This is a North Central University paper about analyzing quasi-emperimental designs. It is written in APA format, includes references, and is graded an instructor.

1. OHAYNESEDR8205-3 1
NORTHCENTRAL UNIVERSITY
ASSIGNMENT COVER SHEET
Student: Orlanda Haynes Date: 05/27/2018
THIS FORM MUST BE COMPLETELY FILLED IN
Follow these procedures: If requested by your instructor, please include an assignment cover
sheet. This will become the first page of your assignment. In addition, your assignment header
should include your last name, first initial, course code, dash, and assignment number. This
should be left justified, with the page number right justified. For example:
DoeJXXX0000-1 1
Save a copy of your assignments: You may need to re-submit an assignment at your instructor’s
request. Make sure you save your files in accessible location.
Academic integrity: All work submitted in each course must be your own original work. This
includes all assignments, exams, term papers, and other projects required by your instructor.
Knowingly submitting another person’s work as your own, without properly citing the source of
the work, is considered plagiarism. This will result in an unsatisfactory grade for the work
submitted or for the entire course. It may also result in academic dismissal from the University.
EDR8205-3
Week 3 Assignment: Analyze Quasi-Experimental (Non-Randomized) Designs
Hi Orlanda,
Nice job with week 3! You made good use of the article by Fitzpatrick and Meulemans (2011) this week to
further your quantitative skills.
This week we got a chance to review a quantitative methodology and a quasi-experimental design. Again
take note of that wording as if you did a study like this you would end up saying this study uses a
quantitative methodology and a quasi-experimental design. That is how you word that.

2. OHAYNESEDR8205-2 2
We use quasi-experimental designs in the same way we would use straight up experimental designs. The
difference is that with quasi-experimental designs we, for whatever reason – and there can be
lots of reasons, cannot do random assignments to treatment and control groups.
In a traditional experiential design we could have two groups and say okay count off and everyone with
an even number will be in this group that gets this treatment and everyone else will be in this
other group that does not get the treatment and at the end we will compare results. In research
that is not always possible for ethical reasons, because groups are already established, etc. So in
those cases we can use a quasi-experimental design to see what impact a certain treatment or
condition has on the participants. Of course this complicates reliability and validity as well, which
also needs to be addressed in the study as a result.
I made a few more comments for you below. Keep up the solid work in the class!
Joanna

3. OHAYNESEDR8205-2 3
Week 3 - Assignment: Analyze Quasi-Experimental (Non-Randomized) Designs
The primary purpose of this assignment is to enhance Ed D students’ awareness of quasi-
experimental (non-randomized) research designs including definition, strengths and weakness,
best practice, and the nature and characteristics of research questions. For illustration purpose,
the author uses Fitzpatrick and Meulemans’s (2011) article “Assessing an information literacy
assignment and workshop using a quasi-experimental design. “Quasi” refers to the state of
resembling; quasi-experiments resemble true experimental research, also known as a true
experiment (Cook & Campbell, 1979). The primary difference is that researchers exclude one or
more standard research components (e.g., random assignment of participants, pre-post-tests,
treatments, and control groups). If researchers use random assignment, for instance, the design
would be a randomized experiment or true experiment.
Comparatively, if the framework includes a nonequivalent control group (e.g., nonrandom
selection of participants that receives or not receives the intervention) or a partial randomized
control group, a comparison group (e.g., similar in baseline characteristics of the nonequivalent
control group), and pre-or-post tests or both the framework would be a quasi-experimental
design (Creswell, 2015; Lodico, Spaulding, & Voegtle, 2010). In education environments,
investigators routinely use quasi-experiments to estimate what casual effects, if any, do
intervention programs have on target populations primarily because (in most real-world settings)
randomization is either not practical or would pose ethical, social, or logistical problems
(Creswell, 2015; Lodico, Spaulding, & Voegtle, 2010). Fitzpatrick and Meulemans (2011) used
the design to explore whether an information literacy program that included a workshop (e.g.,
skills, tools, and strategies needed to complete scholarly research) and a research task would
improve students’ information literacy skills more effectively than instructions on how to use

