Experimental and quasi-experimental research designs are explained together with the concepts on which quantitative research is based .

1. Exploiting Rapid
Change in Technology
Enhanced Learning
… for Post Graduate Education
Quantitative Methodology Part One

2. You can use all the quantitative data
you can get, but you still have to
distrust it and use your own
intelligence and judgment.
Alvin Toffler

3. Our Focus for Today
1. Some important concepts to keep in mind
2. Quantitative research: Characteristics and when to
use it
3. Types of quantitative research methods
4. Exercises to practice

4. Four Main Concepts
Philosophical
Paradigms
Research
Paradigms
Research
Designs
Research
Methods
General to
Specific

5. What Is a Philosophical Paradigm?
It is a basic image of what is
reality (ontology), how we know
something (epistemology), and
how we should find out
knowledge (methodology)

6. Taken from Weaver, K. & Olson, J.K. (2006, p.465)
What Is a Research
Paradigm?
A pattern of beliefs and
practices that regulates inquiry
within a discipline by providing
lenses, frames, and processes
through which investigation is
accomplished

7. Adapted from Wiersma, W. & Jurs, S.G. (2009)
What Is a Research Design?
A plan or strategy for
conducting a research
study. It includes decisions
on what, who, when,
where, how, means,
analyses, etc. It should
respond to the nature of
the research question

8. Adapted from Wiersma, W. & Jurs, S.G. (2009)
What Is a Research
Method?
A set of techniques or
strategies to gather and
analyze data that responds
to the chosen research
design

9. How Do These Concepts Apply to
Quantitative Research?

10. The Philosophical Paradigm
• Ontological assumptions (view of the world):
• There is one defined reality
• It is fixed, measurable, and observable
• Epistemological assumptions (how knowledge is created):
• Knowledge is objective and quantifiable
• Research should test and expand theory
• Methodological assumption (what should be done to get
knowledge):
• Use objective measurement and analysis to get valid
knowledge

11. The Research Paradigm
Positivist Paradigm
There is one objective reality
Quantitative research
paradigm

12. Adapted from Wiersma and Jurs (2009)
The Research Design
• Top-down logic (deductive)
• Looks for relationships, facts, and
causes
• Theory-based
• Focused on individual variables
• Context-free (generalizations)
• Researcher has a neutral role
• Statistical analysis

13. The Research Method
• Experimental
• Quasi-experimental
• Pre-experimental

14. When to Choose Quantitative Research
If you are interested in:
• Determining relationships, effects, and/or causes
• Testing theories, models, approaches (even if that
is not an explicit goal of the study, but theoretical
principles are important in one way or another)

15. Types of Quantitative Research
Methods

16. • Experimental: High degree of control.
Random selection or assignment
• Quasi-experimental: Minor level of control
because random selection or assignment is
not possible. Statistics is used to improve the
control of variables
• Non-experimental: Little or no control

17. Experimental Methods
• Posttest-only control group
• Pretest- posttest control group
• Solomon four groups
• Factorial

18. • Description: Two or more groups are compared using
posttest and random assignment of subjects and
treatment to control prior differences. One group does not
receive treatment
• Diagram: RG1 X1 O1 R = Randomization X = Treatment O = Posttest
RGn Xn On n= number of experimental treatments used
RGn+1
__ On+1 Control group (no treatment)
• Use: When it is necessary to establish if a variable has
effect or not and pretest is not acceptable or possible.
• Common statistical tests: t-test and analysis of
covariance if subject variables are involved
Posttest-Only Control Group Design

19. • Description: Two or more groups are compared using a pretest to
measure the dependent variable before the treatment is
administered. Such measurement is used as statistical control in the
analysis and random assignment of subjects assure equivalence of
the groups. One group does not receive treatment
• Diagram: RG1 O1 X1 O2 R = Randomization X = Treatment O = test
RGn O2n-1 Xn O2n n= number of experimental treatments used
RGn+1 O2n+1 __ O(2n+1) Control group (no treatment)
• Use: When it is necessary to establish if a variable has effect or not
• Threats to validity: Interaction effect of testing (threat to external
validity)
• Common statistical test: Analysis of covariance
Pretest-Posttest Control Group Design

20. • Description: To address the reactive effect of testing and interaction
of testing and treatment, two control groups are added to the
pretest-posttest control group design; one without taking pretest and
another one without pretest and treatment
• Diagram: RG1 O1 X O2
RG2 O3 - O4 R = Randomization O = Test X = Treatment
RG3 - X O5
RG4 - - O6
• Use: When resources and time are available to deal with the
complexity of four research groups
• Threats to validity: None by itself
• Common statistical tests: 2X2 ANOVA (disregarding pretests),
ANOVA plus 2X2 factorial design, or meta-analysis
Solomon Four Groups Design

