Describe the primary goal of scientific research.
The primary goal of the research is to increase knowledge so that we may be able to devise better
solutions to solve real-world problems. This can be done by determining the generalizations
about the topic. Generalizations assist in building theories that bring about new and innovative
knowledge (King, G., Keohane, R. O., & Verba, S., 1994).
Explain the crucial differences between the experimental, statistical, and comparative method
(according to Lijphart)
Experimental, statistical, and comparative methods all aim at scientific explanations that help to
establish a general empirical relationship between two or more variables. In contrast, all other
variables are controlled and held constant. According to Lijphart, the experimental method is
ideal for scientific explanation. However, it cannot often be used for political science due to
practical and ethical impediments. Statistical methods are the conceptual mathematical
manipulation of empirically observed data (Lijphart, 1971). The statistical method can be seen as
an approximation of the experimental method. The comparative method is very similar to the
statistical method. However, it deals with much smaller controls.
What is the “logic of inference”? Why do King, Keohane, Verba, and Keohane discuss this
logic?
The logic of inference is a conclusion that is drawn based on information that is present. It is
similar to a hypothesis. King, Keohane, Verba, and Keohane (KKVK) discuss this logic because
they believe “the differences between the quantitative and qualitative traditions are only stylistic
and are methodologically and substantively unimportant.” KKVK also sought to show that the
quantitative and qualitative traditions shared a single logic of inference that can help to explain
the statistical analysis (King, G., Keohane, R. O., & Verba, S., 1994).
Explain the significant components of research design.
The four major components of research design are the research questions, the theory, the data,
and the use of data. The components are not in any order. Depending on the type of research, the
data collection may be done before the research question is created. There is no precise rule for
choosing a topic when considering the research question. When selecting a theory, it’s essential
to choose one that could potentially be wrong and falsifiable, which can generate many
observable implications. It must be nonbiased for the data and the use of data within the research
design.
What plays the "leading role" in determining which research design is appropriate for your
project?
The research question should pose a question that is “important” in the real world and make a
specific contribution to identifiable scholarly literature by increasing our collective ability to
construct verified scientific explanations of some aspect of the world.
How do research design decisions determine the potential impact of research projects?
Research design decisions determine the potential impact of research projects because it ensures
that the researcher properly carries out the project's work. Research design helps the researcher
stay on task without switching directions. Its overall impact is to create a strategic process that is
easy to follow. A poorly structured research design can negatively impact an entire research
project or study.
References
King, G., Keohane, R. O., & Verba, S. (1994). Designing social inquiry. Princeton university
press.
Lijphart, A. (1971). Comparative politics and the comparative method. American political
science review, 65(3), 682-693
How do research design decisions determine the potential impact of research projects?
The research problem or issue the researcher chooses determines the impact of the research
project. Identifying the problem will determine the procedure that is applied to the project.
Hello Tina
I agree the primary goal of the research design is determining the methods that will be taken.
However, I also believe that understanding the value that the research project will bring to the
world is important. Research has the ability to open a dialogue about topics that may otherwise
have not been brought to light (Kuhar, 2010). And utilizing inferential statistics also helps
suggest explanations for the research question. It helps to draw conclusions based on
extrapolations and is different from data that only summarizes the information that is being
measured.
When considering research design and its potential impact on a research project, it’s also
important to address the philosophical assumptions you are making (Wright, 2016). Being sure
that the information can tell you the how’s and why’s. It’s also important to consider the
ontological and epistemological position by asking the following questions: “What can I know
about the phenomenon of interest? How can I know what I want to know? What approach should
I use and why?” Answering these questions may assist in guiding methodological choices that
will best suit research. An additional element that may positively impact the research design is to
select of the appropriate sampling strategy. This will help to find information-rich cases instead
of general cases. The last thing you want to deal with is selecting a research design without an
appropriate amount of data and prior information. Unless that is the goal of the research is to
bring about more information related to the topic. Lastly, Wright suggests being reflexive by
examining the ways that one's personal history, education, experience, and worldview have
affected the research question that has been selected. This will allow researchers to connect
without topic and refrain from burnout. When you are genuinely connected and interested in the
research design and topic, you will have more drive to fulfill the mission.