4. OHAYNESEDR8205-2 4
library resources alone.
Quasi-Experimental Designs: Strengths and Weaknesses
Strengths. Quasi-experiments have a significant niche in the social sciences, public
health research and industries, education communities, and education research especially when
randomization is not practical or reasonable (Black, 2012; Campbell, & Stanley, 2015; DeRue,
2012; White, & Sabarwal, 2014). In addition, quasi-experimental designs (QEDs)
 exclude core constraints characteristic of true experiments (e.g., random sampling),
 are routinely employed to address internal and external validity issues,
 are carried-out primarily in naturalistic environments vs. controlled sittings,
 evaluate intervention programs and services more efficiently than other strategies,
 reduce ethical problems regarding research methods,
 make generalization more feasible by using matching strategies to create control groups,
 control research costs and efficiency by eliminating pre-screening and randomization
processes,
 make restructuring research designs easier because threats to internal and external
validity can be identified and controlled,
 use pre-post-testing to establish participants’ baseline characteristics,
 could include features from experimental and non-experimental methods, and researchers
 could use the designs in longitudinal studies conducted in different environments
(Campbell, & Stanley, 2015; DeRue, 2012; White, & Sabarwal, 2014).
Using a QED, Fitzpatrick and Meulemans (2011) showed that literacy intervention programs
comprised of workshops (which could include both asynchronous and synchronous learning

5. OHAYNESEDR8205-2 5
tools) and access to computers could address students’ diverse learning styles more effectively
than other means.
Weakness. Quasi-experimental designs do not require random assignments.
Researchers identify comparison groups based on baseline characteristics of those in treatment
groups (Campbell, & Stanley, 2015). Nonequivalent test groups which limit generalizability of
findings to larger target populations is the intrinsic nature of QEDs (White, & Sabarwal, 2014).
Another core weakness is that intervention programs conducted without baseline data create
selection bias or confounding factors (e.g., some factors are unique to only one group; thus, the
confounding factor could be the cause of the intervention outcome differences.) (Campbell, &
Stanley, 2015; White, & Sabarwal, 2014). Moreover, Fitzpatrick and Meulemans (2011)
indicated that “high labor cost” and “time consumption” could become primary limitations for
intervention program developers and administrators as far as designing workshop curricula and
addressing staff needs.
Best Practice: Quasi-Experimental Designs
Common types of quasi-experimental designs include (a) nonequivalent groups, posttest
only, (b) nonequivalent groups, pretest/posttest, and (c) time series designs (Campbell, &
Stanley, 2015; Lodico, Spaulding, & Voegtle, 2010). If researchers want to know, for example,
if a whole language program (WLP) was more effective than a phonetics-based program (PBP),
they could administer the WLP to one group and the PBP to the other followed by a reading
comprehension test. The design would be a nonequivalent group, posttest only (White, &
Sabarwal, 2014). However, a core weakness is that the groups may differ in ways that
negatively or positively affect the outcomes of the posttest results (e.g., participants in either
groups could have been more skillful than their peers in one or both subjects prior to the study or

