Psyc 70 - ucsd

Epistemology

the philosophical study of where knowledge comes from

Personal experience

it happened to me

Intuition

it feels correct

Authority

a respected source says it's true

Science

using rationalism to derive hypothesis from theory; using empiricism to systemically test hypothesis

Rationalism

using formal logic (if A then B) to draw a conclusion from premise

Empiricism

observation through the sense (directly or indirectly)

Availability heuristic

things that come easily to mind seem more likely

Hindsight bias

things seem obvious after you know the outcome

Confirmation bias

looking for evidence that confirms our beliefs

Bias about bias

other people are biased; we aren't

Scientific method

systematically guards against biases

Theory

A set of principles that explain how something works.

Hypothesis

If the theory is true then this prediction must be true; it tests the validity of the theory.

Systematic observation

An empirical process that can be an experiment.

Generative Strategy Hypothesis

Learning strategies that require students to select, organize, and integrate learning material will lead to better learning outcomes than those that don't.

Generative Strategies

Learning strategies that involve actively constructing knowledge.

Self-explaining

A generative strategy where students explain material to themselves.

Summarizing

A generative strategy involving condensing information into a shorter form.

Mapping

A generative strategy that visually represents relationships between concepts.

Self-testing

A generative strategy where students test their own knowledge.

Teaching others

A generative strategy where students explain concepts to others.

Falsifiability

The principle that a theory must lead to a hypothesis that could fail to support the theory when tested.

Parsimony

The preference for the simplest explanation among competing hypotheses.

Applied research

Research conducted with a practical problem in mind.

Basic research

Research aimed at enhancing the general body of knowledge.

Pseudoscience

Claims that are not directly supported by empirical evidence and appeal to experience, intuition, or authority.

Variables

Things that vary and must have at least two levels.

Constant

A variable that has only one level in the study in question.

Frequencies

The rate or degree of a single variable.

Correlations

A relationship where one level of a variable is associated with a particular level of another variable.

Causal relationship

A relationship where one variable is responsible for changing another.

Measurement

The process of assigning numbers or categories to individuals in your sample.

Construct

Ideas we care about that cannot be observed directly.

Observable variable

Things we can observe that tell us about the construct.

Operational definition

The way a researcher defines a construct as an observable variable in a particular study.

Operationalize

The process of turning a construct into a variable.

Population

The group of people you are interested in studying

Sample

The actual subset of people you analyze

Sampling method

How the subset is chosen from the population

Convenience sampling method

What is most convenient to sample, it is a bias

GOAL

Study a representative subset of the population. Research strategy & statistical inference

Research strategy

The empirical approach used to gather data

Statistical validity

Extent to which a study's statistical conclusions are accurate/reasonable

Quantitative research

Draws statistical conclusions, assigns numbers to the variables you measure, analyzes results using statistics

Qualitative research

Draws descriptive conclusions, includes methods such as interviews, focus groups, and participant observation

External validity

How well results of a study represent the people or context besides those in the original study

Sampling bias

Non-representative samples make it difficult to generalize to the population

Novelty effect

Being in a study can cause participants to behave strangely

Operational definitions

Results could be specific to choice of operational definition

Internal validity

How sure are you that X causes Y? Requires eliminating alternative explanations for the relationship

Experiment

Research design in which at least one variable is manipulated by the researcher

Extraneous variable

Anything other than the manipulated variable that might be influencing the observed effect

Independent variable (IV)

Any variable that the researcher intentionally manipulates, generally thought to be the cause of the change in the dependent variable

Dependent variable (DV)

Any variable that the researcher measures as an outcome of the study, generally thought to be the effect of the manipulation of the independent variable

Directionality problem

Don't know whether X causes Y or Y causes X

Third variable problem

Some unidentified variable is responsible for the observed relationship between two variables

Control group

No treatment or neutral condition

Treatment group

The group in an experiment that receives the treatment or intervention

Confound

Alternative explanation for relationship between independent variable (IV) and dependent variable (DV)

Design confound

Mistake in the design of the IV, such that a second variable varies systematically with the IV

Systematic variability

Variability that varies in step with the IV, leading to a confound

Unsystematic variability

Random or haphazard difference that is not a confound

Selection effects

Participants in one level of the IV are systematically different from those in the other

Random assignment

Method used to fix selection effects by randomly assigning participants to conditions

Between subjects design

Experimental design in which different groups of participants are placed into different conditions

Within-subjects design

Experimental design in which each subject participates in all experimental conditions

Posttest-only design

Participants randomly assigned to a condition and tested on the dependent variable once

Pretest/posttest design

Participants randomly assigned to a condition and tested on the dependent variable twice: before and after exposure to the IV

Advantages of within-subjects designs

Participants in the two groups will be equivalent, requires fewer participants than between-subjects design

Order effects

Exposure to one level of the IV influences responses to the next level

Practice effects

Improvement or decline in performance due to experience or fatigue

Carryover effects

Contamination that carries over from one condition to the next

Counterbalancing

Presenting levels of IV in different sequences to avoid order effects

Demand characteristic

Cue that leads participants to guess the experiment's hypothesis

Design confounds

Setting or context differs across treatment conditions

Control for design confounds

Hold everything except the IV constant across conditions

Control for selection effects

Use random assignment

Time-related confounds: Maturation

Subjects naturally change physiologically or psychologically between treatment conditions

Control for maturation

Use a comparison/control group that can control for maturation (should affect both groups equally)

Time-related confounds: History

An outside event occurs between treatment conditions and affects dependent variable in condition(s) subsequent to event

Control for history

Use a comparison/control group that can control for history (should affect both groups equally)

Time-related confounds: Regression to the mean

Extreme scores in first treatment condition statistically likely to become less extreme in subsequent conditions

Control for regression to the mean

Use a comparison/control group to help detect extreme scores (should be equivalent prior to treatment)

Time-related confounds: Attrition

Subjects drop out of the study before completing all conditions

Control for attrition

Remove participants who dropped out from pretest average and analyze pretest scores for differences

Time-related confounds: Order effects

Experience in first treatment condition causes a change in subjects that affects performance in subsequent conditions

Control for order effects

Use counterbalancing

Time-related confounds: Instrumentation

Change in measurement instruments between treatment conditions affects measurement of dependent variable

Control for instrumentation

Use fixed tests and a control group (any shifts should affect both groups equally)

Observer bias

Researchers' expectations influence results (tendency to see what we expect to see)

Demand characteristics

Participants guess study hypothesis and change behavior

Placebo effects

Participants improve because they believe they are receiving a valid treatment

Masking (blinding)

Concealing which condition participant has been assigned to

Double-masked study (double-blind)

Neither participants nor researchers know what condition they are in

Control for placebo effects

Use an active control group that creates the same expectation of improvement as treatment group

Observable variables

A quantity or quality that can be observed directly and varies across individuals

Stress

An adaptive response to a perceived danger or threat that involves physiological, cognitive, affective, and behavioral components.

Social readjustment scale

Stressful events in the last year.

Daily hassles & uplifts scale

Daily stressors.