Before starting a study, you must determine the approach and techniques to ensure it is successful. This is what is called a research design. A clear research design allows for the collection and analysis of data to draw a meaningful conclusion accurately. It defines the problems and addresses the model for analyzing collected data. A good research design will ensure that the results collected will help address the problem raised. For this reason, one must learn how to select the right one. The process of selecting the right design starts with identifying the research priorities, that is, clearly stating what one intends to achieve at the end of the study. This will then guide every decision they make during the research process.
In this article, we will define a research design, identify the different types of design, and explain the difference between a research design and research methods. We will also look at the steps for selecting a suitable research design.
A research design, or a research strategy, is a well-organized procedure one intends to utilize in their research that defines a logical plan for undertaking the research problem through data collection, measurement, and interpretation. In other orders, it is how one plans to conduct their project. The type of research design chosen will allow a researcher to identify and deal with any issues that may arise during the research.
When setting out to conduct any study, the problem will determine or inform the type of research design to choose.
A research design must contain the following elements:
A Clear Purpose
One must clearly define the research question and hypothesis.
This is about selecting a section of the population in a study. It includes making decisions concerning population size, methods for sampling, etc.
This is about the process of gathering useful information from study subjects. It involves decisions about how and when to collect data and the tools for collecting.
A good research design must have the right approach for analyzing and interpreting all collected data. Therefore, data analysis is about making the right decisions about statistical tests for analyzing data.
This is about the decisions about the overall approach for the study.
The chosen research design must have decisions concerning ethical considerations such as participant confidentiality and consent.
A research design should consider critical decisions on finances, staffing, etc.
A researcher must consider decisions on how long the study will take to collect, analyze, and interpret data.
A research design is instrumental as it provides a structure and direction.
With that said, a good research design must contain the following characteristics:
For research to be effective, one must use the right tools to determine the outcomes that align with their objectives to measure success or failure. A good research design helps select the appropriate tools to gauge these outcomes.
A research design will generate similar results whenever it is performed. Nevertheless, this will only be possible if the design is reliable. A reliable research design ensures that the results of the study are accurate.
A good research design should provide results that are free from any biases. One must lower any form of bias during the research process. A research design ensures that the results are correct.
Limit the results of the study to only one section of the population. As such, generalization is a crucial characteristic of a research design. Generalization means that the research design is foolproof and can be applied to any type of population with exact accuracy.
A research design is important for the following reasons:
There are several types of research design, each classified according to its design methods and purpose. However, the research design is categorized into qualitative and quantitative research design.
Qualitative research design answers questions like who and why during the research. Because of this, it is sometimes referred to as subjective.
The design uses open-ended questions to develop findings presented in a written format. Qualitative research design explores and understands unique and deeper world issues.
The following are the different types of qualitative research design:
This approach seeks to understand human experiences through the involved people. These everyday experiences are referred to as lived experiences.
Phenomenological studies aim to investigate the meaning these experiences hold for the subjects. The research subjects are asked to describe their experiences as they perceive them.
To understand these experiences from a vantage point, a researcher must consider their feelings and beliefs. First, one must ask what they would like to discover; then, put those ideas aside in a process called bracketing.
This design is responsible for studying cultures. It involves collecting and analyzing data about culture to understand their actions.
The aim is to establish that an action of one group of people differs from another.
Ethnographic studies are also used to identify inequalities among people. For instance, they study how different cultural groups function and the rules guiding their behaviors.
In this type of design, data is collected and analyzed, and then a theory is drawn from the result. Inductive and deductive reasoning is used in grounded theory.
In healthcare, ground theory is used to understand whether patients can learn to manage new diseases or deal with chronic illnesses.
One of the best ways to find solutions to problems is to understand its history. For instance, in nursing, scholars constantly try to expand the body of knowledge and clearly define the profession.
You can easily achieve this through thorough historical research. Historical studies examine the past to understand the cause and effect of present events. It deals with the identification, location, evaluation, and analysis of collected data.
A case study aims to describe a case (situation, a person, a group of people, an institution). A case study is done to point out an issue by telling a narrative about a person or group of people. A case study uses the following methods to understand a situation.
This type of research design focuses on finding solutions to issues in a social system.
Action research focuses on generating more information or action where a problem exists.
In this research design, the solutions are implemented during the research process.
The quantitative research design involves the collection and analysis of data. It determines how many people behave or feel in a particular way.
Quantitative research design is used to do the following:
There are four different types of quantitative research design:
Use this design to examine how different types of variables (independent and dependent) relate to each other.
Experimental research design establishes a cause-and-effect relationship in any situation.
The main advantage of this design is that it allows you to depict a causal relationship between different variables.
The downside is that you must have control over research subjects and the environment, thus making it difficult to apply it in the real world.
Also known as ex post facto (after the fact), causal-comparative research design attempts to explain the causal relationship between independent and dependent variables. This type of design is the same as true experiments but with certain differences.
The relationship between dependent and independent variables is suggested but not proven. The researcher identifies the independent variable but does not manipulate it, then measures how the independent variable affects the dependent.
