Ch. 11 Canvas Quiz Cognitive Processes w/ Warner- PSU

Explain what Griggs and Cox believed that participants were using to answer everyday logic problems, such as those dealing with drinking age.

"People perform much better when the task is concrete, familiar, and realistic. Griggs and Cox (1982) tested college students in Florida using a variation of the selection task. This task focused on the drinking age, which was then 19 in the state of Florida. Specifically, the students were asked to test this rule: "If a person is drinking beer, then the person must be over 19 years of age". Each participant was instructed to choose two cards to turn over—out of four—in order to test whether people were lying about their age. Griggs and Cox (1982) found that 73% of the students who tried the drinking age problem made the correct selections, in contrast to 0% of the students who tried the standard, abstract form of the selection task. According to later research, people are especially likely to choose the correct answer when the wording of the selection task implies some kind of social contract designed to prevent people from cheating

Contrast the difference between an ill-defined problem and a well-defined problem.

A well-defined problem is one in which the initial state, goal state, and methods available to you are understood. An ill-defined problem is one in which the initial state, goal state, and/or methods are ill-defined.

Generate the characteristics of normative models of utility.

Classical decision theory: Based upon the concept of utility (how much a choice is worth), require specification of the values associated with different choices, prescribe how optimal choices should be made, computer-based decision aids usually use these principles

Describe the two lasting contributions to the study of problem solving by the Gestalt psychologists.

Gestalt psychologists find it is important to think of problems as a whole. There are two types of thinking: Productive thinking (solving with insight) and Reproductive thinking (solving with previous experience and knowledge). In problem solving, the relationships between parts of a problem determine difficulty. A solution can become easy when you recognize the parts to a difficult problem. Emphasizes insight learning. Insight learning comes easiest when one lets go of the perceived constraints. Also through incubation, if you ignore a problem solving block, it can help you solve the problem.

Who found that subjects exposed to a prior problem that was similar by analogy were more likely to solve a problem than those without this experience?

Gick and Holyoak

Recognize the Wason selection task from a description and identify the percentage of subjects getting the Wason selection problem correct.

Imagine that each square below represents a card. Suppose that you are participating in a study in which the experimenter tells you that every card has a letter on one side and a number on the other side. You are then given this rule about these four cards: "IF A CARD HAS A VOWEL ON ONE SIDE, THEN IT HAS AN EVEN NUMBER ON THE OTHER SIDE." Your task is to decide which card (or cards) you would need to turn over, so that you can find out whether this rule is valid or invalid. -EJ67. Wason (1968) found that people show a confirmation bias; they would rather try to confirm or support a hypothesis than try to disprove it. When people try this classical selection task, they typically choose to turn over the E card. This strategy allows the participants to confirm the hypothesis by the valid method of affirming the antecedent, because this card has a vowel on it. If this E card has an even number on the other side, then the rule is correct. If the number is odd, then the rule is incorrect. As discussed, the other valid method in deductive reasoning is to deny the consequent. To accomplish this goal, you must choose to turn over the 7 card. The information about the other side of the 7 card is very valuable. In fact, it is just as valuable as the information about the other side of the E card. Remember that the rule is: "If a card has a vowel on its letter side, then it has an even number on its number side." To deny the consequent in this Wason Task, we need to check out a card that does not have an even number on its number side. In this case, then, we must check out the 7 card. We noted that many people are eager to affirm the antecedent. In contrast, they are reluctant to deny the consequent by searching for counterexamples. This approach would be a smart strategy for rejecting a hypothesis, but people seldom choose this appropriate strategy

List Greeno's three categories of classified well-defined problems.

Inducing Structure: require the discovery of a pattern that can connect the parts of the problem. Ex. Visual Analogy. Transformation: require manipulation of objects or symbols in accordance with rules. Ex. Algebra problems. Arrangement of Elements: elements of the problem must be rearranged to achieve a goal. Ex. Coin Problem.

Explain how routine problems and insight problems differ in terms of people's experiences of them, according to Metcalfe and Wiebe.

People were accurate in predicting whether they'd be successful in solving routine problems but not in predicting success with insight problems. Solutions to the insight problems seemed to come suddenly, without warning.

