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Research Paradigms: Explanation and Examples

4-minute read

• 1st March 2022

Are you planning a research project? If so, you’ll need a research paradigm. But what exactly is a research paradigm, and why is it important? This blog post will cover the following:

●  The definition of a research paradigm

●  Why research paradigms are important

●  Common examples of research paradigms

●  Merging research paradigms

●  Expert editing and proofreading

Read on to find out more or learn about research paradigms in the video below!

The Definition of a Research Paradigm

A research paradigm is a philosophical framework that your research is based on. It offers a pattern of beliefs and understandings from which the theories and practices of your research project operate.

A research paradigm consists of ontology, epistemology, and research methodology .

●  Ontology answers the question: “What is reality?” That is, does a single reality exist within your research? An example of an ontological question would be: “Does God exist?” There are two possible realities (or ontologies) in response to this question: “Yes, God exists,” or “No, God does not exist.”

●  Epistemology is the study of knowledge. It answers the question: “How is it possible to know reality?” Epistemology incorporates the validity, parameters, and methods of acquiring knowledge. An example of an epistemological question would be: “How is it possible to know whether God exists or not?”

●  Research Methodology answers the question: “How do we go about discovering the answer or reality?” This includes the process of data collection and analysis. Research methodology should outline how you conduct your research and demonstrate that the findings are valid.

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Together, ontology and epistemology comprise research philosophy.

Research philosophy combined with research methodology comprises a research paradigm.

Why Are Research Paradigms Important?

Research paradigms are important because they form the philosophical basis of a research project. Research paradigms influence how different schools of learning (such as the sciences versus the humanities) undertake their research. Once a research philosophy has been determined, an appropriate methodology can be chosen.

Furthermore, a knowledge of the philosophical foundation of your research will increase its quality and improve your performance in any analysis you may have to undergo!

Common Examples of Research Paradigms

1. Positivism

Positivists believe that there’s a single reality that’s possible to measure and understand. Because of this, they’re most likely to use quantitative methods in their research. Typically, positivists propose a hypothesis that can be proved or disproved using statistical data analysis. Positivism tends to investigate the existence of a relationship between two variables rather than the reason behind it.

2. Constructivism

Constructivists believe that there’s no single reality or truth, but rather multiple realities. They devote themselves to understanding and interpreting the meaning attached to an action. For this reason, constructivists tend to use qualitative research methods , such as interviews or case studies, which focus on providing different perspectives. Constructivism aims to provide the answer to “why.” For example, asking “Why do 25% of the employees of an organization regularly arrive late to work?” rather than merely establishing the relationship between two variables (e.g., time of arrival at work and availability of nearby parking).

3. Pragmatists

Pragmatists believe that reality is continually interpreted and renegotiated against the backdrop of new and unpredictable situations. Because of this, the philosophy they apply in research depends on the research question itself. Pragmatists often combine positivist and constructivist principles in the same research project, using both qualitative and quantitative methods to investigate different components of a research problem. They believe that the optimal research methods are those that most successfully answer the research question.

Merging Research Paradigms

While most social science research operates from either a positivist (experimental) or constructivist paradigm, it’s possible to combine both, as the field of psychology often does. Quantitative and qualitative methodology are frequently used together in psychology, illustrating the subject’s footing in multiple research paradigms (positivist and constructivist).

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• Cookies & Privacy
• GETTING STARTED
• Introduction
• FUNDAMENTALS

Getting to the main article

Choosing your route

Setting research questions/ hypotheses

Assessment point

Building the theoretical case

Setting your research strategy

Data collection

Data analysis

Research paradigm

In our experience, understanding and setting the research paradigm is without doubt the most confusing part of the dissertation process for students. It is easy to switch off when people talk to you about the philosophy of research , when they start to use words like epistemology and ontology , positivism , post-positivism , critical theory or constructivism , or ask you questions like: What is your view of the nature of reality? We sympathise!

Broadly speaking, research paradigms (e.g., positivism , post-positivism , critical theory , constructivism , etc.) are ways of explaining the basic set of beliefs that you have (i.e., at a philosophical level ) and how these influence the way you do research (i.e., the practical aspects of doing a dissertation). We all have these basic sets of beliefs , but you may not know what they are or what to call them. Whilst they can be very abstract and complicated to understand, we have tried to make these as straightforward as possible in the Research Paradigms section of the Fundamentals part of Lærd Dissertation.