This research design investigates the relationship between two or more variables without manipulating or controlling them.
Correlation design allows the researcher to observe the strength or direction of the natural relationship between positive or negative variables. For this reason, data collected in a correlational design study is more reflective of real-world situations.
Correlation research design is useful when you want to understand the extent of the complex relationship between variables in the real world—for example, the relationship between diet and lack of proper sleep.
This design allows for systematically collecting information that describes a subject's activities without influencing them. More importantly, it helps answer the questions of why, when, what, where, and how.
The methods applied in this design include surveys, case studies, observations, etc. The aim is to gather a comprehensive understanding of data. The steps involved in the descriptive study include:
Descriptive research design is used to understand patterns and existing roadblocks in a situation. It is best to answer and collect unbiased data to reveal recurring phenomena—for example, a description of marijuana use among college students.
Note that both correlative and descriptive designs provide a clear picture of the relationship and characteristics of real-world experiences. Nevertheless, the downside is that one cannot speculate on the conclusion about the cause and effect.
This type of design aims to identify the root cause of behavior or issue. In the business world, diagnostic research is used to identify areas of improvement or opportunities for growth. It aims to answer questions like why this happened and the causes behind it.
The diagnostic research design consists of the following crucial steps:
This research method aims to explore the existing facts and ideas to explore new concepts further. Explanatory design is used to study phenomena that have not been explored properly.
In several situations, using either qualitative or quantitative research design is ideal, and it is easy to be stuck on which to use. As a rule of thumb, one must use qualitative research design to understand something, such as concepts etc., and quantitative design to test something, e.g., a theory.
Within a research paper, there are a research design and methods. In addition, it is easy to confuse research design and methods because they are both essential for the success of any study. However, they are different.
A research design is an overall plan for a project, and it is not easy to proceed with a research project without one.
The research method, on the other hand, is a strategy for implementing that plan. It involves research processes, procedures, tools, and techniques for collecting and analyzing data.
The following are the main differences between the two:
Research methods are concerned with the method suitable for collecting and analyzing data. Research design, on the other hand, is responsible for the planned study and the type of expected results.
A good research method depends on the design chosen for the study, whereas a research design is based on the chosen research question or problem.
Research design is a glue that holds a study, so one must understand how to select the writing one.
Before working on any research, one must have a clear plan of how it will work out. Moreover, this is where aims and objectives come in.
Aims and objectives will determine the research's scope, depth, and direction. The aims describe the goals or purpose of the study. Therefore, it acts as a focal point of the research and gives the readers clarity.
The aims show what is expected to be achieved at the end of the project. A research objective, on the other hand, specifies how the study will achieve its aims.
Well-written aims and objectives must drive a good research project. So, one must think carefully about what they want to achieve.
A researcher must decide whether to use a qualitative or quantitative research design. If they select a qualitative design, they must understand the following:
Quantitative design, on the other hand,
Measures variables and describes frequencies.
Apart from this, one must also think practically about the chosen research design. For instance, they must consider research ethics if it involves people or test subjects. They should think of the following:
Their priorities will guide how they make these decisions concerning their projects, so it's important to have them written.
It is important to settle on one approach for the project. However, choosing between qualitative and quantitative research design is not easy. One must consider the following:
A research problem is an issue that needs to be addressed with the research project. Certain types of problems call for specific types of design. For instance, one should choose a quantitative approach if their problem calls for:
On the other hand, if the problem demands a deeper understanding of a concept because little research has been done, then choosing a qualitative approach is a good idea. One should note that qualitative research design is exploratory and is preferred when deciding which variables to explore is difficult.
A person's experiences, training, and skills will influence their design decision. For instance, quantitative design is the better choice if one is trained in statistics, mathematics, writing, or another related program. Conversely, if one enjoys writing and conducting interviews, it makes sense to go for qualitative research design.
Some researchers could be more comfortable choosing a quantitative research method because of the systematic procedures.
For others, it could be uncomfortable to stand against the faculty by choosing a qualitative and participatory approach to investigation.
On the other hand, the qualitative design gives more room for improvement by being innovative and working within the chosen framework.
Every research is conducted with a target audience in mind. The audience could be journal editors, conference attendees, and readers. One must choose a design supported and considered by the target audience. If the audience cannot accept the research, then it is pointless.
One should note that within the qualitative and quantitative design, there are several designs, each with its framework that could shape your project.
A good research design should identify what the research is about and how one will go about choosing the subjects. In addition, this is where population and sampling come in.
Population is the entire group in which one is trying to ascertain specific information, while a sample is a subset of individuals from a population.
A population is a set of elements that possess similar characteristics that the established sampling criteria have defined. It can comprise anything, including animals, people, countries, etc.
The population is composed of two groups;
The target population refers to the entire population the project intends to investigate. It meets the set of criteria established for the investigation. Some examples of this are:
On the other hand, accessible population refers to the portion of the target population the researcher can access for their research. This may be limited to a small region, state, institution, etc. Examples include:
One must clearly define one's population to make deciding on a particular sample easier.
