is closer to our goal Problem Solving strategies: weak methods Means-end analysis à we identify differences between the present situation and the desired state, or goal, and then make changes that will reduce these differences à is a more sophisticated strategy because it allows us to take an action even if it results in a temporary decrease in similarity between our current state and the goal state Problem Solving strategies: weak methods Working backward à involves reasoning from the goal to a subgoal, from that one to another subgoal etc. until finding the subgoal we can readily obtain The candle problem Given the depicted materials, how can you support the candle on a door? Thought in Action: Problem Solving Two ways of representing the problem: visual representation is better for some problems, propositional representation better for others. Imaginal thought relies on analogical representations (imagery involves the same processes and representations that are used in perception), in contrast with propositional thought which relies on symbolic representations. Problem Solving: Representing the problem Key step toward a successful solution: arriving at a useful representation of a problem is half the solution of the problem! Functional fixedness: a bias that limits a person to use an object only in the way it is traditionally used. Vs Restructuring a problem, thinking of it differently (maybe also finding an appropriate analogy), can be very helpful à Divergent thinking, creativity (the ability to produce something that is new and valuable also departing from the norm). Problem Solving: Expert versus novice Experts in domain solve problems qualitatively differently than novices do They differ in following ways: Experts hold a multitude of representation and more specific representations in memory to use Experts represent novel situations in terms of solution principles (structural features) rather than of surface features Experts form a plan first before taking action Experts tend to work in a forward direction (from givens of the problem toward the solution), while novices tend to apply the working-backward strategy The Stroop Effect Interference of the automatic reading process with the colour-naming task. Problem Solving: Automaticity Automatic processes can be carried out without conscious control Unconscious thought: Is an active process Is goal dependent results in a different representation of the information, that apparently allows for a better consideration of the factors that are important in complex decisions. Much of our thinking processes become automatic with experience, e.g. reading.

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