21. • Description: The different levels of two or more independent variables (factors) are
considered to establish not only their effects on the dependent variable but also the
ones caused by the interaction among them. Theoretically, the number of independent
variables and their levels may be as needed. For example, a 2 X 3 X 5 means one
variable with 2 levels, another with 3, and the last one with 5
• Diagram: (Notation of a 2 X 2 factorial design)
R X11 O
R X12 O
R X21 O
R X22 O
R = Randomization X11 = Factor 1, level 1 X12 = Factor 1, level 2 X21 = Factor 2, level 1 X22 = Factor 2, level 2 O = Measurement
• Use: When measuring the interaction among variables is needed
• Threats to validity: None by itself
• Common statistical test: Factorial ANOVA, MANOVA, MANCOVA, multiple regression
analysis
Factorial Design
Drug Therapy
Placebo Drug A
Psycho-
therapy
None Control Drug A
Method A Method A Combined

22. Quasi-Experimental Designs
• Nonequivalent posttest-only control
group
• Nonequivalent pretest- posttest control
group
• Counterbalanced
• Time series

23. • Description: Two or more groups are compared using only
posttest. There is not random assignment of subjects since
they are already in groups
• Diagram: G1 X O1 X = Treatment O2 = Posttest n = number of treatments used
Gn Xn On
Gn+1 ___ On+1
• Threats to validity: Selection, statistical regression, and
reactive effect of testing
• Use: Only if some antecedent data establish extent of
similarity between groups
Nonequivalent Posttest-Only Control Group
Design

24. • Description: Two or more groups are compared using pretest and
posttest. Pretest scores are used for statistical control or for
generating gain scores. There is not random assignment of subjects
since they are already in groups
• Diagram: G1 O1 X1 O2 O= Test X = Treatment n= number of treatments used
Gn O2n-1 Xn O2n
Gn+1 O2n+1 __ O2n+2
• Threats to validity: Selection, statistical regression, and reactive
effect of testing
• Common statistical tests: Covariance and multiple regression
Nonequivalent Pretest –Posttest Control
Group Design

25. • Description: The order in which treatments are administrated is
changed during the study so as to test every subject for all the
considered conditions and control order effects in repeated
measures
• Basic Diagram :
G1 XA XB O
G2 XB XA O
X = Treatment G = Group O = Measurement
• Threats to validity: Multiple treatment interference
• Common statistical test: ANOVA
Counterbalanced Design

26. • Description: The dependent variable is measured several
times before applying a treatment and then a new series of
measurement is performed
• Diagram : O1 O2 … X Oi… On
X = Treatment O = Measurement
• Threats to validity: History and reactive effect of testing
• Statistical tests: They depend on the specific type of time
series designed
Time Series Design

27. Taken from The bmj
(2017)
Some Statistical
Tests

28. Pre-Experimental Designs
These designs will be explained in
the second session of the webinars
devoted to quantitative research

29. Exercises

30. Establish what research design is appropriate for
this study…
•Problem: A researcher has three different groups of employees
(engineers, administrators, sales personal) which are not
performing at the expected level. Data shows three different levels
of current performance: high, average, and low.
•Purpose: To determine the effects of different types of feedback
on employees’ performance
•Research Question: What is the effect of different types of
feedback over the performance of employees?
• Values of the independent variable: positive, negative, no
feedback

31. Establish what research design is appropriate for
this study…
•Problem: Faculty morale is low at a university according to
the results of a questionnaire applied.
•Purpose: To establish the effect of sensitivity training on
faculty morale
•Research Question: What is the effect of sensitivity training
workshops on faculty morale?
• Values of the independent variable: treatment, no
treatment

32. Establish what research design is appropriate for
this study…
•Problem: A new calculus program has been suggested to
improve students performance
•Purpose: To establish the effect of the suggested program
on students’ calculus scores
•Research Question: What is the effect of the suggested
calculus program on students’ scores?
• Values of the independent variable: treatment, no
treatment

33. Now do the same with your own study…
•Problem:
• Research Question:
• Research Design:
•Research Method:

34. Advanced Ideas for Today:
Your research question determines the method
you should use to gather data
Quantitative research asks for data that
generate valid and objective answers

35. Now you know
1. The paradigms behind quantitative
research
2. The experimental and quasi-
experimental methods you can use to
answer your research question(s)

36. References
Thebmj (2017). Study design and choosing a statistical test. BMJ
Publishing Group Ltd. Retrieved from
http://www.bmj.com/about-bmj/resources-
readers/publications/statistics-square-one/13-study-
design-and-choosing-statisti
Weaver, K. & Olson, J. K. (2006). Understanding paradigms used
for nursing research. Journal of Advanced Nursing, 53(4),
459-469. doi: 10.1111/j.1365-2648.2006.03740.x
Wiersma, W. & Jurs, S.G. (2009). Research methods in education:
An introduction (9th ed.). Boston, MA: Allyn and Bacon

37. What’s Up at MN & DN this summer?
1. VERY IMPORTANT – backwards map your summer work
2. 30 day writing challenge, 30 day work-life balance challenge, and 365s -
keep you in touch with your work
3. Group work – RLC writing OR
Lingerers

38. Avoid this one
1. VERY IMPORTANT – backwards map your summer work
2. 30 day writing challenge, 30 day work-life balance challenge, and 365s -
keep you in touch with your work
3. Group work – RLC writing OR Lingerers