Your dissertation guidelines may not mention the need to discuss research paradigms or research philosophies ; and in some cases, your supervisor may have explicitly told you not to include them. If this is the case, move onto STEP TWO: Research design . However, since most students have to produce a Research Paradigm section within their Research Strategy chapter (usually Chapter Three: Research Strategy ), even if their dissertation guidelines do not mention such things, it is still worth checking with your supervisor whether this is a requirement. If you leave it out at the start, but are later told it needs to be included, it can be much more difficult to incorporate at a later date. This is because when applied properly to your research, it is so instrumental in shaping the choices you make when setting your research strategy, as well as affecting the conclusions that you make based on your findings (something that we discuss in Chapter Five: Discussion/Conclusions within the Route #1: Chapter-by-Chapter part of Lærd Dissertation).

Since you are taking on a Route #1: Replication-based dissertation , you will ideally need to understand the research paradigm that underpins your main journal article so that you can compare this with your chosen research paradigm. Unfortunately, journal articles rarely state the research paradigm that underpinned their research, usually because journals do not require such information to be included, or because many academics will either not think about such things or they will be implicit in the way that the research was carried out or written up. Since understanding the principals and characteristics of research paradigms can be a difficult process in and of itself, especially at the undergraduate and master's level where you're limited in the time you'll have to look into such things, this makes it very tricky to recognize the characteristics of different research paradigms in the main journal article you are interested in. As a result, assuming that including a Research Paradigm section within your Research Strategy chapter is a must, this leaves you with two choices:

Option A Focus on the research paradigm guiding your dissertation

If a difference in the research paradigm underpinning the research in the main journal article and your dissertation is not a major justification for your choice of route or the approach within that route, we would suggest ignoring the research paradigm used in the main journal article, and simply thinking about the research paradigm you want to use in your dissertation. To do this, you'll need to think about your basic set of beliefs , since it is these beliefs that you have (i.e., at a philosophical level ), which influence the way you do research (i.e., the practical aspects of doing a dissertation). Ultimately, since you are doing a quantitative dissertation, this will most likely lead you to choose between a positivist or post-positivist research paradigm. However, it is worth noting that there are other research paradigms that may be appropriate when taking on a quantitative dissertation, as well as different ways of describing such research paradigms (e.g., the way that post-positivism is characterised can be very different between texts). Nonetheless, to (a) learn more about these two paradigms, (b) how to choose between them, and (c) some of the implications that your choice will have for the rest of your research strategy, jump to the Research Paradigms section of the Fundamentals part of Lærd Dissertation now.

Option B Learn how to recognize some of the main characteristics of research paradigms in a piece of research

If a difference in the research paradigm underpinning the research in the main journal article and your dissertation is a major justification for your choice of route or the approach within that route, we would suggest learning how to recognize some of the main characteristics of research paradigms in a piece of research. A research paradigm can act as a major justification for your choice of route and approach when the choice of research paradigm in the main journal article has led to a potential flaw or limitation in the main journal article. Take the following example:

Example A Research paradigms and "wild assertions" Imagine that the authors of your main journal article made what you would consider to be "wild assertions" when it came to saying how far their findings could be generalised. To illustrate this, imagine that your main journal article examined the relationship between teaching method and exam performance , concluding that the use of seminars in addition to lectures improved exam performance amongst the population of undergraduate students at a single university . But what if in the Discussion section of the main journal article, the authors had concluded that: The addition of seminars to lectures improves exam performance amongst university students . The authors are making the assertion that their results can be generalised not only to the population that they investigated (i.e., undergraduate students at a single university in the United States), but a much wider population (i.e., all types of student - undergraduates, postgraduates, part-time students, full-time students, etc. - and all universities, wherever they may be in the world). Now such an assertion could simply reflect a loose writing style , which could be criticised for being nothing more than that, but it could also reflect a particular basic set of beliefs (i.e., those beliefs that form part of a research paradigm known as positivism , which without going into any detail at this stage, are more inclined to support context-free generalisations such as these). If your basic set of beliefs differed from these, and you felt that such assertions could not be made about the findings from the main journal article, this would be a philosophical justification to test the different populations , settings/contexts , treatments and time in which the findings from the original study hold (i.e., a Route B: Generalisation -based justification).

To learn how to recognize the characteristics of different research paradigms in journal articles, start by learning about the two main research paradigms you are likely to come across in quantitative research, positivism and post-positivism , in the Research Paradigms section of the Fundamentals part of Lærd Dissertation.