What is an algorithm in problem-solving? a. A set of iterative rules that consistently whittles down a problem b. A mathematical procedure that solves most problems when successfully applied c. A fixed, exhaustive, and sometimes brute-force method that will produce a solution if properly applied d. A rule of thumb that can sometimes lead to a quick solution, but can also fail

a. A set of iterative rules that consistently whittles down a problem

A well-defined problem has what three components? a. A start state, rules for moving from state to state, and a goal state b. A start state, several intermediate states, and a goal state c. Several possible beginnings, rules, and a goal state d. An algorithm, a heuristic, and a goal

a. A start state, rules for moving from state to state, and a goal state

The tendency to choose an option because it is readily recalled from memory is known as the ______ heuristic: a. Availability b. Frequency c. Maximum likelihood d. Representativeness

a. Availability

Which of the following is the best example of a well-defined problem? a. Constructing a proof in algebra b. Figuring out how to tell your mother that you eloped c. Creating a guest list for a party d. Finding a detour around a traffic problem e. Writing a paper for your cognition class

a. Constructing a proof in algebra

Mental set in problem solving refers to one's tendency to do which of the following? a. Continue to use a strategy that worked in the past even if it is not the best for the problem at hand b. Use a method or tool only for its original intended use c. Follow a systematic plan in moving through the problem space d. Eliminate solution pathways that lead to contradictions

a. Continue to use a strategy that worked in the past even if it is not the best for the problem at hand

Adoption of a rigid mental set toward an object, in which you cannot see alternative uses or unconventional uses, is called: a. Functional fixedness b. Ill-defined thinking c. Incomplete representation d. Object set e. Well-defined thinking

a. Functional fixedness

Confirmation bias is a common human tendency that contradicts which of the following important components of the scientific method? a. Hypothesis testing b. Theory building c. Generalization d. Data analysis

a. Hypothesis testing

It is easier to say that an elephant is larger than a giraffe than it is to say a rat is larger than a mole. This is a common behavioral trait called the _________ effect. a. Semantic congruity b. Mental imagery c. Typicality d. Symbolic distance

a. Semantic congruity

an often complex rule or procedure that always produces the correct answer if followed correctly

algorithm

Why does human problem solving often rely upon heuristics?

algorithmic solutions often don't exist for complex problems, are tedious, or overwhelming

a conceptual structure consisting of a set of rules or ideas is mapped onto another conceptual structure Ex. Eyes are to vision as ears are to hearing.

analogical strategy

a rule in which we judge the probability of an event on the basis of how easily instances of the event can be remembered, but memory is not perfectly correlated with objective frequency, causing errors

availability heuristic

An illicit conversion is exemplified by which of the following statements? a. If some A are B, then some B must be A b. If all A are B, then all B must be A c. If all B are A, then some A must not be B d. If some B are not A, then all A must be B

b. If all A are B, then all B must be A

1st conceptual structure Ex. "Eyes are to vision..."

base domain

Analogical reasoning is a special case of ______ reasoning. a. Conditional b. Deductive c. Inductive d. Probabilistic

c. Inductive

The representativeness heuristic in decision making describes how people tend to do which of the following? a. Remember similar situations and come up with good choices made in the past b. Trade off potential gains and losses c. Judge how well a sample represents a population d. Choose between a small reward now or a bigger one later

c. Judge how well a sample represents a population

In problem solving, a strategy known as _________ can work by leading to intermediate solutions that are closer to the final goal. a. Working backwards b. The maximin heuristic c. Means-end analysis d. The closing algorithm

c. Means-end analysis

The symbolic distance effect can be found in tasks involving judgements between words or symbols. In general, what is that effect? a. Large differences between the objects symbolized produce longer judgement times b. Large words take longer to judge than small words c. Small differences between the objects symbolized produce longer judgement times d. Large objects take longer to judge than small objects, regardless of the words use to symbolize them

c. Small differences between the objects symbolized produce longer judgement times

theory that focuses on optimal, rational decisions made through the use of expected values

classical decision theory

tendency to look for evidence that confirms a hypothesis, but not for evidence that would falsify it. Ex. The Wason Selection Task

confirmation bias

thinking about alternative possibilities for past or future events. You imagine the consequences of something that is contrary to what actually happened Ex. "If Lee-Harvey-Oswald had not shot JFK, then someone else would have" and "If Lee-Harvey-Oswald had not shot JFK, then the sky would have rained marshmallows."