Kuhar, C. W. (2010). Experimental design: Basic concepts. Encyclopedia of animal
behavior (pp. 693-695) doi:10.1016/B978-0-08-045337-8.00224-2 Retrieved
from https://dx.doi.org/10.1016/B978-0-08-045337-8.00224-2
Wright, S., O'Brien, B. C., Nimmon, L., Law, M., & Mylopoulos, M.
(2016). Research Design Considerations. Journal of graduate medical
education, 8(1), 97–98. https://doi.org/10.4300/JGME-D-15-00566.1
Kuhar, C. W. (2010). Experimental design: Basic concepts. Encyclopedia of animal
behavior (pp. 693-695) doi:10.1016/B978-0-08-045337-8.00224-2 Retrieved
from https://dx.doi.org/10.1016/B978-0-08-045337-8.00224-2
Select an appropriate sampling strategy. Purposive sampling is often used in qualitative research,
with a goal of finding information-rich cases, not to generalize.6
Be reflexive: Examine the ways in which your history, education, experiences, and worldviews
have affected the research questions you have selected and your data collection methods,
analyses, and writing.13
Your post is very well written. As you rightly pointed out, "comparison can be
a strong component of social science research. The premise that comparison
is beneficial is ingrained into the fabric of how individuals intuitively
understand the world around them (Livingston, 2022, Canvas). Additionally,
permit me to contribute to what you have alluded to; according to Collier and
Mahon (1993), "Comparative analysts must make sure that they emphasize
description and prescription in their methodological analysis of categories"
due to confusion and ambiguity that may be present in the research method;
thus, comparison in the social science is imperative to eliminate ambiguity
and proffers 'decisive' or 'new' knowledge which is a result of generalization
that Munson (2021) alluded to in her presentation. Moreover, because social
science is unlike natural science, the comparative method is the substitute
with limitations (Lijphart, 1971, 685).
Also, to your point that inference is an imperfect process, I will add that
Creswell and Creswell (2018) argue that qualitative gives us more details and
quantitative proffers a broader trend, but both methodologies are united in
style; therefore, according to KKV, they help us identify causation to produce
valid descriptive and causal inferences (King, Keohane, and Verba 1994, 4).
Furthermore, KKV asserts that to "achieve unbiased inference on the
collection and use of data, one should anticipate problems (KKV, 1994, 28) to
avoid sources of bias in the collection process to improve inference.
According to Creswell, “Research designs are plans and the procedures for research that span the
decisions from broad assumptions to detailed methods of data collection and analysis” (Creswell,
2018). The major components of a research design assist with the overall strategic planning
process. Researchers may integrate the different elements of the study in a way that assists in
logical analysis. This ensures that the research problem is effectively addressed. Vogt also adds
that research design is most effective when it is driven by the nature of the research problem
(Vogt, 2018). It is essentially the blueprint for analyzing data. According to King, the research
design has four components as you mentioned (King, G., Keohane, R. O., & Verba, S. 1994).
However, it’s important that researchers understand the significance of those components. Other
elements of the research design can be seen by prioritizing the following. Considering your aims
and approach, identifying your population and sample method, selecting your data collection
processes, and deciding on the data analysis. This research design methodology ensures that each
step of the planning model is carefully thought out and executed. It’s important to carefully
consider the possible outcomes. Researchers must make a point to select alternatives that will fall
within the goals and objectives that were originally set. The research design should conclude
with monitoring and evaluating the outcomes and results. Coming up with a strategic plan
creates a vision and ideas within one segment of our lives and strays away from that vision
because of more exciting or in some cases easier paths. If we look at the timeless principle of the
book of the bible Habakkuk 2:2 which says, “Write the vision, make it plan” it gives us
instructions on how to stick with the goals and visions that were previously given to us.
Creswell, John W., and J. David Creswell. Research Design Qualitative,
Quantitative, and Mixed Methods Approaches. Thousand Oaks: Sage, 2018.
King, Gary, Robert O Keohane, and Sidney Verba. Designing Social Inquiry
Scientific Inference in Qualitative Research. Princeton: Princeton University
Press, 1994.
Vogt, W. Paul. "The Dictatorship of the Problem: Choosing Research
Methods." Methodological Innovations Online, 2008: 1-17.
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