6. OHAYNESEDR8205-2 6
other underlying constructs could have influenced the test results). (Campbell, & Stanley, 2015;
Lodico, Spaulding, & Voegtle, 2010).
On the other hand, if researchers access the language skills of both groups before
beginning the study then the design would be a nonequivalent group, pretest/posttest. By
identifying participants’ baseline characteristics, positive differences on the posttest could be
accredited to intervention programs or if pretest scores showed that the groups’ baseline
characteristics differed at the onset of the study then any differences on the posttest would be
difficult to interpret correctly (Campbell, & Stanley, 2015). Although time-series designs could
become more costly and time-consuming than either nonequivalent groups, posttest only or
nonequivalent groups, pretest/posttest, the results could improve the precision of causal estimates
(e.g., data richness) because (by definition) best practices (BP) recommend multiple assessments
(or measurements) from both groups (e.g., treatment and control) before and after
implementation of the intervention program (Campbell, & Stanley, 2015; Lodico, Spaulding, &
Voegtle, 2010; White, & Sabarwal, 2014). Fitzpatrick and Meulemans (2011) used a pre-test to
assess participants information literacy skills prior to implementation of the literacy program and
a posttest afterward.
Moreover, BP recommend that, when using quasi-experiment designs, researchers should
provide scientific reasoning that supports their methodological perspectives (Lodico, Spaulding,
& Voegtle, 2010). Fitzpatrick and Meulemans (2011), based their theoretical foundation on the
works of Jean Piaget (e.g., self-directed learning facilitates cognitive development) and Lev
Vygotsky (e.g., social interactions enhance learning). These schools of thoughts facilitated the
development of an information literacy intervention program; results showed statistical
significant differences between the pre-and-posttest assessments and the students’ perceived self-

7. OHAYNESEDR8205-2 7
efficacy.
Sample Quasi-Experimental Design Questions
General thesis statements for quasi-experimental designs could include any of the
following:
 What effect does XYZ math intervention program has on high school seniors at Mount
Tam High School (nonequivalent group, posttest only, [creates a single unit confound])?
 Does Z-Mack information literacy tutorial program improve students’ literacy skills in
information technology courses (nonequivalent group, pretest, posttest)?
 Does career mentoring leads to an increase in job satisfaction levels (time series
designs)?
Conclusion
The primary purpose of this assignment is to enhance Ed D students’ awareness of quasi-
experimental (non-randomized) research designs including definition, strengths and weakness,
best practice, and the nature and characteristics of research questions. For illustration purpose,
the author uses Fitzpatrick and Meulemans’s (2011) article “Assessing an information literacy
assignment and workshop using a quasi-experimental design. “Quasi” refers to the state of
resembling. Except for non or partial randomization, quasi-experiments (QEs) resemble true
experimental research, also known as a true experiment (Cook & Campbell, 1979). In education
environments. investigators routinely use QEs to estimate casual effects of intervention programs
(Campbell, & Stanley, 2015; Lodico, Spaulding, & Voegtle, 2010; White, & Sabarwal, 2014).
Fitzpatrick and Meulemans (2011) findings showed that information literacy intervention
programs that incorporate workshops and research activities facilitate the development of
information literacy skills more effectively than written instruction alone.

8. OHAYNESEDR8205-2 8
References
Black, T. (2012). Doing quantitative research in the social sciences: An integrated approach to
research design, measurement, and statistics. Thousand Oaks, CA: Sage Publications.
Campbell, D. T., & Stanley, J. C. (2015). Experimental and quasi-experimental designs for
research. Thousand Oaks, CA: Ravenio Books.
Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design & analysis issues in
field settings. Boston, MA: Houghton Mifflin
Creswell, J.W. (2015). Educational research: Planning, conducting, and evaluating quantitative
and qualitative research (5th Ed.). Boston, MA: Pearson.
DeRue, S. (2012). A quasi experimental study of after-event reviews. Journal of Applied
Psychology. 97 (5), 997–1015. doi:10.1037/a0028244
Fitzpatrick, M. J., & Meulemans, Y. N. (2011). Assessing an information literacy assignment
and workshop using a quasi-experimental design. College Teaching, 59(4), 142-149.
doi:10.1080/87567555.2011.591452
Lodico, M., Spaulding, D., & Voegtle, K. (2010). Methods in educational research: From theory
to practice (Laureate Education, Inc., custom ed.). San Francisco: John Wiley &Sons.
White, H., & Sabarwal, S. (2014). Quasi-experimental design and methods, methodological
briefs: Impact evaluation 8. UNICEF Office of Research, Florence. Retrieved from
https://www.unicef-irc.org/KM/IE/img/downloads/Quasi Experimental_Design_and_
Methods_ENG.pdf.