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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 January 23, 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, 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.
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.
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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.
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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What (Exactly) Is A Research Proposal?
A simple explainer with examples + free template.
By: Derek Jansen (MBA) | Expert Reviewed By: Dr Eunice Rautenbach | June 2020
If you’re nearing the end of your degree program and your dissertation or thesis is on the horizon, or you’re planning to apply for a PhD program, chances are you’re going to need to craft a convincing research proposal . If you’re on this page, you’re probably unsure exactly what the research proposal is all about. Well, you’ve come to the right place.
Overview: Research Proposal Basics
- What a dissertation or thesis research proposal is
- What things a research proposal needs to cover
- How long a research proposal needs to be
- How to structure and write up a proposal
What is a research proposal?
A research proposal is a simply a structured, formal document that explains what you plan to research (i.e. your research topic), why it’s worth researching (i.e. your justification), and how you plan to investigate it (i.e. your practical approach).
The purpose of the research proposal (it’s job, so to speak) is to convince your research supervisor, committee or university that your research is suitable (for the requirements of the degree program) and manageable (given the time and resource constraints you will face).
The most important word here is “ convince ” – in other words, your research proposal needs to sell your research idea (to whoever is going to approve it). If it doesn’t convince them (of its suitability and manageability), you’ll need to revise and resubmit . This will cost you valuable time, which will either delay the start of your research or eat into its time allowance (which is bad news).
What goes into a research proposal?
As we mentioned earlier, a good dissertation or thesis proposal needs to cover the “what”, the “why” and the “how” of the research. Let’s look at each of these in a little more detail:
Your proposal needs to clearly articulate your research topic. This needs to be specific and unambiguous . Your research topic should make it clear exactly what you plan to research and in what context. Here’s an example:
Topic: An investigation into the factors which impact female Generation Y consumer’s likelihood to promote a specific makeup brand to their peers: a British context
As you can see, this topic is extremely clear. From this one line we can see exactly:
- What’s being investigated – factors that make people promote a brand of makeup
- Who it involves – female Gen-Y consumers
- In what context – the United Kingdom
So, make sure that your research proposal provides a detailed explanation of your research topic. It should go without saying, but don’t start writing your proposal until you have a crystal-clear topic in mind, or you’ll end up waffling away a few thousand words.
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As we touched on earlier, it’s not good enough to simply propose a research topic – you need to justify why your topic is original . In other words, what makes it unique ? What gap in the current literature does it fill? If it’s simply a rehash of the existing research, it’s probably not going to get approval – it needs to be fresh.
But, originality alone is not enough. Once you’ve ticked that box, you also need to justify why your proposed topic is important . In other words, what value will it add to the world if you manage to find answers to your research questions ?
For example, let’s look at the sample research topic we mentioned earlier (factors impacting brand advocacy). In this case, if the research could uncover relevant factors, these findings would be very useful to marketers in the cosmetics industry, and would, therefore, have commercial value . That is a clear justification for the research.
So, when you’re crafting your research proposal, remember that it’s not enough for a topic to simply be unique. It needs to be useful and value-creating – and you need to convey that value in your proposal. If you’re struggling to find a research topic that makes the cut, watch our video covering how to find a research topic .
It’s all good and well to have a great topic that’s original and important, but you’re not going to convince anyone to approve it without discussing the practicalities – in other words:
- How will you undertake your research?
- Is your research design appropriate for your topic?
- Is your plan manageable given your constraints (time, money, expertise)?
While it’s generally not expected that you’ll have a fully fleshed out research strategy at the proposal stage, you will need to provide a high-level view of your research methodology and some key design decisions. Here are some important questions you’ll need to address in your proposal:
- Will you take a qualitative or quantitative approach ?
- Will your design be cross-sectional or longitudinal ?
- How will you collect your data ( interviews , surveys , etc)?
- How will you analyse your data (e.g. statistical analysis, qualitative data analysis , etc)?
So, make sure you give some thought to the practicalities of your research and have at least a basic understanding of research methodologies before you start writing up your proposal. The video below provides a good introduction to methodology.
How long is a research proposal?
This varies tremendously, depending on the university, the field of study (e.g., social sciences vs natural sciences), and the level of the degree (e.g. undergraduate, Masters or PhD) – so it’s always best to check with your university what their specific requirements are before you start planning your proposal.