By the end of STEP ONE: Research paradigm , you should be able to state , describe and justify the research paradigm underpinning your dissertation (i.e., typically a positivist or post-positivist research paradigm), and if using a philosophical justification for your choice of route, and approach within that route, explain your philosophical justification.

Research Paradigm: An Introduction with Examples

This article provides a detailed and easy-to-understand introduction to research paradigms, including examples.

If you are considering writing a research paper, you should be aware that you must set criteria for constructing the approach you will use as a methodology in your work, which is why you must comprehend the concept of the research paradigm .

A research paradigm , in simplest terms, is the process of constructing a research plan that can assist you in quickly understanding how the theories and practices of your research project work.

The purpose of this article is to introduce you to research paradigms and explain them to you in the most descriptive way possible using examples. 

What is a research paradigm?

A research paradigm is a method, model, or pattern for conducting research. It is a set of ideas, beliefs, or understandings within which theories and practices can function. The majority of paradigms derive from one of two research methodologies: positivism or interpretivism . Every research project employs one of the research paradigms as a guideline for creating research methods and carrying out the research project most legitimately and reasonably. 

Though there were essentially two paradigms, various new paradigms have arisen from these two, particularly in social science research. Keep in mind that selecting one of the paradigms for your research project demands a thorough understanding of the unique characteristics of each approach.

What are the 3 paradigms of research?

To select the best research paradigm for your project, you must first comprehend the three pillars: ontology, epistemology, and methodology.

Ontology is a philosophical theory regarding the nature of reality, asserts that there is either a single reality or none at all. To be more specific, ontology answers the question, “ What is reality? ” 

Epistemology

Epistemology is the study of knowledge, focusing on the validity, extent, and ways of gaining knowledge. Epistemology seeks to address the question, “ How can we know reality? “

Methodology

Methodology refers to general concepts that underpin how one explores the social environment and proves the validity of the knowledge gained. The methodological question is “ How to go about discovering the reality/answer? “

What is the purpose of a research paradigm?

The importance of choosing a paradigm for a research project stems from the fact that it establishes the foundation for the study’s research and its methodologies. 

A paradigm investigates how knowledge is understood and researched, and it explicitly outlines the objective, motivation, and expected outcomes of the research. 

The proper implementation of a research paradigm in research provides researchers with a clear path to examine the topic of interest. 

As a result, it gives a logical and deliberate structure for carrying it out, besides improving the quality of your work and your proficiency.

Research paradigms examples

Now that you understand the three pillars and the importance of the research paradigm, let’s look at some examples of paradigms that you may use in your research.

Positivist Paradigm

Positivists believe in a single reality that can be measured and understood. As a result, quantitative approaches are utilized to quantify this reality. 

Positivism in research is a philosophy related to the concept of real inquiry. A positivism-based research philosophy employs a rigorous approach to the systematic study of data sources.

Interpretivism or Constructivism Paradigm

The interpretivism approach is used in the majority of qualitative research conducted in the social sciences; it is predicated on the existence of numerous realities rather than a single reality. 

According to interpretivists, human behavior is complex and cannot be predicted by predefined probability. 

Human behavior is not like a scientific variable that can be easily controlled. The word interpretivism refers to methods of gaining knowledge of the universe that rely on interpreting or comprehending the meanings that humans attach to their behaviors. 

Pragmatism Paradigm

The research question determines pragmatism. Depending on the nature of the research issue, pragmatics may incorporate both positivism and interpretivism approaches within a single study. 

It is a problem-solving philosophy that maintains that the best research techniques are those that contribute to the most effective answer to the research issue. This is followed by an examination of many aspects of a research problem using a combination of quantitative and qualitative approaches. 

Postpositivism Paradigm

The positivism paradigm gave way to the postpositivism paradigm, which is more concerned with the subjectivity of reality and departs from the logical positivists’ objective perspective. 

Postpositivism seeks objective answers by striving to recognize and deal with such biases in the ideas and knowledge developed by researchers.

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What is a Research Paradigm? Types of Research Paradigms with Examples

If you’re a researcher, you’ve probably heard the term “ research paradigm .” And, if you are a researcher, especially if you haven’t been trained under the social sciences, you are probably confused by the concept of a research paradigm . What is a research paradigm? How does it apply to my research? Why is it important? 

