The reliability and quality of your research depend upon several factors such as determination of target audience, the survey of a sample population, choice of technique and methods for research, and analysis of results. The answer to all these questions is the research design. An effective research design creates minimum discrepancies in data and improves trust in the research information that is collected and analyzed. An impactful research design offers a very less margin for errors and ensures accuracy in all types of design. This blog decodes the types of research design, its elements, and salient features. Check out our artificial intelligence free courses to get an edge over the competition.
Research design, simply put, is a specification related to the processes and methods for gaining information needed. It is an operational pattern that is overall a framework of any project. This states precisely what information could be gathered or collected from a source by the use of specific methods. The research design also helps to gain insights into the methods to be employed for the same. This is why you must be wondering if and which research design is diagnostic in nature?
What Are The Features Of Research Design?
Any research design is a strategy that suggests the specific means by which you can provide answers for any of the research questions, test any hypotheses, and also achieve research purposes that help select from the apt decision alternatives. This helps solve any management problem and even take advantage of an existing market opportunity, besides helping understand which research design is diagnostic in nature and the research design types.
What is Research Design?
To begin every important research, the researcher chooses a structure of techniques and methods to be applied to the research process. This structure or framework is called research design. Research design enables researchers to hone the ideal research methods for the topic at hand and establish an environment for successful research studies.
Benefits Of Research Design
Any research design functions like a bridge that connects what has already been established, that is, research objectives, to what actually has to be performed as part of the conducted study. The final goal is to achieve the specific objectives. It tries to gauge what a client will need regarding findings and arrive at the analytical work on gathered data that will convert these into relevant findings.
Are There Different Types Of Research Design?
If there is no explicit design, a researcher will have ideas that are fogged around what needs to be performed. Thus, it is extremely advisable that any design gets put up on paper since it is obvious that any study might go down the drain if the concepts exist in a researcher’s mind only. Unless the research design is clear and written or drawn up well, the research actually becomes flaky in terms of structure. This is why there must be clarity to help understand the research design types.
The research design topic explains the type of research, whether it is experimental, correlational, survey, semi-experimental, or review. It also defines the sub-type, be it research problem, experimental design, descriptive case study, etc. You can also consider doing our Python Bootcamp course from upGrad to upskill your career.
The three most common research design types are data Collection, measurement, and analysis. The research design type is determined by the research problem faced by the organization, and the design phase of the research study determines what and how to use research tools.
More On What Are The Features Of Research Design?
Among the types of research design, a formal design has advantages that are specifically appreciated when an investigator decides on the required data. If the data collected among types of research design, leads to being irrelevant, the result is inefficient as well as puzzling. It is more serious when you end up ignoring some data that might have been necessary. This could be revealed only very later in the stage of analysis.
While understanding what are the features of research design, remember that all research design, including research design is diagnostic in nature, actually provides a number of advantages while studying data and also understanding their meaning and research design types. This helps in keeping calculations and also thinking on a path to recommendations and solutions. Remember, this in no way means that design must be in a rigid framework. A good design will guide and never dictate or conduct any research.
Main Elements of Research design
Research design is a blueprint for data collection, measurement, and analysis. It is the stepping stone for decisions regarding what, where, how much, when, and steps for research design are undertaken.
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A research design is a schedule of conditions for data collection and evaluation designed to align with the research objectives and available resources.
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Research design is a plan that recognizes the kinds and sources of information related to the research problem.
Research design is a strategy that indicates the methods to be adopted for collecting and analyzing data.
The research design also includes the time and cost budgets constraints that are primary to any research study.
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Although all types of research design have some common characteristics, the key elements that every good research design have are:
- Purpose statement
- Data collection techniques
- Methods of research data analysis
- Type of research methodologies
- Possible obstacles to the research
- Settings for research study
- Time of the research study
- Analysis measurement
Salient features of Research Design
Accurate and reliable results drive the validity of research design. But unfortunately, many companies tend to make crucial decisions driven by skewed research. The main reason for this is the failure of researchers to consider biased research. To achieve 100% accuracy in your research data, you must do everything to safeguard your research against any bias.
Moreover, your research outcome must apply to a wide population rather than a small sample. To guarantee a wide reach, you must get accurate models and account for any margin of error.
The essential characteristics of good research design are:
When you set up the research study, you may need to make some assumptions about the data collected, and the results projected must remain neutral and free of any bias.
In regularly conducted research, the researcher will expect similar results each time. Your research design must ensure that the research questions help maintain the standard of results. You can attain the desired results only if your research design is reliable.
The researcher must leverage the right measuring tools to gauge the accuracy of the research results and check whether the results align with the research objectives.
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The outcome of your research design must apply to an entire population and not just a confined sample. A generalized design ensures a full-proof design that can be applied to any population with the same level of accuracy.
