Distinguish between thinking, problem solving, and reasoning (p. 412).
Thinking: mentally representing some aspects of the world and
transforming these representations so that new representations, useful to
our goals, are generated
Problem solving: set of cognitive processes that we apply to reach a goal
when we must overcome obstacles to reach that goal
Reasoning: cognitive processes we use to make inferences from
knowledge and draw conclusions
Describe the structure of a problem, including the initial state and the goal state
There are three parts to a problem
Goal state: where you want to be at the solution of the problem
Initial state: where you are now as you face the problem that
needs to be solved
Set of operations that you can apply: the actions to get from the
initial state to the goal state
Compare well-defined problems to ill-defined problems, including special
mention of insight problems (p. 415).
Well-defined problems: problems in which the initial state and the goal
state are clearly defined at the possible moves are known
Ill-defined problems: problems in which the initial state, the operations,
or even the goal of the problem are unknown. The problem solver must
find the constraints that apply to particular situations
Insight problems: a special case of ill-defined problems that is
characterized by a sudden “flash of understanding” despite all of
the unknown factors
Define problem space theory (pp. 416-417).
Developed by Newell and Simon
The set of states or possible choices that faces the problem solver at each
step in moving from initial state to goal state
Compare and contrast problem solving heuristics, including random search, hill
climbing, means-ends analysis, and verbal protocol analysis (pp. 417-421).
Problem solving heuristics: a rule of thumb that usually, but not always,
gives the correct answer in a rather quick fashion. An algorithm is a much
more accurate procedure for problem solving though tends to take much
Random search: the simplest and least demanding heuristic that is
characterized by a process of trial and error. We frequently resort
to this when everything else has failed.
Hill climbing: problem solver looks one move ahead and chooses
the move that most closely resembles the goal state. This is often a more reliable heuristic than random search but can lead the
problem solver astray
Means-ends analysis: the problem is broken into sub-problems.
This is often a more demanding but more successful heuristic
Verbal protocol analysis: the analysis of the thought process of
the problem solver as described aloud by the solver in the course
of working on the problem.
Identify what areas of the brain are involved in problem solving, as have been
identified through neuroimaging techniques and brain damage patients (p.
In healthy participants who are monitored while performing problem
solving tasks, the right dorsolateral prefrontal cortex, bilateral parietal
cortex and bilateral premotor cortex were activated. These regions are
heavily associated with working memory and executive processes.
Discuss how working memory might be involved in problem solving (p. 421).
When a problem solver is determining what operations are required to
reach goal state using goals and sub-goals, working memory must be
used to recall these tasks.
Describe how expert problem solvers differ from novices in their organization
and encoding of the problem, and direction of search (pp. 423-424).
Experts typically know more information about a particular topic than
Novices often organize concepts in terms of surface features whereas
experts organize in terms of deeper abstract principles.
This is because novices and experts encode information differently
Experts chunk information and can access related chunks of
knowledge from long term memory thus making their problem
solving more efficient
Define analogical reasoning, including the identification of the five sub-
processes involved (pp. 424-427).
Analogical reasoning: a process of comparison, using knowledge from
one relatively known domain and applying it to another domain. Trying
to think of a problem with similar characteristics that have been solved
before and either use or adapt that solution to the present problem
Five sub-processes involved
Retrieval: holding a target in WM while accessing a similar
example from LTM
Mapping: holding both source and target in WM while also
aligning the source and target with similar sources
Evaluation: is the analogy useful?
Abstraction: isolating the structure shared by source and target
Predictions: developing hypotheses about the behavior of the
target from what is known about the source Compare and contrast Structure Mapping Theory (SMT) and the LISA model as
theories of analogical reasoning (pp. 427-428).
Structure mapping theory (SMT)
Stage 1: LTM is searched for potential sources that have a
superficial feature that is contained in the target
State 2: how good does a match exist between what was retrieved
in the first stage and the target
Although structural similarity is the key component of analogical
reasoning, the human cognitive system looks for superficial
matches when searching memory for possible sources and we find
it difficult to retrieve true relational analogs
LISA model (learning and inference with schemas and analogies)
Mechanisms that are like neural networks that features both
source and target may be considered as nodes in a network
Target is represented in terms of the activations of features of the
Describe inductive reasoning, including category-based induction (p. 429).