Research paradigms refer to the beliefs and assumptions that provide the structure for your research. These can be characteristics of your discipline or even your personal beliefs. For example, if you are a physical scientist and you are conducting research on the performance of a newly developed catalyst for removing chemical impurities from drinking water, your study is probably based on the premise that there is one reality, and your results will show that the new product either works better or it doesn’t. However, if your research discipline is education and you’re looking at the effects of parental literacy rates on the literacy or academic success of their children, you will not expect a such a definite result, and you may be examining your topic from different viewpoints, such as cultural or socio-economic. Your findings will then depend on those assumptions, beliefs, and biases.  

The rest of this article will try to clarify the concept of research paradigms, provide a research paradigm definition, and offer some examples of different types of research paradigms . While years of study may not completely clear up your confusion about research paradigms , perhaps you will think a little better of them and how they can help you in your work and maybe even in your personal life.  

Table of Contents

What is a research paradigm?  

According to the Merriam-Webster Dictionary, a paradigm is “ a philosophical and theoretical framework of a scientific school or discipline within which theories, laws, and generalizations and the experiments performed in support of them are formulated. ” 1 As applied in the context of research, a research paradigm is a worldview or philosophical framework, including ideas, beliefs, and biases, that guides the research process. The research paradigm in which a study is situated helps determine the manner in which the research will be conducted.  

The research paradigm is the framework into which the theories and practices of your discipline fit to create the research plan. This foundation guides all areas of your research plan, including the aim of the study, research question, instruments or measurements used, and analysis methods.   

Most research paradigms are based on one of two model types: positivism or interpretivism. These guide the theories and methodologies used in the research project. In general, positivist research paradigms lead to quantitative studies and interpretivist research paradigms lead to qualitative studies. Of course, there are many variations of both of these research paradigm types, some of which lead to mixed-method studies.  

What are the three pillars of research paradigms ?     

So, now you may be asking, what makes up a research paradigm ? How are they formed and categorized? The research paradigm framework is supported by three pillars: ontology, epistemology, and methodology. Some scholars have recently begun adding another pillar to research paradigms : ethics or axiology. However, this article will only discuss the three traditional aspects, which together define the research paradigm and provide the base on which to build your research project.  

Ontology is the study of the nature of reality. Is there a single reality, multiple realities, or no reality at all? These are the questions that the philosophy of ontology attempts to answer. The oft-used example of an ontological question is “Does God exist?” Two possible single realities exist: yes or no.  

Think about your research project with this in mind; that is, does a single reality exist within your research? If you’re a medical researcher, the answer is probably yes. You’re looking for specific results that ideally have clear yes or no answers. If you’re an anthropologist, there probably isn’t one clear, specific answer to your research question but multiple possible realities, and the study results are interpreted through the researcher’s viewpoint or paradigm.  

Epistemology is the study of knowledge and how we can know reality. It incorporates the extent and ways to gain knowledge and how to validate that knowledge. A frequently used example question in epistemology is “How is it possible to know whether or not God exists?”  

The epistemology of your research project will help determine your approach to your study. For example, if the medical researcher believes there is one singular truth, an objective approach will be taken. On the other hand, if the anthropologist believes in multiple realities viewed through a cultural lens, the research results will be more subjective and understood only in the proper context. This difference divides research studies into those using quantitative and qualitative techniques.  

Methodology is the study of how one investigates the environment and validates the knowledge gained. It attempts to answer the question “how to go about discovering the answer/reality.” Addressing this pillar leads to specific data collection and analysis plans.   

The medical researcher may create a research plan that includes a clinical trial, during which blood tests that measure a specific protein are conducted. These results are then analyzed, with a focus on differences within groups. The anthropologist, on the other hand, may conduct observations, examine artifacts, or set up interviews to determine certain aspects of reality within the context of a group’s culture. In this situation, yes or no answers are not sought but a truth is discovered.  

What is the purpose of research paradigms ?  

Put all the information about the three pillars of a research paradigm together, and you can see the purpose of research paradigms . Research paradigms establish the structure and foundation for a research project.   

Once the research paradigm has been determined, an appropriate research plan can be created. The philosophical basis of the study guides what knowledge is sought, how that knowledge can be discovered, and how to form the collected information or data into the knowledge being sought. The research paradigm clearly outlines the path to investigate your topic. This brings clarity to your study and improves the quality of your methods and analysis.  

In addition, it is important for researchers to understand how their own beliefs, assumptions, and biases can affect the research process. The study’s data collection, analysis, and interpretation will be impacted by the worldview of the researcher. Knowing the underlying research paradigm and how it frames the study allows researchers to better understand the effect of their perspective on the study results.   

Types of research paradigms  

As mentioned previously, there are two basic types of research paradigms , from which other frequently used paradigms are derived. This section will briefly describe these two major research paradigms .   