As a rough guide, a formal research proposal at Masters-level often ranges between 2000-3000 words , while a PhD-level proposal can be far more detailed, ranging from 5000-8000 words . In some cases, a rough outline of the topic is all that’s needed, while in other cases, universities expect a very detailed proposal that essentially forms the first three chapters of the dissertation or thesis.
The takeaway – be sure to check with your institution before you start writing.
How is a research proposal structured?
While the exact structure and format required for a dissertation or thesis research proposal differs from university to university, there are five “ essential ingredients ” that typically make up the structure of a research proposal:
- A descriptive title or title page
- A rich introduction and background to the proposed research
- A discussion of the scope/delimitations of the research
- An initial literature review covering the key research in the area
- A discussion of the proposed research design (methodology)
For a detailed explanation of each of these, and step by step guidance covering how to write a research proposal, have a look at this video post . You might also consider using our free research proposal template here .
Final thoughts
As you write up your research proposal, remember the all-important core purpose: to convince . Your research proposal needs to sell your research idea in terms of suitability and viability. So, focus on crafting a convincing narrative and you’ll have won half the battle.
Psst… there’s more (for free)
This post is part of our research writing mini-course, which covers everything you need to get started with your dissertation, thesis or research project.
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41 Comments
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You’re most welcome. We don’t have any research proposals that we can share (the students own the intellectual property), but you might find our research proposal template useful: https://gradcoach.com/research-proposal-template/
Cheruiyot Moses Kipyegon
Thanks alot. It was an eye opener that came timely enough before my imminent proposal defense. Thanks, again
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Thank you. This is a great insight. I am a student preparing for a PhD program. I am requested to write my Research Proposal as part of what I am required to submit before my unconditional admission. I am grateful having listened to this video which will go a long way in helping me to actually choose a topic of interest and not just any topic as well as to narrow down the topic and be specific about it. I indeed need more of this especially as am trying to choose a topic suitable for a DBA am about embarking on. Thank you once more. The video is indeed helpful.
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Hi. For my MSc medical education research, please evaluate this topic for me: Training Needs Assessment of Faculty in Medical Training Institutions in Kericho and Bomet Counties
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I need any research proposal
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How to Write a Research Design – Guide With Examples
Published by Alaxendra Bets at August 14th, 2021 , Revised On January 9, 2023
A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the research questions .
It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design. Below are the key aspects of the decision-making process:
- Data type required for research
- Research resources
- Participants required for research
- Hypothesis based upon research question(s)
- Data analysis methodologies
- Variables (Independent, dependent, and confounding)
- The location and timescale for conducting the data
- The time period required for research
The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.
Your project’s validity depends on the data collection and interpretation techniques. A strong research design reflects a strong dissertation , scientific paper, or r esearch proposal .
The research design can be divided into five broad categories; descriptive, experimental, correlational, diagnostic, and explanatory.
Step 1: Establish Priorities for Research Design
Before conducting any research study, you must address an important question: “how to create a research design.”
The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.
Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.
If one research design is weak in one area, then another research design can cover that weakness. For instance, a dissertation analyzing different situations or cases will have more than one research design.
For example:
- Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
- Quantitative research is good for the statistical part of the project, but it may not provide an in-depth understanding of the topic .
- Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.
While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;
- Do you have enough time to gather data and complete the write-up?
- Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
- Do you have in-depth knowledge about the different statistical analysis and data collection techniques to address the research questions or test the hypothesis ?
If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.
Step 2: Data Type You Need for Research
Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:
Primary Data Vs. Secondary Data
Qualitative vs. quantitative data.
Also, see; Research methods, design, and analysis .
What data collection method best suits your research?
- Find out by hiring an expert from Research Prospect today!
- Despite how challenging the subject may be, we are here to help you.
Step 3: Data Collection Techniques
Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.
It is time to determine your research method to address the research problem . Research methods involve procedures, techniques, materials, and tools used for the study.
For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your dissertation’s structure .
The following table shows the characteristics of the most popularly employed research methods.
Research Methods
Step 4: Procedure of Data Analysis
Use of the correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;
Quantitative Data Analysis
The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.
This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.
Qualitative Data Analysis
Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.
You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.
Step 5: Write your Research Proposal
The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results and conclusion .
Read our guidelines to write a research proposal if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.
The research methodology or research design, on the other hand, is generally written in the past tense.
How to Write a Research Design – Conclusion
A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.
