# Research Design Methodology Part 1. Objectives  Qualitative  Quantitative  Experimental designs  Experimental  Quasi-experimental  Non-experimental.

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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

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 O 1  Pre-test/post test  R O 1 T O 2  R O 3 O 4 Experimental group R Control group R Pre-test O 1 Pre-test O 3 Treatment T Post-test O 2 Post-test O 4 R = Random N = Non-random O = Test/measurement T = Treatment Both groups measured at the same time

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 Pretest- Posttest Design  NA O 1 TO 2 NB O 3 O 4  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 5 th 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 quasi- experimental?  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+  Weaknesses: Selection differences, time 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.

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

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