Research Design
Methodology Part 1
Objectives
 Qualitative
 Quantitative
 Experimental designs
 Experimental
 Quasi-experimental
 Non-experimental
Research Design
 Plan for selecting subjects, research sites, and data collection
procedures to answer research questions
 Credibility
 Extent to which results approximate reality, are accurate &
trustworthy
 Reduced error
Research
Design
Experimental
Quantitative
Qualitative
QuasiExperimental
NonExperimental
Descriptive
Comparative
Mixed
Methods
Correlational
Qualitative Design
 Research where results are given in words
 In depth understanding
 Data collection
 Observations
 Interviews (open ended questions)
 Documents
 Identify patterns
 Study behavior in the natural environment
 Multiple realities, subjective
 Example….
Quantitative Design
 Research where results are given in numbers
 Specifically designed instruments & statistics
 Objectivity is critical
 Use data from a sample to generalize to larger population
 Look for:
 cause & effect
 relationships
 describe, predict variables
 Articles??
Experimental Design
 Researcher manipulates what the subject(s) will
experience
 give treatments and observe/measure to see if they
cause changes in behavior
 Manipulate independent variables & measure
dependent variables
 True experimental design has randomly assigned
treatment groups
 Only difference in groups is due to chance
Experimental Designs
 Notations:
 Post test only
 R
T
O1
R= Random
N= Non-random
O= Test/measurement
T = Treatment
 Pre-test/post test
 R
O1
 R
O3
T
O2
O4
Both groups
measured at the
same time
Experimental
group
R
Pre-test
O1
Control
group
R
Pre-test
O3
Both groups
measured at the
same time
Treatment
T
Post-test
O2
Post-test
O4
Experimental Designs
 Strengths:
 Random selection into groups…reduces error
 Best approach for determining cause-and-effect relationships
among variables
 High degree of control of extraneous variables
 Power of manipulation of variables
 Weakness/limitation:
 Experiments typically occur in laboratories
 Difficult to replicate the “real world”
Quasi-Experimental Designs
 Nonequivalent , non-random groups PretestPosttest Design
 NA
O1
NB
O3
T
O2
O4
 Uses intact already established groups of
subjects
 IWU/ISU basketball
 Classes
 Selection can be a major problem if one group
scores higher than the other because of a factor
Activity
 A researcher wants to test the effectiveness of 3 methods
of teaching a dance to a group of 5th graders. A local PE
teacher allows use of 3 of her classes. The researcher
administers a pretest to all students, each class receives
a different method of teaching for two weeks, and then
all students get a posttest.
 What type of design is it? Experimental or quasiexperimental?
 Write out a design notation
Non-Experimental Designs
 Researchers measure subjects in order to describe them
as they naturally exist without experimental intervention
 Don’t control/manipulate the environment
Non-Experimental Designs
 Types of non-experimental Design
 Descriptive
 Comparative
 Correlational
Relationships…when one variable varies
systematically to another variable
Non-Experimental Designs
Descriptive
 Summarize the current or past status of
something
 Describe attitudes, behaviors, characteristics
 Example
 What are the leadership styles of Athletic
Directors/Principals/Nonprofit CEOs
 Attitudes of students towards campus rec/athletics
Non-Experimental Designs
 Descriptive – 2 types
 Longitudinal (over time)
 Same cohort/group
 Weaknesses: Subject attrition, time
 Cross sectional (across groups)
 Different groups of subjects over time
 20-25; 30-35; 40-45; 46+
Longitudinal Alumni survey
* Survey same alumni
every 5 years
Cross Sectional Alumni
survey
* Survey alumni who have
been out 5, 10, 15 & 20
years one time.
 Weaknesses: Selection differences, time
Non-Experimental Designs
 Comparative
 Differences between 2+ groups
 Value of the DV in 1 group is different than the
value of the DV in the other group.
 Public schools vs. private schools
 D1 vs. D3
 Other examples…
Non-Experimental Designs
 Is there a difference…….
 in donations to athletic departments between public &
private institutions?
 in attitudes towards fitness between recreational volleyball
players, baseball players, & softball players?
 in fitness levels between youth who participate in structured
and unstructured recess?
Non-Experimental Designs
 Comparative
 Difference or similarity conclusions can be
made.
 Causal conclusions can not be made.
Non-Experimental Designs
 Correlational
 Relationships (correlational analysis)
 Gender & management style
 Predictions (regression analysis)
 Grad admissions criteria
 Predictor variable – Undergrad GPA
 Criterion variable – Grad GPA, GRE score
 March Madness success
 Predictor variables??
Non-Experimental Designs
 Correlational
 Correlation & Causation: never infer causation from
correlation
 High relationship does not mean one variable causes
another
 May be unmeasured variables affecting the
relationship
 Examples…
Non-Experimental Designs
Correlational
 Measuring the relationship between variables
 Correlation can be measured statistically
 Pearson’s correlation coefficient (r)
 Correlation coefficient (r) can range from –1 to 0 to 1
 Further from 0 = stronger relationship
 -1/1 is a perfect negative/positive relationship
 0 means no relationship
Mixed Methods Designs
 Utilize both qualitative & quantitative methods to
triangulate research results
 Sequential mixed methods
 Begins with 1 methodology then uses the other to
elaborate or expand findings
 Delphi Study
 Concurrent mixed methods
 Use both methodologies at the same time & merge
findings
Triangulation:
reach the
same
conclusion
using multiple
methods