Positivist paradigm – Proponents of a positivist paradigm believe that there is a single reality that can be measured and understood. Therefore, these researchers are likely to utilize quantitative methods in their studies. The research process for positivist paradigm studies tend to propose an empirical hypothesis, which is then supported or refuted through the data collection and analysis. Positivists approach research in an objective manner and statistically investigate the existence of quantitative relationships between variables instead of looking for the qualitative reason behind those relationships. Researchers who subscribe to this paradigm also believe that the results of one study can be generalized to similar situations. Positivist paradigms are most frequently used by physical scientists.  

Interpretivism paradigm – Interpretivists believe in the existence of multiple realities rather than a single reality. This is the research paradigm used by the majority of qualitative studies conducted in the social sciences. Interpretivism holds that because human behavior is so complex, it cannot be studied by probabilistic models, such as those used under positivist paradigms . Knowledge can only be created by interpreting the meanings that people put on behaviors and events. Therefore, studies employing this framework are necessarily subjective and are greatly affected by the researcher’s personal viewpoint. Interpretivist paradigm research is conducted within the reality of those being studied, not in a contrived environment such as a laboratory. Because of the nature of interpretivist studies, their results are only valid under the particular circumstances of the study and are usually not generalizable.   

Research paradigm examples    

Positivist and interpretivist research paradigms , sometimes referred to as quantitative and qualitative paradigms, are the two major approaches to research. However, many other variations of these have been used. Following are brief descriptions of some of the more popular of these research paradigm variations.  

Pragmatism paradigm – Pragmatists believe that reality is continually changing amid the flow of constantly changing situations. Therefore, rather than use a single research paradigm , they employ the framework that is most applicable to the research question they are examining. Both qualitative and quantitative techniques are often used as positivist and interpretivist approaches are combined. Pragmatists believe that the best research method is the one that will most effectively address the research question.  

Constructivist paradigm – Like interpretivists, constructivists believe that there are numerous realities, not a single reality. The constructivist paradigm holds that people construct their own understanding of the world through experiencing and reflecting on those experiences. Constructivist research seeks to understand the meanings that people attach to those experiences. Therefore, qualitative techniques, such as interviews and case studies, are frequently used. Constructivists are seeking the “why” of events. Constructivism is also a popular theory of learning that focuses on how children and other learners create knowledge from their experiences and learn better through experimentation than through direct instruction.  

Post-positivism paradigm – Post-positivists veer away from the concept of reality as being an absolute certainty and view it instead in a more probabilistic manner, thus taking a more subjective viewpoint. They believe that research outcomes can never be totally objective and a researcher’s worldview and biases can never be completely removed from the research results.  

Transformative paradigm – Proponents of transformative research reject both positivism and interpretivism, believing that these frameworks do not accurately represent the experiences of marginalized communities. Transformative researchers generally use both qualitative and quantitative techniques to better understand the disparities in community relationships, support social justice, and ultimately ensure transformative change.    

Combining research paradigms    

While most research is based on either a positivist (quantitative) or interpretivist (qualitative) foundations, some studies combine both. For example, quantitative and qualitative techniques are frequently used together in psychology studies. These types of studies are referred to as mixed-method research. Some research paradigms are themselves combinations of other paradigms and frequently employ all the associated research methods. Post-positivism combines the paradigms of positivism and interpretivism.  

5 steps to a paradigm shift  

Research studies aren’t the only things that can be considered to have paradigms. Researchers themselves bring a specific worldview to their work and produce higher quality work when they are aware of the effect their perspective has on their results. Understanding all the aspects of a personal paradigm, including beliefs, habits, and behaviors, can make it possible for that paradigm to be changed. Here are suggested steps to successfully shift your personal paradigm and increase the quality of your research 2 .  

• Identify the paradigm element you want to change – what part of your worldview do you want to change? What habitual or hidden behavior may be adversely affecting your research or your life? 
• Write down your goals – setting specific desired outcomes and putting them down on paper sets them in your subconscious.   
• Adjust your mindset – intentionally influencing your thoughts to support your goals can motivate you to create the change you want. Some suggested activities to help with this include journaling, reading motivational books, and spending time with like-minded people.  
• Do uncomfortable things – you need to get out of your comfort zone to effect real change. This will get your subconscious out of its usual habits and move you toward your goal.  
• Practice being who you want to be – the change you want will become solidified and part of your new paradigm once you break out of your old habit and keep repeating the new behavior so as to cement it in your subconscious.  

