Running head: RESEARCH DESIGN REPORT 1
Research Design Report 1
Todd M. Gruhn
Texas A&M University-Commerce
1
RESEARCH DESIGN REPORT 1
2
Introduction
In this research design report, we will focus on quantitative and mixed-methods
approaches to research and discover cases in which one method is advantageous over others. In
addition to the broad categories of quantitative and mixed-methods, correlational, causal
comparative, and experimental research types will be analyzed and evaluated. Finally, the
quality of surveys and participant response in qualitative research will be explored.
Quantitative Designs
The quantitative designs of correlational, causal comparative, and experimental will be
defined and discussed in this section. Scenarios detailing the advantages of these methods over
others will also be discussed. In addition to the advantages, the disadvantages of each will also
be covered.
Correlational
Correlational studies are studies where researchers use the statistical technique of
correlation to describe the relationships between two or more variables. (Creswell, 2012, p. 619)
This particular research design is used when the degree of influence between variables needs to
be explored. For example, designing a study to predict a student’s success in postsecondary
education given their ACT and SAT scores would be a correlational study. Researchers would
hope that students with higher ACT and SAT scores would typically be more successful in
postsecondary studies but it would take careful analysis of the relationship between these two
variables to be able to make a true determination as to whether scores were an accurate
determiner of success (or vice versa.)
Correlational studies can be very simple to perform in comparison with other quantitative
techniques due to the relative ease of coming up with a research design. Data collection is also
RESEARCH DESIGN REPORT 1
3
very straightforward in administering the instruments (tests) and collecting the data for each
participant. Many of the disadvantages of correlational research is found in the analysis of the
data and determination of any patterns in the data. Sample sizes may be to small to actually
determine any relationship between the data or the data may be edited or made up; these are
several ethical issues that can be found in correlational research. (Creswell, 2012, p. 353)
Causal Comparative
Causal comparative research is similar to correlational research in that it seeks to identify
relationships or associations; the difference is that causal comparative research looks specifically
at the differences (and the causes of those differences) in the variable relationships. (Fraenkel,
2009) One example of a possible causal comparative study would be to examine the relationship
between years of experience and job satisfaction. Do people with more time in a particular job
exhibit more job satisfaction than those still in their probationary period? This question could be
answered by a causal comparative study; part of the examination of job satisfaction hinges on the
difference between an employee with some longevity versus a new employee.
Correlational studies and causal comparative studies share many of the same advantages.
Both types of studies rely on the examination of variables (and not the creation of experiments.)
One disadvantage of the causal comparative study is the lack of randomization. When cause and
effect are examined, it is important to have diverse treatment groups but causal comparative
studies do not have the same random assignment as experiments. Due to this disadvantage,
causal comparative studies occasionally develop into experimental studies.
Experimental
According to Creswell, in experimental designs there must be a test or procedure to
determine if an outcome or variable is influenced by the test or procedure. (2012, p. 295) In
RESEARCH DESIGN REPORT 1
4
order to need to use an experimental design, the researcher must first determine whether there is
a need to establish a cause and effect relationship between the independent and the dependent
variables. Experiments rely on random assignment and strict control over any extra variables
outside of the system being tested. Treatment groups are also formed and compared with other
non-treatment groups to determine cause and effect. An example of a scenario in which an
experimental design would be recommended if a researcher wanted to determine the
effectiveness of a new diet pill. The researcher could do this by establishing a control group (to
a placebo) and establishing a test group (to take the actual diet pill.) It would be very important
in this experiment to make sure that the participants were randomly assigned to their prospective
groups.
One of the main advantages of the experimental design is that the findings produced by
the research are backed up by collected and validated data. The data collected during the
experiment is checked for bias and evaluated by statistical measures to determine that any cause
and effect relationship found is, indeed, a legitimate one. A major disadvantage of the
experimental design is the ethical issue that surrounds the research. Research subjects that are in
the most need of a particular treatment may not always get that treatment since participants are
randomly assigned to various treatment groups. (Creswell, 2012, p. 327)
Survey Designs
A very important part of quantitative research is the survey. Surveys provide valuable
insight to researchers on attitudes, opinions, behaviors, or characteristics of the population being
examined. (Creswell, 2012, p. 376) The data collected via surveys can be analyzed via statistical
methods to provide data (typically correlational) to help find relationships between the variables
tested on the survey instrument and some question that has been established before the
RESEARCH DESIGN REPORT 1
5
implementation of the survey. In order to design an effective survey, the researcher must look at
existing models (if they exist) and determine how well those models relate to the needs for the
current survey. A quick modification of an existing survey will save time over creating a new
survey.
If a new survey must be developed, it must be developed with the end goal of the
research in mind. Questions must be focused and specific in order to collect data on specific
metrics needed by the research. If time allows, the researcher should hold a pilot testing run in
order to find any biased questions or vague questions that may trip up the research participants.
Researchers must also be aware of the need to have high response rates from participants.
Higher response rates give researchers more confidence in the data that they have collected from
the survey instruments. (Creswell, 2012, p. 390) Current technology makes it much easier for
participants to respond to surveys by answering questions online.
RESEARCH DESIGN REPORT 1
6
References
Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative
and qualitative research (4th ed.). Boston, MA: Pearson.
Fraenkel, J. R. & Wallen, N. E. (2009). How to design and evaluate research in education (7th
ed.). New York, NY: McGraw-Hill Education.