counterfactual reasoning

A syllogism is a classic example of _______ reasoning task. a. A reductive b. An inductive c. A productive d. A deductive

d. A deductive

What is a method that is not guaranteed to produce a problem solution, but is a rule of thumb that might find a problem solution? a. An algorithm b. An analogy c. A means-ends test d. A heuristic

d. A heuristic

When one recalls the solution to an old problem and uses it to solve a new, similarly structured problem, one has reasoned by: a. Analysis b. Introspection c. Working memory d. Analogy e. Backtracking

d. Analogy

What common aspect of human behavior is most antithetical to the scientific method of inquiry? a. Rationalism b. Solipsism c. Conformity bias d. Confirmation bias

d. Confirmation bias

Inductive reasoning involves which of the following? a. Deriving logical conclusions from general premises b. Generating expected utilities from expected values c. Using general principles to generate specific examples d. Generalizing from specific examples to general principles

d. Generalizing from specific examples to general principles

changes that remove an unusual event from the story Ex. If Mr. Jones had taken his usual route rather than a different one, he would have avoided the accident.

downhill changes

Which of the following is an example of an ill-defined problem? a. Constructing a proof in geometry b. Solving the Tower of Hanoi problem c. Solving Rubik's Cube puzzle d. Solving an algebra problem e. Putting together your schedule of classes for next semester

e. Putting together your schedule of classes for next semester

an inability to think of or consider anything but the customary uses for objects and tools

functional fixedness

generating possible solutions and testing them. Very useful for smaller problems which constrain the possible solutions to a manageable few

generate and test heuristic

ultimate solution to the problem

goal

a short-cut strategy or rule of thumb that might not produce the correct answer. Human problem solving often relies upon this

heuristic

searching for an operator that will take you (apparently) closer to the goal

hill climbing heuristic

the after-the-fact judgement that some event was very likely to happen, even though it wasn't predicted beforehand. A bias in which otherwise plausible outcomes are now less easy to imagine than the outcome that actually happened

hindsight bias

changes where one detail in the story is replaced by another of comparable likelihood Ex. Mr. Jones arrives at the intersection three seconds earlier, thus avoiding the accident.

horizontal changes

a deep, useful understanding of the nature of a problem. Frequently a sudden "aha" experienced with difficult problems Ex. Wolfgang Kohler and chimps Sultan and Grande

insight

better transfer occurs when elements of the base domain map onto corresponding elements in the target domain

mapping of problem structure

repeatedly determining the difference between the current state and the goal or subgoal state, and finding an operator (or means) that reduces this difference. Has been used in problem-solving computer models, such as Newell and Simon's (1972) General Problem Solver (GPS). Modern Ex. Keys locked in car

means-end analysis heuristic

To become accustomed to a single approach or way of thinking about a problem, making it difficult to recognize or generate alternative approaches. A tendency to see things in a certain way, even though other ways are better or equally good

mental/negative set

the set of legal moves that can be performed during problem solving

operator

high surface similarity between the base and target domains is beneficial

problem similarity

What 3 factors are important in determining the usefulness of analogies with the multi-contraint theory?

problem similarity, mapping of problem structure, and purpose

the initial, intermediate, and goal states in a problem and the problem solver's knowledge and any external resources that can be used to solve the problem

problem space

better transfer occurs when the purpose of problem solving is shared between the base and target domains

purpose

A judgment rule in which people estimate the probability of an event by: How similar the event is to the population of events it came from; Whether the events seems to be similar to the process that produced it

representativeness heuristic

finding an acceptable or satisfactory solution to a problem, even though the solution may not be optimal

satisficing

involves a mental construction or imagining of outcomes - a forecasting of how some event will turn out or how it might have turned out under different circumstances

simulation heuristic

an intermediate goal that must be achieved to reach a final goal

subgoal

2nd conceptual structure Ex. "...ears are to hearing."

target domain

a version of the simulation heuristic involving the undoing of some outcome by changing the events that led up to it. Uses Counterfactual Reasoning: when a line of reasoning deliberately contradicts the facts in a "what if" kind of way

undoing heuristic

changes that bring an unlikely event to the story Ex. Mr. Jones had a flat tire shortly after leaving work that day.

uphill changes

a word-for-word transcription of what the subject said aloud during the problem-solving attempt

verbal protocol

beginning at the goal state and working back to the starting state. Especially useful for complex problems when the goal state is known but the starting state and the paths leading from it are unclear. Ex. Reverse Engineering

working backward heuristic