Above mentioned five steps are the answer to how to write a research design. So, follow these steps to formulate the perfect research design for your dissertation .
Research Prospect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part writing service.
Our dissertation writers are also able to help you with the full dissertation paper . No matter how urgent or complex you need may be, Research Prospect can help.
You May Also Like
Here we explore what is research problem in dissertation with research problem examples to help you understand how and when to write a research problem.
Struggling to find relevant and up-to-date topics for your dissertation? Here is all you need to know if unsure about how to choose dissertation topic.
Penning your dissertation proposal can be a rather daunting task. Here are comprehensive guidelines on how to write a dissertation proposal.
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Examples of research proposals
How to write your research proposal, with examples of good proposals.
Research proposals
Your research proposal is a key part of your application. It tells us about the question you want to answer through your research. It is a chance for you to show your knowledge of the subject area and tell us about the methods you want to use.
We use your research proposal to match you with a supervisor or team of supervisors.
In your proposal, please tell us if you have an interest in the work of a specific academic at York St John. You can get in touch with this academic to discuss your proposal. You can also speak to one of our Research Leads. There is a list of our Research Leads on the Apply page.
When you write your proposal you need to:
- Highlight how it is original or significant
- Explain how it will develop or challenge current knowledge of your subject
- Identify the importance of your research
- Show why you are the right person to do this research
- Research Proposal Example 1 (DOC, 49kB)
- Research Proposal Example 2 (DOC, 0.9MB)
- Research Proposal Example 3 (DOC, 55.5kB)
- Research Proposal Example 4 (DOC, 49.5kB)
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- Indian J Anaesth
- v.60(9); 2016 Sep
How to write a research proposal?
Department of Anaesthesiology, Bangalore Medical College and Research Institute, Bengaluru, Karnataka, India
Devika Rani Duggappa
Writing the proposal of a research work in the present era is a challenging task due to the constantly evolving trends in the qualitative research design and the need to incorporate medical advances into the methodology. The proposal is a detailed plan or ‘blueprint’ for the intended study, and once it is completed, the research project should flow smoothly. Even today, many of the proposals at post-graduate evaluation committees and application proposals for funding are substandard. A search was conducted with keywords such as research proposal, writing proposal and qualitative using search engines, namely, PubMed and Google Scholar, and an attempt has been made to provide broad guidelines for writing a scientifically appropriate research proposal.
INTRODUCTION
A clean, well-thought-out proposal forms the backbone for the research itself and hence becomes the most important step in the process of conduct of research.[ 1 ] The objective of preparing a research proposal would be to obtain approvals from various committees including ethics committee [details under ‘Research methodology II’ section [ Table 1 ] in this issue of IJA) and to request for grants. However, there are very few universally accepted guidelines for preparation of a good quality research proposal. A search was performed with keywords such as research proposal, funding, qualitative and writing proposals using search engines, namely, PubMed, Google Scholar and Scopus.
Five ‘C’s while writing a literature review
BASIC REQUIREMENTS OF A RESEARCH PROPOSAL
A proposal needs to show how your work fits into what is already known about the topic and what new paradigm will it add to the literature, while specifying the question that the research will answer, establishing its significance, and the implications of the answer.[ 2 ] The proposal must be capable of convincing the evaluation committee about the credibility, achievability, practicality and reproducibility (repeatability) of the research design.[ 3 ] Four categories of audience with different expectations may be present in the evaluation committees, namely academic colleagues, policy-makers, practitioners and lay audiences who evaluate the research proposal. Tips for preparation of a good research proposal include; ‘be practical, be persuasive, make broader links, aim for crystal clarity and plan before you write’. A researcher must be balanced, with a realistic understanding of what can be achieved. Being persuasive implies that researcher must be able to convince other researchers, research funding agencies, educational institutions and supervisors that the research is worth getting approval. The aim of the researcher should be clearly stated in simple language that describes the research in a way that non-specialists can comprehend, without use of jargons. The proposal must not only demonstrate that it is based on an intelligent understanding of the existing literature but also show that the writer has thought about the time needed to conduct each stage of the research.[ 4 , 5 ]
CONTENTS OF A RESEARCH PROPOSAL
The contents or formats of a research proposal vary depending on the requirements of evaluation committee and are generally provided by the evaluation committee or the institution.
