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Chapter 10: Experimental Designs (Six steps to conduct ED (Selection and…
Chapter 10:
Experimental Designs
Variables
Independent - v that is investigated
dependent - v affected by the change in IV
Six steps to conduct ED
Selection and definition of the problem
Statement of a hypothesis indicating a causal relationship between variables
Selection of participants and instruments
Random selection of a sample of subjects from a larger population
Random assignment of members of the sample to each group
Selection of valid and reliable instruments
Selection of a research plan
Comparison of two different approaches
Comparison of new and existing approaches
Comparison of different amounts of a single approach
Execution of the research plan
Sufficient exposure to the treatment
They need to be substantively different treatments
Analysis of data
Formulation of conclusions
Manipulation & Control
Manipulation
of the independent variable
Active variables are those the researcher actively manipulates
e.g. Choice of an instructional strategy; a particular counseling approach
Assigned variables are those that cannot be manipulated by the researcher but are of interest
e.g. Gender, race
Control - efforts to remove the influence of any extraneous variables that might have an effect on the dependent variable --> assured the only differences between groups is that related to the independent variable
Participant variables – characteristics of the subjects
e.g. Pre-existing achievement levels; Differences in attitudes
Environmental variables – characteristics of the context
e.g. Learning materials; Differences in the time available for treatment between groups
Validity
control internal v --> decrease external v
control external v --> decrease internal v
internal v first; then external v
Internal - the degree to which the results are attributable to the independent variable and not some other rival explanation
threats to Internal v
History:an event occurs not related to IV
Maturation: Ss change over time
Testing: Exposure to pretest might improve scores on posttest
Instrumentation: Reliability, Validity, and not using the same test
Statistical regression: Regression to the mean
Differential selection of participants: Groups might be different outside of IV
Mortality: Ss drop out of the study
Selection-maturation interaction, etc.: Groups grow at different rates not due to the IV
External - the extent to which the results of a study can be generalized
Population validity – generalizations related to other groups of people
Ecological validity – generalizations related to other settings, times, contexts, etc.
Threats to external v
Pre-test treatment interaction: Taking the pretest impacts the treatment itself.
Multiple treatment interference: More than one treatment/ experiment performed (old impacts new)
Selection treatment interaction: Who is in your sample impacts the results.
Specificity of variables: Not specific enough in the following areas to replicate the study or know if generalizable
Participants
Operational definition of the treatment
Operational definition of the dependent variable
Specific times
Specific circumstances
Treatment diffusion: Two groups talk to one another and share treatment information so that they are not in effect one group.
Experimenter effects: Something about the experimenter changes the outcome of the DV.
Reactive arrangements: Something about the Ss changes the outcome of the DV. Some examples of this are: reaction to the environment, reaction to the attention from the researcher, placebo effect, and novelty effect.
Extraneous variables must be controlled to be able to attribute the effect to the treatment
Group equivalency must be assured
how to achieve control
Randomization
Selection – controls for representation
Assignment – controls for group equivalency
Matching
Identifying pairs of subjects “matched” on specific characteristics of interest
Randomly assigning subjects from each pair to different groups
Difficulty with subjects for whom no match exists
Comparing homogeneous groups
Restricting subjects to those with similar characteristics
Restricting subjects results in problems related to generalization
Using subjects as their own controls
Multiple treatments across time
Problem with carry-over effects
Analysis of covariance (ANCOVA)
Statistically adjusting the posttest scores for the subjects in each group for pretest differences that existed at the beginning of the study
Creates statistically equivalent groups
Holding variables constant
Using only males rather than males and females
Selecting teachers with only similar levels of experience
Selecting only one grade level
Group Designs
Single-variable designs – one independent variable
Factorial designs – two or more independent variables
experimental designs
Pre-experimental designs
One-shot case study
x o
One-group pretest-posttest design
O X O
Static group comparison
X1 O
X2 0
Experimental designs
Pretest-posttest control group design
R O X O
R O O
Posttest only control group design
R X O
R O
Solomon four-group comparison
R O X O
R O O
R X O
R O
Quasi-experimental designs
groups may be randomly assigned, not Ss
Non-equivalent control group design
O X O
O O
Time series design
O O O O X O O O O
Counterbalanced design
O X1 O X2 O X3 O
O X3 O X1 O X2 O
O X2 O X3 O X1 O
Factorial Designs
2 IV; 1 DV
examples
-The effect of teaching strategy and gender on students’ achievement
The effect of a particular counseling technique and the clients’ ethnicity on the success of the treatment
The effect of a specific coaching approach and children in three age groups on the ability to perform certain physical tasks
Interactions The degree to which changes in the dependent variable are different depending on the levels of each of the independent variables
e.g. A particular instructional strategy is more effective for males than females
graph: parallel lines indicate no interaction
non-parallel lines indicate an interaction