Inductive reasoning: any thought process that uses our knowledge of
specific known instances to draw an inference about unknown instances
Category-based induction: either generalizing from known instances to
all instances or generalizing from some members of a category known to
have a given property to other instances of that category
Identify and describe the different strategies used in general inductions
Describe the components of specific inductions, including the premise and the
conclusion (pp. 432-433).
Describe the similarity-coverage model, and give examples (p. 434).
A model of category-based induction
Underlying the typicality effects observed in inductive reasoning
is the notion of coverage
Describe how deductive reasoning relies on syllogisms (p. 437).
Syllogisms: arguments that consist of two statements and a conclusion.
The conclusion may be either true or false. A conclusion that follows
from the two statements is a valid conclusion
The premise of deductive reasoning is that a valid conclusion follows
from the premises as a matter of logical necessity
Compare and contrast categorical and conditional syllogisms (pp. 437-440).
Categorical syllogism: relations between two categories of things
Often represented in venn diagrams Conditional syllogisms: consists of two premises and a conclusion
that follow the if p than q statement
Discuss what types of errors are often witnessed in deductive thinking, including
form and content errors (pp. 440-443).
Form errors: result from errors in the structural form or format of the
Atmosphere effect: the use of “some, all, or no” in the two
premises conveys an overall mood that leads participants to
accept a conclusion containing the same term
Matching bias: accepting a conclusion as valid if it contains the
syntactic structure of the premises or some of the terms of the
Strongly influenced by quantifiers (some, all, no) used in
Content errors: logical deductions should be influenced only by the
structure of the premises however due to a world where content is often
important, we focus on the truth or falsity of individual statements in the
syllogism while ignoring the logical connection between statements
Belief-bias effect: tendency to be more likely to accept a
believable conclusion to a syllogism than an unbelievable one
Compare and contrast the various theories of deductive reasoning, including
rule-based approaches and mental models (pp. 443-446).
Ruled-based approaches: deduction depends on formal rules of inference
akin to those of a logical calculus
Humans naturally possess a logical system that enables us to
We attempt to solve deductive reasoning problems by generating
sentences that link the premises to the conclusion
Mental models: internal representations of real or imaginary situations
that can be derived from information such as that in syllogisms.
Constructed that best represents the information in the premises
A tentative conclusion is generated and evaluated to be
determined if it’s consistent with the model derived in the first
Must be validated
Provides a good account for both form and content errors in
Describe the linguistic versus spatial differentiation in reasoning (pp. 446-447).
Linguistic model: because deductive reasoning involves language-like
properties of representations, we should see activation of the left-
hemisphere language structures such as frontal and posterior temporal
regions Patients with left hemisphere damage have a deficit in simple
deductive reasoning tasks
Spatial model: in order to reason we create spatial representations of
linguistic information and we would expect to see activation of the
visual-spatial perceptual structures such as the parietal and occipital lobes
Significant activations in right middle temporal cortex and right
inferior frontal gyrus for a similar task of deductive reasoning
Explain what motor cognition is (p. 452).
Mental processing in which the motor system draws on stored
information to plan and produce our own actions, as well as to anticipate,
predict, and interpret the actions of others.
Identify the difference between movement and action (pp. 452-453).
Movement is a voluntary displacement of a body part in a physical space
Action is a series of movements that must be accomplished to reach a
Describe the perception-action cycle and the role of intentions (p. 453).
Perception-action cycle: transformation of perceived patterns into
coordinated patterns of movement. It relies on a sophisticated set of
Role of intentions: intentions are mental plans that are designed to
achieve a goal through action. The contents of both perceptions and
intentions depend on neural processes with both perceptual and motor
aspects working together
Locate and describe the three parts of the brain that are involved in motor
processing (pp. 453-454).
M1: responsible for specific movements
SMA: supplementary motor area is responsible for the planning of an
PM: premotor area that is responsible for generalized or less precise
Describe how shared motor representations complement our social environment
Shared motor representations: our ability mentally to represent actions
made by other people