Five Common Types of Research Design
There are several ways to distinguish research design. Depending on the method and purpose of design, we can categorize research design into five types:
1. Descriptive Design
In this hypothesis-based design methodology, the researcher primarily describes the subject matter central to the research. Descriptive research design applies to natural observations, case studies, and surveys. This method involves data collection, data analysis, and its presentation. It allows the researcher to put forth the problem to persuade others to comprehend the necessity for the research.
2. Correlational Design
True to its name, correlational research design enables the researchers to establish relationships between two related variables. This type of research design method needs at least two data groups. This method can be utilized for observational studies.
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3. Experimental Design
Be it a quasi-experiment, a field, or a controlled experiment, this research design type establishes a clear cause and the effect of any event. The researcher studies the impact of the independent variable on the dependent variable.
Typically, this research design type is applied to solve a specific issue by altering the independent variables and observing the changes to the dependent ones. For instance, an experiment can be performed on the price change, and its effect on customer gratification can be observed.
4. Diagnostic Design
In diagnostic research design, the researchers strive to explore the underlying reason for the occurrence of certain circumstances. This method can assist you in examining in depth the elements that cause specific challenges that your customers may face. The design generally comprises three phases, namely the problem inception phase, problem diagnosis phase, and the problem solution phase.
5. Explanatory Design
As the name suggests, explanatory design is utilized by researchers to explore, expand and explain theories and innovative ideas. This design method is applied to find the missing pieces of a puzzle or obtain clarity on vague aspects of a certain topic.
Qualitative and Quantitative Research Design
Qualitative and Quantitative research designs are explained in detail below:
1. Qualitative Design
Qualitative design can give solutions to questions such as how and why some event is occurring. Qualitative research typically depends upon open-ended questions for surveys and definitive answers that cannot always be quantified or expressed through numbers. Qualitative research is the perfect approach to collect assimilated information and understand customers’ mindsets and behavior.
Qualitative research is mostly used to discover ideas, explain numbers and formulate predictions.
2. Quantitative design
The quantitative design aims to answer queries such as who, what, where, how many, and when?
Because the questions are closed-ended, the outcome of quantitative research surveys can be transformed quickly into statistics, graphs, charts, and numbers. Businesses often leverage quantitative research surveys to obtain more information about their clients and base their decisions on the data procured. For instance, a quantitative research survey is ideal for measuring the satisfaction of customers on a scale of, say, 1 to 10.
Flexible and Fixed Research Design
Yet another research design classification is the flexible and fixed research design. Fixed research design is based on quantitative data collection, and flexible research design is based on qualitative data collection.
In a static design method, the design is settled and fixed before data collection. With a flexible research design, you have more freedom for collecting data.
For instance, survey questions with multiple choice answers are a part of fixed research design, while surveys, where respondents need to type their answers, are a part of flexible research design.
Research Design types based on grouping
Another allocation of research design is made based on the grouping of participants. Mostly, grouping is based on the hypothesis of the research and the sampling of participants. Given below are the four main research design types based on grouping:
1. Cohort Design Study
A cohort research design study is a longitudinal research study that takes samples of a cohort group of people (those with similar characteristics). In this kind of panel study, the panel individuals share certain common characteristics.
2. Cross-sectional Design Study
In a cross-sectional research study, data is analyzed either from an entire population or from a typical sample at one instance.
3. Longitudinal Design Study
A longitudinal research design study comprises of similar observations of the same variants for a short period or a longer period. A longitudinal method is often touted as a kind of observational research study though they may also be characterized as random experiments.
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4. Cross-Sequential Design Study
Cross-sequential design study combines both cross-sectional and longitudinal analysis, working to make up for some inherent issues present in both research design methodologies.
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Research is a vital part of every field of study, be it medicine, science, technology, art, culture or media, maths, geography,, etc. An effective research design must be in place to successfully carry out extensive research on a substantial sample population. To sum up, a good research design will contain a concise statement, techniques for data collection, data processing, and data analysis.
What is the purpose of data collection?
Data collection is the process of obtaining information from individuals or objects for use in a research study. The data collection process is often the most time-consuming part of a research project and can often take a great deal of effort and planning on the researcher's part. However, when done correctly, data collection can yield invaluable information that can enhance a research project and provide answers to questions that would otherwise remain unanswered. The purpose of data collection is to obtain the information needed for a research study, and the most effective way to do this is to focus on the goals of the study rather than on the characteristics of the participants.
What does “variable” refer to in the correlational method?
Correlational research designs are used when the goals of the researcher are to understand, describe, and explain the relationship between two or more variables. In this type of design, two or more variables are measured or observed to determine if there is a relationship between them. The term variable refers to the thing being studied or the factor being measured in a research study. In a correlational method in research design, the term variable refers to the thing being correlated or the factor being correlated.
What are qualitative and quantitative data collection?
Qualitative research techniques are used to understand one variable's effects on another, or to understand the effect that an event has on a person’s feelings, attitude, and behaviour. Quantitative data collection is a method by which researchers collect large amounts of data from a large number of people and study it to extract meaningful results and uncover significant patterns. In this method, large quantities of data are collected and analyzed, often without the knowledge of those people being studied.