In general, a cover page should contain the (i) title of the proposal, (ii) name and affiliation of the researcher (principal investigator) and co-investigators, (iii) institutional affiliation (degree of the investigator and the name of institution where the study will be performed), details of contact such as phone numbers, E-mail id's and lines for signatures of investigators.
The main contents of the proposal may be presented under the following headings: (i) introduction, (ii) review of literature, (iii) aims and objectives, (iv) research design and methods, (v) ethical considerations, (vi) budget, (vii) appendices and (viii) citations.[ 4 ]
Introduction
It is also sometimes termed as ‘need for study’ or ‘abstract’. Introduction is an initial pitch of an idea; it sets the scene and puts the research in context.[ 6 ] The introduction should be designed to create interest in the reader about the topic and proposal. It should convey to the reader, what you want to do, what necessitates the study and your passion for the topic.[ 7 ] Some questions that can be used to assess the significance of the study are: (i) Who has an interest in the domain of inquiry? (ii) What do we already know about the topic? (iii) What has not been answered adequately in previous research and practice? (iv) How will this research add to knowledge, practice and policy in this area? Some of the evaluation committees, expect the last two questions, elaborated under a separate heading of ‘background and significance’.[ 8 ] Introduction should also contain the hypothesis behind the research design. If hypothesis cannot be constructed, the line of inquiry to be used in the research must be indicated.
Review of literature
It refers to all sources of scientific evidence pertaining to the topic in interest. In the present era of digitalisation and easy accessibility, there is an enormous amount of relevant data available, making it a challenge for the researcher to include all of it in his/her review.[ 9 ] It is crucial to structure this section intelligently so that the reader can grasp the argument related to your study in relation to that of other researchers, while still demonstrating to your readers that your work is original and innovative. It is preferable to summarise each article in a paragraph, highlighting the details pertinent to the topic of interest. The progression of review can move from the more general to the more focused studies, or a historical progression can be used to develop the story, without making it exhaustive.[ 1 ] Literature should include supporting data, disagreements and controversies. Five ‘C's may be kept in mind while writing a literature review[ 10 ] [ Table 1 ].
Aims and objectives
The research purpose (or goal or aim) gives a broad indication of what the researcher wishes to achieve in the research. The hypothesis to be tested can be the aim of the study. The objectives related to parameters or tools used to achieve the aim are generally categorised as primary and secondary objectives.
Research design and method
The objective here is to convince the reader that the overall research design and methods of analysis will correctly address the research problem and to impress upon the reader that the methodology/sources chosen are appropriate for the specific topic. It should be unmistakably tied to the specific aims of your study.
In this section, the methods and sources used to conduct the research must be discussed, including specific references to sites, databases, key texts or authors that will be indispensable to the project. There should be specific mention about the methodological approaches to be undertaken to gather information, about the techniques to be used to analyse it and about the tests of external validity to which researcher is committed.[ 10 , 11 ]
The components of this section include the following:[ 4 ]
Population and sample
Population refers to all the elements (individuals, objects or substances) that meet certain criteria for inclusion in a given universe,[ 12 ] and sample refers to subset of population which meets the inclusion criteria for enrolment into the study. The inclusion and exclusion criteria should be clearly defined. The details pertaining to sample size are discussed in the article “Sample size calculation: Basic priniciples” published in this issue of IJA.
Data collection
The researcher is expected to give a detailed account of the methodology adopted for collection of data, which include the time frame required for the research. The methodology should be tested for its validity and ensure that, in pursuit of achieving the results, the participant's life is not jeopardised. The author should anticipate and acknowledge any potential barrier and pitfall in carrying out the research design and explain plans to address them, thereby avoiding lacunae due to incomplete data collection. If the researcher is planning to acquire data through interviews or questionnaires, copy of the questions used for the same should be attached as an annexure with the proposal.
Rigor (soundness of the research)
This addresses the strength of the research with respect to its neutrality, consistency and applicability. Rigor must be reflected throughout the proposal.
It refers to the robustness of a research method against bias. The author should convey the measures taken to avoid bias, viz. blinding and randomisation, in an elaborate way, thus ensuring that the result obtained from the adopted method is purely as chance and not influenced by other confounding variables.
Consistency
Consistency considers whether the findings will be consistent if the inquiry was replicated with the same participants and in a similar context. This can be achieved by adopting standard and universally accepted methods and scales.
