Problem Solving, Reasoning, & Judgment Claudia Stanny PSY 2012

Problem Solving Problem Space  Initial state  Goal state  Operations Well-defined Problems  Can be solved using algorithms  Initial state, goal state, and operations can be clearly identified Ill-defined Problems  Initial state, goal state or operations are ambiguous. Not always clean when the problem is solved.

Algorithms Step-by-step process Following the steps will always produce a solution to the problem  Ordering a set of books alphabetically  Solving an arithmetic problem Used with well-defined problems

Heuristics Cognitive “short cuts” or “rules of thumb” Suggest a possible solution to a problem quickly May not always generate the best answer to the problem  availability heuristic  representativeness heuristic Used for ill-defined problems

How to study problem solving? Think-aloud protocols  Problem: John has 6 marbles. Paul has twice as many marbles as John. Phil has 3 marbles fewer than John and Paul combined. How many marbles does Phil have?  Describe what you think about as you solve the problem Describe how you organize the problem Describe the steps you follow to solve the problem

Improving Problem Solving Find the correct representation of the problem  Within knowledge domains, expert problem solvers learn about types of problems and how best to represent each type Practice operations used to solve problems within a domain  Ability to rapidly carry out problem-solving operations allow experts to rapidly reason forward from current knowledge  Novices tend to use more time-consuming backward reasoning strategies

Functional Fixedness Explain the rule that determines the order of each of the following sets of ten numbers:   

Reasoning Drawing logical conclusions from assumptions or other prior information Correctly apply the rules of logic to arrive at valid conclusions  All apples are fruit.  This is an apple.  This is a fruit.

Belief-Bias Effect We tend to judge the validity of arguments based on the truth of the conclusion rather than on the validity of the logic used. Invalid use of logic sometimes produces conclusions that are true.  If my finger is cut, then it bleeds. My finger is bleeding. Therefore, my finger is cut. (Invalid but true)  If I eat candy often, then I have cavities. I have cavities. Therefore, I eat candy often. (Invalid and not true)

Judgment & Decision Making Choices made with ill-defined problems No established, correct rules for making these choices No clear method for determining whether we have made the correct decision  Which of two apartments should you rent when the choices vary in cost, location, size, age of appliances, etc.?

Heuristics & Biases in Judgment Heuristics  rules of thumb or other short cuts that usually produce good solutions  attractive because they allow us to arrive at decision quickly  create problems because they do not guarantee that the solution will be correct

Which set of letters (A or B) will allow us to draw the largest number of different paths? X X X X A X B

Availability Heuristic Decisions made based on the most readily available information Decisions made on information accessed quickly rather than on all of the relevant information Memory processes can provide a biased sample of examples or biased information  which event is the more likely cause of death in the US? Falling airplane parts Shark attack Tornado Lightning Car accident Pneumonia

Representativeness Heuristic Which of the following sequences of letters was most like to have been created by a random process (such as flipping a coin)? XOXXXOOOOOXXOOOXXXXOX XOXOXOOOXXOXOXOOXXXOX

Anchoring Heuristic If all of the human blood in the world were poured into a cube-shaped tank, how wide would the tank be?

Framing Effects Representation (frame) of the problem can influence the decision made.  Which lottery would you choose? Ticket has a sure win of $250. Ticket has a 25% chance to win $1000 and a 75% chance to win nothing.  Which lottery would you choose? Ticket has a sure loss of $750. Ticket has a 75% chance to lose $1000 and a 25% chance to lose nothing.

Decision Aversion Situations in which people try to avoid making any decision at all.  Decisions that will result in gains for some and losses for others  Decisions in which the person fears that they will regret their choice  Decisions in which the person will be held responsible for bad outcomes  Decisions made on behalf of other people