References:  

• Merriam-Webster Dictionary. https://www.merriam-webster.com/dictionary/paradigm [Accessed March 10, 2023]  
• What is research paradigm – explanation and examples. Peachy Essay. https://peachyessay.com/blogs/what-is-research-paradigm/ [Accessed March 10, 2023]  

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Based on 21+ years of experience in academia, Researcher.Life All Access empowers researchers to put their best research forward and move closer to success. Explore our top AI Tools pack, AI Tools + Publication Services pack, or Build Your Own Plan. Find everything a researcher needs to succeed, all in one place –  Get All Access now starting at just $17 a month !    

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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Research Paradigms

A lot of effort can be spent refining and calibrating a research question to fully understand what kind of data could be collected and what kind of validity analysis might offer when answering the question. Researchers rarely proceed by choosing an ontology, epistemology and axiology separately and then deciding which research method to apply. Instead, the starting point will usually be a research question framed within a particular paradigm. It’s also common in practice for researchers to identify the method they will use (perhaps determined by the data that is available) and then articulate the theoretical justification behind it by drawing on a paradigm.

Kuhn’s (1962) The Structure of Scientific Revolutions is one of the most influential works on the philosophy of science, and is credited with introducing the idea of competing paradigms (or “disciplinary matrices”) in research. Kuhn investigated the,way that scientific practices evolve over time, arguing that we don’t have a simple,progression from “less knowledge” to “more knowledge” because the way that we,approach inquiry is changing over time. This can happen gradually, but results in,moments of change where our understanding of a phenomenon changes more,radically (such as in the transition from Newtonian to Einsteinian physics; or from,Lamarckian to Darwinian theories of evolution).

There are four stages in the cycle of science in Kuhn’s approach. Firstly, a pre-paradigmatic state where competing approaches share no consensus. Secondly, the “normal” state where there is wide acceptance of a particular set of methods and assumptions. Thirdly, a state of crisis where anomalies that cannot be solved within the existing paradigm emerge and competing theories to address them follow. Fourthly, a revolutionary phase where some new paradigmatic approach becomes dominant and supplants the old. Schnieder (2009) suggests that the Kuhnian phases are characterised by different kinds of scientific activity.

Newer approaches often build upon rather than replace older ones, but they also overlap and can exist within a state of competition. Scientists working within a particular paradigm often share methods, assumptions and values. In addition to supporting specific methods, research paradigms also influence things like the ambition and nature of research, the researcher-participant relationship and how the role of the researcher is understood.

For studies that look into paradigmatic change within open education research, see Bozkurt (2019) and Weller et al. (2018). Next we will go on to look at methods associated with different research paradigms.

Research Methods Handbook Copyright © 2020 by Rob Farrow; Francisco Iniesto; Martin Weller; and Rebecca Pitt is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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A research paradigm is a set of commonly held beliefs and assumptions within a research community about ontological, epistemological, and methodological concerns. This chapter starts by introducing two well-established research paradigms, positivism and interpretivism, and discusses their role in design science research. We also present two alternative research paradigms, critical realism and critical theory, and show how these can influence design science work.

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Aljafari R, Khazanchi D (2013) On the veridicality of claims in design science research. In: 2013 46th Hawaii international conference on system sciences (HICSS), January 2013, pp 3747–3756

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Horkheimer M et al. (1975) Critical theory: selected essays. 1st edn. Continuum Publishing Corporation, New York

Kuhn TS (2012). The structure of scientific revolutions: 50th anniversary edition, 4th edn. University of Chicago Press, Chicago

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Vaishnavi V, Kuechler W (2004) Design research in information systems. http://www.desrist.org/desrist/ . Accessed 26 June 2014

Weber R (2004) Editor’s comments: the rhetoric of positivism versus interpretivism: a personal view. MIS Q 28(1), iii–xii

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• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Think of yourself as an intrepid explorer with only a compass and a map exploring the unknown. Now, imagine that the compass is your research paradigm, guiding you through the labyrinth of knowledge, and the map represents the various methodologies at your disposal. Sounds intriguing, No?

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Well, buckle up because we're about to embark on a fascinating journey of exploring the world of research paradigms!

In this article, we will unfold the mysteries of research paradigms and how they can provide a strong foundation for your research endeavours.

What is Paradigm in Research?