Applicability
Applicability refers to the degree to which the findings can be applied to different contexts and groups.[ 13 ]
Data analysis
This section deals with the reduction and reconstruction of data and its analysis including sample size calculation. The researcher is expected to explain the steps adopted for coding and sorting the data obtained. Various tests to be used to analyse the data for its robustness, significance should be clearly stated. Author should also mention the names of statistician and suitable software which will be used in due course of data analysis and their contribution to data analysis and sample calculation.[ 9 ]
Ethical considerations
Medical research introduces special moral and ethical problems that are not usually encountered by other researchers during data collection, and hence, the researcher should take special care in ensuring that ethical standards are met. Ethical considerations refer to the protection of the participants' rights (right to self-determination, right to privacy, right to autonomy and confidentiality, right to fair treatment and right to protection from discomfort and harm), obtaining informed consent and the institutional review process (ethical approval). The researcher needs to provide adequate information on each of these aspects.
Informed consent needs to be obtained from the participants (details discussed in further chapters), as well as the research site and the relevant authorities.
When the researcher prepares a research budget, he/she should predict and cost all aspects of the research and then add an additional allowance for unpredictable disasters, delays and rising costs. All items in the budget should be justified.
Appendices are documents that support the proposal and application. The appendices will be specific for each proposal but documents that are usually required include informed consent form, supporting documents, questionnaires, measurement tools and patient information of the study in layman's language.
As with any scholarly research paper, you must cite the sources you used in composing your proposal. Although the words ‘references and bibliography’ are different, they are used interchangeably. It refers to all references cited in the research proposal.
Successful, qualitative research proposals should communicate the researcher's knowledge of the field and method and convey the emergent nature of the qualitative design. The proposal should follow a discernible logic from the introduction to presentation of the appendices.
Financial support and sponsorship
Conflicts of interest.
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- Research toolkit
7 simple steps to efficient research design with example
Dr dawid hanak.
- July 15, 2022
- No Comments
Wondering where to start your research project? Here are 7 steps to research design that you can apply today!
As we explained last week, Motivated Academics are curious to brainstorm and test new research ideas . But once you come up with your research idea and develop your hypothesis, how do you know what type of research design to use so that you collect reliable data? That’s where research design comes into the academic picture!
I want to emphasise one thing – the generation of new research ideas is one of the most crucial aspects that you will need to learn as an academic. Each research project and scholarly paper depends on your ideas. But great ideas without efficient research design process and research execution are just that – great ideas without meaningful outputs.
That’s why Motivated Academics are eager to TEST their innovative concepts and ideas to make sure these bring tangible benefits to the economy, society and environment we all live in.
How do you test your ideas then? Well, that’s what research design is for!
What is research design?
Let me first define what’s research design. According to Oxford Reference, a research design is “a detailed proposal relating to a defined piece of [research] endeavour, which includes a definition of a problem, subject, or hypothesis for investigation; the background and context to the investigation; the proposed means and methods of the investigation; the work plan and timetable; details of the proposed investigators, management arrangements, and quality control procedures; and a table of costs.”
This definition was originally presented for archaeological endeavours and activities, but I believe it can be extended to any research area. At the end of the day, it is all about defining the design of a scientifically sound method that will allow you to produce a sufficient amount of data to test your hypothesis.
How to design your research in 6 simple steps?
Now that you know what research design is, let me share a simple 7-step framework that will help you develop a well-planned research design. I’ll try to support this research design with example where possible.
Step 1: Reflect on your hypothesis
The hypothesis you’ve developed for your research includes a piece of crucial information about your research question and variables that you want to evaluate.
Therefore, your research design should start by reflecting on your research hypothesis. You should be able to answer the following questions:
- what variables or parameters you should investigate?
- what information do you need to collect in your research to test your hypothesis?
- how much data do you need to test your hypothesis?
This information is crucial in the next step.
Step 2: Decide on research approach
Now there are two main approaches to your research approach: qualitative approach or quantitative approach.
The qualitative approach aims to characterise the relationships between the dependent and independent variables using mathematical tools to correlate the observations from your data. This usually generates quantitative data that are numerical and help you evaluate different case studies.
The quantitative approach aims to characterise the relationship between the dependent and independent variables using observations and non-mathematical data (pictures, recordings, text, transcripts, interviews, focus groups) to draw insights and conclusions.
