Exam 2 - Section 6 Flashcards
What are the two critical elements of a true experimental research design?
(1) Manipulation or Control of the Independent Variables and (2) Randomization of participants to assure group “equivalency”
What are the main features or differences of Group Studies?
Reports made on the group performance, instead of individual scores; minimum number of participants per group; comparison of means and SD since the focus is on group data
What does the notation “R” stand for?
Random Assignment
What does the notation “X” stand for?
Experimental treatment/condition
What does the notation “O” stand for?
Observations or measurement
What are the key features of a Posttest-Only Design?
Randomization of participants to the control; manipulation of the independent variable; measurement/observation taken only after the treatment
What are the key features/elements of a Pretest-Posttest Randomized Control Group Design?
Randomization of participants; Pretest or baseline measurement; Manipulation of the independent variable; Posttest measurement after the treatment
What is one benefit of a Pretest-Posttest Randomized Control Group Design?
Assures the groups are similar before intervention (equivalency of groups)
What are the key features of the Solomon Randomized Four-Group Design?
Random of assignment of participants across all four groups; two groups have the pretest and two do not; two groups receive treatment or intervention and two do not
What is one benefit of the Solomon Randomized Four-Group Design?
Verifies that learning did not occur because of the pretest
What are the key elements of a Factorial Design?
Manipulation of two or more independent variables at the same time in the same study
What does a Factorial Design allow investigators to examine?
How each variable affects the outcome; how independent variables work together or influence one another (interaction effects); look at each factor independent from one another and see if the factors are contingent or interact with one another
What is a Main Effect in terms of a Factorial Design?
The effect associated with each independent variable; a significant Main Effect means there is a difference between the levels of one of the independent variables
What is an Interaction Effect in terms of a Factorial Design?
The independent variables work together or influence one another
What is Internal Validity?
The extent in which researchers’ conclusions about cause/effect relationships are accurate
What Aspects can Impact/Threaten Experimental Control (Important for Internal Validity)?
History, Instrumentation, Maturation, Selection, Mortality, and Statistical Regression
What is History in terms of Experimental Control Threats?
“Outside” influences that occurred during the course of a study; can influence the observed outcomes at the end of a study; Example: participants are distracted by news of a new strain of COVID-19, so they cannot focus on the study
What is Instrumentation in terms of Experiment Control Threats?
Changes in equipment or human observers; Example: during the pretest, you took measures for 15 minutes, but during the posttest you took measures for 30 minutes
What is Maturation in terms of Experimental Control Threats?
Performance influence by participants’ development or recovery; Example: you are conducting a study on stroke patients, but over time they begin to naturally recover from the stroke
What is Selection in terms of Experimental Control Threats?
Groups vary in some way; participants/groups differ in a systematic way, rather than in a random way, prior to a study; Example: those with a lower IQ score were placed in Group A, and those with a higher IQ score were placed in Group B
What is Mortality in terms of Experimental Control Threats?
Participants discontinue participation and loss may not be “random”; participants drop out before the end of a study; Example: participants with the lowest scores or those making less progress in treatment drop out of the study
What is Statistical Regression in terms of Experimental Control Threats?
Effect of repeated testing may cause change in some scores; effect of being tested repeatedly; Example: if a participant scores extremely high on a test, there’s a strong probability that the condition had nothing to do with it, and the next test taken will be closer to the mean/average score