A research paradigm can be defined as a distinctive framework encompassing a set of beliefs, values, and techniques shared by research community members. These paradigms serve as vital compasses, guiding researchers in their quest for knowledge and shaping their interpretations of empirical data. According to Wikipedia, it is a theoretical framework that underpins the entire research process, including the choice of research questions, data collection methods, and data analysis techniques. By understanding the meaning and implications of research paradigms, scholars can navigate the intricacies of their inquiries with greater clarity and precision.

Types of Research Paradigms

●       quantitative research paradigm.

A systematic investigation employs numerical data to identify and analyze patterns, relationships, and trends among variables.

Key Features of Quantitative Research

• Structured data collection
• Statistical analysis
• Hypothesis testing
• Objectivity and generalizability
• Experimental design

●       Qualitative Research Paradigm

Research Paradigm Example for Qualitative: An ethnographer immerses themselves within a community to explore the group's cultural nuances and social dynamics.

Key Features of Qualitative Research: Qualitative research delves into the subjective experiences, perceptions, and meanings individuals ascribe to their lived realities. This paradigm utilizes in-depth interviews, observations, and narrative analysis to uncover the rich tapestry of human experiences.

●       Theoretical Paradigm in Research

Theoretical Paradigm in Research Example : A sociologist utilizes critical race theory to analyze the impact of systemic racism on educational access and equity.

Role of Theory in Shaping Research Paradigms: Theory plays a vital role in shaping research paradigms by providing the conceptual framework, guiding research questions, and influencing methodology choices, ultimately impacting the interpretation of study outcomes.

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The paradigm of the study in research.

The paradigm of the study in research is the fundamental framework guiding the research process. It encompasses the researcher's beliefs, theories, and approaches, shaping the research questions , methodology, and interpretation of results.

Some common examples of paradigms of the study in research include positivism, interpretivism, pragmatism, and critical theory.

However, choosing the right paradigm for the study example ensures its validity and relevance, enabling researchers to explore their topic thoroughly. With a proper understanding of the paradigm, you can provide meaningful insights and see things from a bigger perspective.

How to Make Research Paradigm Research Paradigms: Steps to Creating Them

• Identify the research question.
• Create a questionnaire around the topic.
• Select the appropriate paradigm.
• Choose a research paradigm that aligns with your objectives.
• Outline relevant theoretical frameworks or models
• Identify the underlying philosophical perspectives

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Step-by-Step Guide How to Write Research Paradigm Effectively

• Articulate the Rationale

Begin by explaining the reasons for choosing the specific paradigm and how it aligns with the research objectives.

• Describe the Research Methods:

Detail the research methods from the chosen paradigm, such as data collection techniques, analysis methods, and study design.

• Provide Examples:

Provide practical examples of how the selected paradigm will inform your research approach and outcomes.

• Be Clear and Concise:

Ensure your writing is easy to understand, jargon-free, and void of unnecessary information. Clearly articulate the rationale for the chosen paradigm, demonstrate its alignment with the study objectives, and highlight the specific research methods that stem from it.

Example of Research Paradigm in Thesis

Research Writing 101: A Guide on How to Write A Strong Hypothesis for a Research

Researchers might use interpretivism in a study about social media's effect on mental health. This approach focuses on understanding people's personal experiences and thoughts. They could use interviews and group discussions to gather information and then analyze the findings by themes. This method recognizes that people's realities are shaped by society, and everyone has different viewpoints. Interpretivism helps researchers understand how individuals feel about social media and mental health .

Research Paradigm Example with Explanation

A research paradigm is a theoretical framework that guides researchers in collecting, analyzing, and interpreting data.

How to Restating Your Thesis: A Beginner’s Guide & Examples

Here are three common paradigm research examples:

1.     Positivism

Positivism is a way of knowing things that believes there's one real truth outside human opinions. It supports using science, numbers, and facts to understand how things work. Positivists try to find cause-and-effect relationships and make reliable predictions based on real information.

2.     Constructivism

Constructivism is a way of thinking that believes reality is created from personal experiences and social interactions. This idea highlights that it's important to understand the detailed meanings people give to their experiences to make sense of the complex human world.

3.     Pragmatism

A flexible way of thinking avoids strict rules and set methods. By supporting adaptability, practical thinkers combine different ways to solve specific problems. They use numbers and personal experiences in their research, focusing on useful evidence that helps make smart choices and deal with real-life issues.

In the end, understanding the basics of research paradigms is crucial for any researcher to conduct meaningful and rigorous scientific inquiry. The paradigm of the study in research shapes a researcher's approach to knowledge production, guiding their choice of methodology and data analysis.

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How to write a research proposal

What is a research proposal.