Sampling is selecting a subset of a population (a group of people, events, or behaviors to conduct an investigation. A sample size could be extremely large if the population is large, for instance, national or international.
Since it is difficult to collect information from every individual element in a population, it makes sense to collect data from a sample. The following approaches should be used to select a sample:
The chosen sampling method will determine how well one can generalize their results to the entire population.
Probability sampling involves choosing a sample from a large population using a method dependent on a probability theory.
It is mainly used in quantitative research because it leads to a strong statistical inference about the chosen population.
Even though probability sampling is the most valid option, it can be difficult to achieve unless you are researching a small population.
Nonprobability sampling involves selecting units from an identified population using subjective methods (nonrandom ways).
It can be used in both qualitative and quantitative methods. Even though no probability sampling is easier to use, there is more risk of research bias.
If one chooses a nonprobability sampling, one must consider the limitations and all potential biases.
There is no need for a sample in qualitative research designs, such as ethnography and case studies. The aim here is to understand the specific context.
Rather than sampling, one will collect as much data as possible about the topic under investigation. However, they will still need to select a case and have a clear rationale of why it is suitable for their research question. For instance, one may choose a case highlighting an unusual problem.
Data collection methods are techniques, procedures, and approaches used to gather data to make better decisions for a study. Making appropriate decisions without the necessary data is impossible because they give first-hand insights and knowledge about a research problem.
The choice of data collection methods will depend on the following:
The data collection method is categorized into primary and secondary data methods. Primary data collection methods are collected from first-hand experience and are specific to the researcher’s motives. They are also quite specific. These types of data collection methods include:
Secondary data are those that have been used in the past. One collects this data from both internal and external sources. Internal sources include magazines, sales reports, CRM software, etc. External sources include business journals, libraries, and the internet.
Secondary data is recommended when one cannot collect data from the target population because of a lack of time and funds. With secondary data, one makes an analysis that answers the research questions. This data will also allow one to expand the scope of their research since they can access more samples than one could have on their own. Despite that, it also means that they do not have control over the type of variable to measure and how to measure them. Therefore, their results could be limited.
Apart from coming up with data collection methods, a researcher must have a strategy for using them to collect the needed data. Planning a data collection strategy is necessary, particularly when conducting quantitative research.
First, one must decide on the kind of information to collect. A researcher should consider the following questions:
Their goals for the research will determine the answers to these questions.
Second, they must consider the cost of collecting the data, considering that every additional data is an added cost.
Thirdly, they should think of identifiers. Identifiers are information that points to the source and context for a response in a survey. The more identifiers one has, the better one will identify the successes and failures of the research.
Finally, one should consider how they would get to a data point. Some data is unavailable, and sometimes available, but it is not easy to access. Or one may not have permission to access it.
In research, one will come across variables that are easy to measure, for instance, age and height, but other times, they might run into some that can be hard to measure, such as feelings, thoughts, etc. A researcher should turn all these fuzzy ideas into measurable data.
Reliability and Validity
Reliability signifies that a study's results can be reproduced. One should ask the following questions to ensure their work meets reliability criteria.
To get a valid and reliable outcome, one must ensure that the measurement materials are thoroughly researched and designed.
Additionally, one must plan to contact and engage the targeted sample. Things like how many participants one will need for the target sample size, the inclusion and exclusion criteria needed to get eligible candidates, and the methods for contacting each participant, e.g., through the mail, text, calls, etc., should be considered.
One must also think about how they will manage the collected data. For instance, do they intend to transcribe the interviews? Or will they do data entry for the observations?
Now that data has been collected, it's time to analyze it and make it useful. Raw data is useless because it cannot answer the research questions. This is why there is a need for analysis.
The best way to do this is to set a data analysis plan. This is a roadmap on how one intends to organize and analyze data. Setting a data analysis plan is critical for research as it will help achieve the following objectives:
The type of analysis chosen will depend on the research design. For quantitative analysis, one will use any of the following methods of analysis:
Qualitative analysis is a bit different from quantitative. This is because qualitative data involves words, abbreviations, images, etc. Therefore, it can be difficult to derive meaningful data. Analysis of qualitative data begins immediately after the data is received. Some of the analysis methods include:
After analyzing data, the final step is writing a research proposal. Research serves two purposes:
A research proposal is an important part of the research process because it is a chance to show the knowledge they have acquired. When writing a proposal, one must:
It is important to consider research proposal examples to get ideas for writing one.
A research design is a necessary part of the research process. The strategy allows one to answer the research question and solve the identified problem. One can choose from different types of research designs, and each will depend on the type of research they have conducted (qualitative or quantitative). The tips above will help you select the right design for your study.
A research design is the strategy one intends to implement to answer the research questions.
There are two major types of research design: qualitative and quantitative. Types of qualitative research design:
Quantitative research designs, on the other hand, are:
A research design is an overall structure to answer the research question, while a research method is a strategy for implementing that plan.