CPSY 3308 W Exam 1

observer drift

straying from coding standard (do not want this) can't just change what you're doing

internal validity

-ability of research design to test hypothesis -causality

reliability

-consistency or repeatability of a measure -will repeated application yield similar values -importance of coding system and/or proper operationalism

cross sectional design

-different participants studied at one point in time ex: 3 and 4 year olds in ToM task classic pencil task

inter-rater reliability

-do different judges agree independently? ex: olympic judges

primary source

-does it contain the results of a single research study/experiment? -terms like book, chapter, "review", "summary" "met analysis", and "synthesis" usually signal a secondary source review article

external validity

-generalizability -controlled lab

theories

-integrated set of principles, concepts, and/or ideas -organized belief/framework about behavior and/or development -testable -makes predictions about future behaviors Good theories are: parsimonious falsifiable

microgenic design

-longitudinal studies document results (products) of change -what happens *what Ss is like at T1 T2 T3 etc *no info about how change happens *no info about everything that happens between T1 and T3 -"movie" of development -repeated high density observations across period of change is happening -process of change (how it happens)

face validity

-look at operationalization and see whether it 'looks good' eg; depression measure that looks at childs affect -weakest, passes PORI test

time lag design

-looks at historical changes -same age at different points in time -difference you find in 10 year olds reflect: --generational factors (main confound in cross sectional design) --time of measurement factors (main confound longitudinal) -or both!

sequential design

-mix between cross sectional and longitudinal -cohort sequential design

scientific methods

-observe -invent idea consistent with observation -use idea to make predictions/hypotheses -test predictions -modify based on your results

testing effects

because they have taken test before, do better ex: doing better on exam 2

subject variable

characteristics of participants that might actually affect your study --self esteem, sex, age, native language, IQ --only "important" stuff related to the study's variable --sometimes treated as IV in developmental sciences

operational definition

define or represent ideas in terms of specific behaviors or concrete activities that anyone can witness or repeat

situational variable

describes characteristics of context --can be IV (usually) or DV ex: children in classroom

Hawthorne effect

doing better because someone you and paying attention

non-response bias

don't have quiet people talking

attrition

dropping out of research study

cohort

group of like individuals ex: group of ids in 20s much different than people in 20s 30 years ago

duration

how long does response last

latency

how long it takes to get this response

experimental bias

if you think it changes behavior, may notice it does

dependent variable

meausured variable, response, hopes it it changed by how researcher manipulates ex: amount of popcorn eaten

nominal

SCALES OF MEAUREMENT -categorical -no ordering -arbitrary--ex: pretend play as a function of sex, attachment classifications

applied research

- Investigate real-world issues -Generate information that can be applied directly to the solution of a real-world issue ex: Can a very young child open a crankhandled window?

authority

-INFO GATHERING

ecological validity

-Measure reflect what people do in real-world/real-life settings? -may effect the design of the study of the scale of measurement you use

longitudinal design

-some participants observed one or more times -look at similarities and differences in SAME individual as they age -waves (any time you assess) -ex: MN parent-child project

structured observation

-takes place in lab pros: all kids observed in same context -greater control Cons: -lab setting less "natural" for kids -may behave differently than they do in real life

hypothesis

-tentative statement about relationship b/t variables -involves specific testable predictions of observable behavior *children are born bad and need to be civilized (not scientific) *providing preschool children videos and books that contain characters who model sharing behavior will increase the amount of sharing they do during free play -stated so can be refuted or confirmed -data collection possible

secondary source

-terms like book, chapter, "review", "summary" "met analysis", and "synthesis" usually signal a secondary source review article

pilot study

-testing carried out prior to formal data collection, the goal being to refine the procedure and sharpen testing skills

basic research

-theory driven -confirm/disconfirm hypotheses -gather info about behavior/phenomenon -real world? -most university research ex: does the language you speak affect the categorization of objects?

test-retest reliability

-used to assess the consistency of a measure from one time to another -same test twice but... -alternative forms procedure (huge test bank)

narrative record

-write down a description of the behavior that was recorded -focus typically on one kid -strengths: completeness weakness: time consuming

empiracism

CANNONS OF SCIENCE gaining knowledge through systematic observation of the world

testability

CANNONS OF SCIENCE the assumption that explanations of behavior can be tested and falsified through observation

determinism

CANNONS OF SCIENCE the assumption that phenomena have identifiable causes

parsimony

CANNONS OF SCIENCE the assumption that the simplest explanation of a phenomenon is most likely to be correct

selection bias

Dewey phonecall

cliches

INFO GATHERING

folklore

INFO GATHERING

hindsight

INFO GATHERING we think we already know what we are learning -this is because previous info is used, makes new info easier to learn

literature review

Set of peer-reviewed primary/ empirical sources

translational research

Make the results of research applicable to the population under study

rival hypothesis

Might there bean alternative explanation for the results of your study?

lit search

Purpose: -define and limit topic -place study in historical perspective -avoid unnecessary and unintentional replication -select promising methods and measures -relate findings to previous knowledge and suggest further research -develop research hypothesis

interval

SCALES OF MEASUREMENT -ordered -constant scale -difference makes sense, ratios do not -no absolute zero -eg: temperature

ordinal

SCALES OF MEASUREMENT -rank order -different b/t values not mathematically important -ex: class rank, movie rating, Likert Scale, SES, ER pain scale

ratio

SCALES OF MEASUREMENT -ordered -constant scale -absolute zero -eg: weight, length

validity

accuracy of a measure measures what you intend to measure

correlation

an index of the strength and direction of the relation between two variables

intensity

extremity of response

internal consistency

form of reliability based on consistency of response across the different items of a test

maturation

naturally occurring changes in the Ss as a function of the passage of time during the study

frequency

number of times

subjective

personal perspectives/biased

historynarra

potentially important events occurring between early and later measurements in addition to the interdependent variables being studied

random assignment

procedure for assigning participants to experimental conditions in which each participant has an equal chance of being assigned to each condition

random sample

procedure for selection of research participants in which each member of the target population has an equal chance of being selected

double-blind

researcher and participants and others don't know what group they are in

independent variable

researcher can manipulate ex: genre of movie

sampling

selection of a sample of research Ss from a larger poulation

population

the total set of people, observations, or events within some domain

confound

threats to validity ex: experimenter bias, Hawthorne Effect can be confound, 3rd variable

expectancies

trying to confirm hypotheses, do't even realize you're doing it

objective

unbiased