A research proposal should present your idea or question and expected outcomes with clarity and definition – the what.

It should also make a case for why your question is significant and what value it will bring to your discipline – the why. 

What it shouldn't do is answer the question – that's what your research will do.

Why is it important?

Research proposals are significant because Another reason why it formally outlines your intended research. Which means you need to provide details on how you will go about your research, including:

• your approach and methodology
• timeline and feasibility
• all other considerations needed to progress your research, such as resources.

Think of it as a tool that will help you clarify your idea and make conducting your research easier.

How long should it be?

Usually no more than 2000 words, but check the requirements of your degree, and your supervisor or research coordinator.

Presenting your idea clearly and concisely demonstrates that you can write this way – an attribute of a potential research candidate that is valued by assessors.

What should it include?

Project title.

Your title should clearly indicate what your proposed research is about.

Research supervisor

State the name, department and faculty or school of the academic who has agreed to supervise you. Rest assured, your research supervisor will work with you to refine your research proposal ahead of submission to ensure it meets the needs of your discipline.

Proposed mode of research

Describe your proposed mode of research. Which may be closely linked to your discipline, and is where you will describe the style or format of your research, e.g. data, field research, composition, written work, social performance and mixed media etc. 

This is not required for research in the sciences, but your research supervisor will be able to guide you on discipline-specific requirements.

Aims and objectives

What are you trying to achieve with your research? What is the purpose? This section should reference why you're applying for a research degree. Are you addressing a gap in the current research? Do you want to look at a theory more closely and test it out? Is there something you're trying to prove or disprove? To help you clarify this, think about the potential outcome of your research if you were successful – that is your aim. Make sure that this is a focused statement.

Your objectives will be your aim broken down – the steps to achieving the intended outcome. They are the smaller proof points that will underpin your research's purpose. Be logical in the order of how you present these so that each succeeds the previous, i.e. if you need to achieve 'a' before 'b' before 'c', then make sure you order your objectives a, b, c.

A concise summary of what your research is about. It outlines the key aspects of what you will investigate as well as the expected outcomes. It briefly covers the what, why and how of your research. 

A good way to evaluate if you have written a strong synopsis, is to get somebody to read it without reading the rest of your research proposal. Would they know what your research is about?

Now that you have your question clarified, it is time to explain the why. Here, you need to demonstrate an understanding of the current research climate in your area of interest.

Providing context around your research topic through a literature review will show the assessor that you understand current dialogue around your research, and what is published.

Demonstrate you have a strong understanding of the key topics, significant studies and notable researchers in your area of research and how these have contributed to the current landscape.

Expected research contribution

In this section, you should consider the following:

• Why is your research question or hypothesis worth asking?
• How is the current research lacking or falling short?
• What impact will your research have on the discipline?
• Will you be extending an area of knowledge, applying it to new contexts, solving a problem, testing a theory, or challenging an existing one?
• Establish why your research is important by convincing your audience there is a gap.
• What will be the outcome of your research contribution?
• Demonstrate both your current level of knowledge and how the pursuit of your question or hypothesis will create a new understanding and generate new information.
• Show how your research is innovative and original.

Draw links between your research and the faculty or school you are applying at, and explain why you have chosen your supervisor, and what research have they or their school done to reinforce and support your own work. Cite these reasons to demonstrate how your research will benefit and contribute to the current body of knowledge.

Proposed methodology

Provide an overview of the methodology and techniques you will use to conduct your research. Cover what materials and equipment you will use, what theoretical frameworks will you draw on, and how will you collect data.

Highlight why you have chosen this particular methodology, but also why others may not have been as suitable. You need to demonstrate that you have put thought into your approach and why it's the most appropriate way to carry out your research. 

It should also highlight potential limitations you anticipate, feasibility within time and other constraints, ethical considerations and how you will address these, as well as general resources.

A work plan is a critical component of your research proposal because it indicates the feasibility of completion within the timeframe and supports you in achieving your objectives throughout your degree.

Consider the milestones you aim to achieve at each stage of your research. A PhD or master's degree by research can take two to four years of full-time study to complete. It might be helpful to offer year one in detail and the following years in broader terms. Ultimately you have to show that your research is likely to be both original and finished – and that you understand the time involved.

Provide details of the resources you will need to carry out your research project. Consider equipment, fieldwork expenses, travel and a proposed budget, to indicate how realistic your research proposal is in terms of financial requirements and whether any adjustments are needed.

Bibliography

Provide a list of references that you've made throughout your research proposal. 

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