You can also use mixed methods that combine both qualitative and quantitative approaches. With this approach to research, you can get more comprehensive answers to your research problem and you can deduct more informed conclusions.
Step 3: Select the type of research design
Wondering what are 4 types of research design? Here is the answer.
For quantitative research design, you can use experimental design, quasi-experimental design, correlational design, and descriptive design for your quantitative research. Here’s a brief overview of these research design types:
An experimental design seeks to determine a cause and effect correlation of variables that you study. Your experimental research design usually involves independent and dependent variables, and you are trying to understand how the change in the independent variable influences the dependent variables. The samples you use are often randomised. Your experiments are usually performed in a controlled environment.
A quasi-experimental design is similar to the experimental design, but it relies on pre-existing groups (non-randomised samples). Your experiments are usually performed in a natural environment.
A correlational design focuses on determining whether a correlation exists between the variables under question and how strongly these are correlated. It heavily relies on a statistical analysis of your data.
A descriptive design relies on understanding the characteristics of a single sample, such as averages and standard deviations. This type of design may not need a hypothesis as usually, you are focusing on understanding the existing data.
For qualitative research design, the most commonly used types of research design include case study, ethnography, grounded theory, and phenomenology.
Case study design aims to understand and explain the experience of a defined sample via direct observation and interaction with that sample. The focus is placed on the description of the experience.
Ethnography design aims to describe the characteristics of a selected culture. This is achieved via a selection of variables and characteristics to consider in the study and data collection via literature review, culture immersion, direct observation and interaction with subjects. The outcome is the description of culture.
Grounded theory design aims to discover the problems and challenges in society and how members of society deal with these. It involves an iterative process of “formulation, testing and re-development of propositions until a theory is developed” . The data is collected via interviews or observations. The outcome is a new theory that is supported with data.
Phenomenology design aims to describe the experiences from the individuals perspective. It aims to understand the feelings and experiences with regard to a specific phenomenon. Usually, there are no defined steps in terms of the data collections to allow space for creativity. The outcome is the understanding of the subject’s point of view and structural explanation of the specific phenomenon.
Step 4: Define your population and sampling method
Once you decided on the research design process that will provide the best set of data to test your hypothesis, it’s crucial to define the amount of data, aka. population, and sampling method.
I often find that researchers tend to generate way too much data, which makes it difficult to decide what data to include in your chapter or research article.
Therefore, it’s crucial to decide the characteristics of the population you want to study at the outset of your research to maintain focus. For example, your population can be characterised by a specific demographic or comprise a given set of technologies.
Once you understand what data you need to collect to test your hypothesis, you need to decide how this data will be sampled. This is in particular important when you’re dealing with large populations, e.g., people in a specific country, and it is impossible to get data on all of them. Instead, you will collect data based on a representative sample of that population. But let’s leave a discussion like this for our further articles.
To sample data from your population, you can use two main sampling methods.
Probabilistic sampling relies on using random methods to generate data, usually involving some sort of mathematical representation of the population you evaluate. It allows you to truly understand the correlations and characteristics of the population via thorough statistical analysis.
Deterministic sampling, aka, non-probabilistic sampling, relies on non-random selection of the sample and is usually easier to perform. However, it is subject to bias depending on how your sample is selected.
Step 5: Select data collection method
Now that you know what data you need to collect, it is important to decide how exactly you are going to collect your data. This is one of the most crucial aspects of the research design process, as you will actually decide what kind of tools you will use in your research.
At this stage, it is crucial to distinguish between the primary data and secondary data.
The former focuses on collecting new data via surveys, questionnaires, interviews, observations, mathematical modelling and so on.
The latter uses the data that has already been published in the literature. Therefore, the collection of the secondary data largely relies on literature review, database search, raw data mining and so on.
Step 6: Design your data collection process
We’re almost there! So you know what methods you’re going to use, what parameters to measure, and how to sample them. Now it’s time to determine the minimum amount of data necessary for your research.
Remember, you only need to generate a sufficient amount of data that is necessary to prove or disprove your hypothesis. Oversampling will neither give you more additional information nor improve the accuracy of your results – it will just consume more of your time during the data collection period.
To determine the minimum amount of data necessary for your research, you may use rules of thumb in your area (i.e. 3 repetitions of the same experiment), Taguchi design or fractional factorial design.
