quantitative research design - module 1 provides a basic understanding of quantitative research
DESCRIPTION
A basic understanding of quantitative design. The first module covers some terms used when conducting this type of study.TRANSCRIPT
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Curriculum Designed by
Dorothy Kropf
Quantitative Studies
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Instructor: Dorothy Kropf, M.A.
Doctoral Student of Education at Walden University
Specialization: Educational Technology
Area of Interest: Research and Higher Educational Issues
Module 1
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In a quantitative research design, the researcher poses several hypotheses to analyze the cause and effects of specific variables in order to predict and explain certain phenomenon (Creswell, 2009).
Quantitative Research Design
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To conduct a study, you must have a theoretical framework. What are you basing your research on?
Theoretical Framework
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What new questions or observations do you have?
Do you want to investigate a phenomenon?
Do you want to see if an intervention that worked for a small school will work in a larger school?
Deductive Reasoning
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Start with a research problem.
Deductive Reasoning
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Start with a research problem. A research problem is a question that stimulates a response through scientific inquiry.
Deductive Reasoning
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Quantitative research designs start with observations that need further explanations and theories. They make predictions that can potentially answer the hypotheses.
Quantitative Research Design
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Quantitative research designs are structurally scientific methods, utilizing deductive reasoning in forms of hypotheses (Price & Oswald, 2009).
Quantitative Research Design
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The outcomes measured in a quantitative research design are factual and based on data-driven information from specific measurement instrument(s) rather than from perceptions (Frankfort-Nachmias & Nachmias, 2008).
Quantitative Research Design
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The overarching goal of a quantitative research design is to draw relationships between dependent and independent variables, thereby assisting the researcher in developing generalizations that explain or predict certain phenomenon (Creswell, 2009).
Quantitative Research Design
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Variables and Unit of Analysis
According to Frankfort-Nachmias & Nachmias (2008), “the variable whose changes the researcher wishes to explain is known as the dependent variable, while the variable the researcher thinks induces or explains the change is the independent variable” (p. 49).
Quantitative Research Design
Wow! My kite flies higher when the wind blows harder!
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There are 3 types of measures in quantitative research designs:
1. Nominal
2. Ordinal
3. Interval
4. Ratio
Quantitative Research Design
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Example of Nominal measures:
01 = Female
02 = Male
Quantitative Research Design
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Example of ordinal measures:
College Education
1=some college courses taken
2=Associates Degree conferred
3=Bachelor’s Degree conferred
4= Master’s Degree conferred
5= Doctoral Degree conferred
Quantitative Research Design
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Example of Intervals:
Test Scores:
A: =90-100%
B = 80-89%
C= 75-79%
D= 70-74%
F= 69% and below
Quantitative Research Design
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Types of Quantitative Research Designs
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Experimental Design
A design in which the researcher controls and manipulates variables to determine cause and effects.
Quantitative Research Design
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Balanced Experimental Design: allows “equal number of observations” despite of the randomness of the study (University of Texas at Austin, n.d.)
Quantitative Research Design
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Correlational Research Design: A study that examines the relationship between variables and outcomes.
Hypothetical Example: There is a strong correlation (or link) with income and the type of car one drives. Again, this is only hypothetical – the more income a salesperson makes, the nicer his car....
Quantitative Research Design
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Quasi-experimental Design:
The researcher has control over the selected participants and the selected instrumentation. However, the researcher doesn’t have control over who will be exposed and when will the exposure occur.
Quantitative Research Design
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Single case research:
Continuous study of human behavior over time. Example: an intervention study
Quantitative Research Design
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Meta-analysis research
The researcher studies the aggregation of results with other relevant studies.
This type of research usually explores the effectiveness of a specific method (Frankfort-Nachmias & Nachmias, 2008).
.
Quantitative Research Design
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Properties or attributes a researcher would like to identify and measure.
Types of variables:
• Independent variable
• Dependent variable
• Control variable
Variables
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Independent variable is the variable that the
Researcher has control over. This means that this variable can be manipulated.
Independent Variable
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Is not a variable that a researcher can manipulate. Instead, a dependent variable can be observed and measured as a result of the variations of the independent variable.
Dependent Variable
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A variable that the researcher will keep constant.
Control Variable
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• To prepare for module 2:
• Review the terminologies in this module then decide on a quantitative study you would like to conduct.
• Identify what type of research design it is, what your variables are, and your research questions
End of Module 1
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Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage Publications.
Frankfort-Nachmias, C., & Nachmias, D. (2008). Research methods in the social sciences (7th ed.). New York: Worth Publishers.
Price & Oswald (2008). Experimental research. Retrieved from http://psych.csufresno.edu/psy144/Content/Design/Types/experimental.html
Price & Oswald (2009). Developmental research. Retrieved from http://psych.csufresno.edu/psy144/Content/Design/Types/experimental.html
Simon, M. (n.d.) Quantitative research: The “N” side in the paradigm war [PowerPoint slides]. Retrieved from https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=12&ved=0CDIQFjABOAo&url=http%3A%2F%2Fmyweb.cebridge.net%2Fkimblum%2FQuantitative%2520Researchpresentation.ppt&ei=x9cpU9_hMo7eoASg5oCwDw&usg=AFQjCNGnys3Q6t6w5sgnIyTIvd8rqcqmww&sig2=Eum26gRrDj_vW_RKKdtlwg
University of Texas at Austin (n.d.). The statistics glossary. Retrieved from University of Texas at Austin website: http://www.stats.gla.ac.uk/glossary/?q=node/543
Bibliography