I feel that it is important to mention that you also need to develop a data management plan as early as possible in your research. This is especially true during questionnaire design or qualitative design, as you need to make sure you properly deal with the sensitive data and adhere to your funder’s data management requirements.
Importantly, when you decide on the amount of data to collect, your research design must have the following characteristics:
- Objectivity: the research methods you use in your work should allow you to objectively test your hypothesis. This means that your results should be free from bias and should not include subjective opinions. This is difficult to achieve, as we tend to promote our interests. We also make assumptions in our work. Therefore, for others to understand what you did and why you did it, it is essential to explicitly state the assumptions and approach of your work. It is important to ensure that your work could be replicated by other researchers so that they could verify your results and conclusions, and built on your research
- Repeatability: the research method you use in your work should be reliable and accurate. This means that whenever you conduct similar research under similar conditions using the same method, your results should be similar and lead to the same conclusions. This is especially true for statistical and experimental work, so your research design must include a sufficient number of observations to allow for uncertainty analysis. This is to ensure that your results are representative and not influenced by the research design. This is also important for any sort of computational or analytical research, where you develop models or correlations to represent the system or concept that you analyse. Why? Well, you need to make sure that the methods you used are valid, which means these represent the actual system accurately.
- Validity: the research method that you select needs to support you in testing and verifying your hypothesis, and subsequently answering your research questions. Your methods should help you to produce and analyse your data objectively to draw conclusions in the context of your hypothesis and research question. When selecting methods ask yourself what kind of data you’ll need to test your hypothesis.
- Generalisation: finally, it is important that you select the appropriate size of your test sample so that the analysis you do is representative and can be generalised to the entire population, not just the sample that you’re considering. For example, if you’re analysing whether sharing research via social media increases the visibility of your profile, you should include at least 100, or in ideal case 1000, researchers in your study so that you could generalise the findings.
Step 7: Develop approach to data analysis
Now that you’ve designed the data collection process, it’s time to decide how you are going to analyse your data. You can do it by using the qualitative and quantitative data analysis tools, following the research design approach you selected in Step 2.
For the qualitative data analysis, you’ll use your statistical analysis skills including descriptive statistics, inferential statistics, and hypothesis testing.
Descriptive statistics will help you to understand the characteristics of your data, especially in terms of statistical distribution, the central tendency of data and variability of data. The inferential statistics will help you understand the relationships between your data, and generalise the characteristics of the population based on your sample. Finally, using hypothesis testing you can understand whether the correlations you derived are statistically significant.
For qualitative data analysis, you may consider using thematic analysis or discourse analysis. The former focuses on the understanding the data content and its wider implications to determine key themes. The latter focuses on contextualising the data and is commonly used to understand the communication patterns.
Of course, other qualitative and quantitative tools do exist. You would usually find these via a comprehensive literature review of your research field .
Conclusions
Now you understand why research design is a crucial aspect of each research project, especially at the early stage of your PhD degree.
Having a clear path to the delivery of your research will reduce the anxiety and uncertainty associated with your work. Follow the 7-step process outlined in this article to develop your research design!
But there is one thing that I want to share with you here that helped me to successfully complete my PhD and publish my work in top journals. When you follow your initial research design process, you’ll generate new ideas and avenues – don’t be worried to pivot from your initial plan as you go through your project.
Always follow the most exciting ideas, as long as they are consistent with the main objective of your project!
What kind of research do you pursue? Qualitative or quantitative?
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Research design and methods ... Following the literature review, restate your main objectives. This brings the focus back to your own project.
A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions
A research proposal is a simply a structured, formal document that explains what you plan to research (i.e. your research topic), why it's worth researching (
A poorly-prepared proposal adversely affects the research project although by some means it managed to get approved. Conversely, a well-written
objectives, research methodology, research activities, and a time schedule in ... A sample proposal is attached here for your reference. ... By definition,.
Step 5: Write your Research Proposal. The research design is an important component of a research proposal because it plans the project's
Your research proposal is a key part of your application. It tells us about the question you want to answer through your research. It is a chance for you to
The proposal is a detailed plan or 'blueprint' for the intended study, and once it is completed, the research project should flow smoothly. Even today, many of
According to Oxford Reference, a research design is “a detailed proposal relating to a defined piece of [research] endeavour, which includes a definition of a
The research problem, research questions, purposes, sample, data collection, analysis and reporting should be tuned to each other. A research proposal not