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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.
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 ]
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.
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 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 refers to the degree to which the findings can be applied to different contexts and groups.[ 13 ]
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 ]
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.
There are no conflicts of interest.
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.
Need a helping hand?
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 .
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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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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- 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.
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.
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.
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 .
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.
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.
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.
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?
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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Organizing Your Social Sciences Research Paper: Purpose of Guide
Purpose of guide.
- Design Flaws to Avoid
- Independent and Dependent Variables
- Glossary of Research Terms
- Narrowing a Topic Idea
- Broadening a Topic Idea
- Extending the Timeliness of a Topic Idea
- Academic Writing Style
- Choosing a Title
- Making an Outline
- Paragraph Development
- Executive Summary
- The C.A.R.S. Model
- Background Information
- The Research Problem/Question
- Theoretical Framework
- Citation Tracking
- Content Alert Services
- Evaluating Sources
- Reading Research Effectively
- Primary Sources
- Secondary Sources
- Tiertiary Sources
- What Is Scholarly vs. Popular?
- Qualitative Methods
- Quantitative Methods
- Using Non-Textual Elements
- Limitations of the Study
- Common Grammar Mistakes
- Writing Concisely
- Avoiding Plagiarism
- Footnotes or Endnotes?
- Further Readings
- Annotated Bibliography
- Dealing with Nervousness
- Using Visual Aids
- Grading Someone Else's Paper
- Types of Structured Group Activities
- Group Project Survival Skills
- Multiple Book Review Essay
- Reviewing Collected Essays
- Writing a Case Study
- About Informed Consent
- Writing Field Notes
- Writing a Policy Memo
- Writing a Research Proposal
This guide is intended to help students organize and write a quality research paper for classes taught in the social and behavioral sciences. Also included are recommendations concerning how to successfully manage and complete specific course assignments. Note that, if you have any questions about a writing assignment, you should always seek advice from your professor before you begin. Requirements set forth by your professor will always supersede instructions provided in these general guidelines.
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Research Proposal: Definition, Purpose, & Writing Steps
Few students fully get the meaning and the importance of a research proposal. If you have a good research proposal, it means that you are going to carry out adequate research. A low-quality research proposal may be the reason your research will never start.
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The main purpose of a research proposal is to convince the reader of your project’s value . You will have to prove that you have a plan for your work and that your project will be successful. Your reader has to be sure that it is not another useless piece of writing, but a profound research work that will be extremely important for science.
Want to learn more about the reasons why it is important to have a research plan? Continue reading this article by Custom-writing.org experts!
- 🔤 Definition
- ❗ Purpose & Importance
- 👣 Writing Steps
🔤 research proposal: definition.
A research proposal is a document that proposes a particular research project, usually in academia or sciences, intending to get funding from an institution. A typical research proposal addresses a range of points:
- A research question(s) that the proposed research seeks to answer
- The data & methods that will be used to answer the questions
- The time and financial costs for the research
- The prior research in the field
- Potential benefits for the sponsoring institution
Research proposals are usually required when one plans to write a thesis, dissertation, or research paper. The format is similar to that of a research paper, with an introduction, a literature review, a methods section, and a conclusion.
❗ Research Proposal: Purpose & Importance
The primary goal of any research proposal is to convince a sponsoring institution that a particular research project is worthwhile. The document usually aims to cover the aspects below.
👣 Making a Research Plan in 10 Steps
- Writing a Research Proposal (USC Library Guides)
- Writing a research proposal – Research & Learning Online
- How to write a research proposal? – NCBI
- How to Write a Research Proposal – University of Birmingham
- How To Write an Academic Research Proposal
- How to write a research proposal (Yale College)
- How to write a research proposal for a strong PhD application (University of Sydney)
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Thanks a lot dear!! Many information gained
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Thanks it’s so much easier and helpful who are work first time in research proposal like me It’s interesting but I can’t decided what topic I researching for my collage project or which topic is better 🙂 so I need a guide line or instructions for choosing a good topic
thank you for our explanation about research proposal but i want to know the aims or purpose of research proposal
This is informative and inspiring paper for me👏👏
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very good concept on research proposal. thank you
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A very important concept. Thanks
hi…may you please offer free definitions and relevance of a research proposal.
You are welcome to use our blog articles to find out whatever information you need.
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How to Write a Research Proposal
Table of Contents
In academia, especially in social and behavioral sciences, writing a research proposal is an essential first step while planning a new research project. A research proposal is an initial pitch, or theoretical framework that serves to introduce the topic and anticipated results of a project, provide an overview of the methods to be used, and convince the reader that the proposed research can be conducted successfully. It is very essential to know how to write a research proposal, whether you are a student trying to fulfill course requirements or a researcher looking for funding for scholarly research. But writing a well-structured proposal is easier said than done.
To make things simpler for you, In this article, I explained the fundamentals of a research proposal, its structure, the steps involved in writing a research proposal, and common mistakes to avoid. Continue reading to gain a thorough understanding of the concept and purpose of a research proposal. This blog will also enable you to write the research proposal quickly, reducing the likelihood of rejection.
What is a Research Proposal?
In simpler terms, A research proposal is a document written to explain and justify your chosen research topic and the necessity to carry out that particular research by addressing the research problem. Likewise, a good research proposal should carry the proposed research's results and benefits, backed by convincing evidence.
Always keep your audience in mind while writing your research proposal. Your audience expects a concise summary and a detailed research methodology from you in the research proposal.
To begin, you must understand the purpose of a research proposal in order to effectively write a research proposal and also to receive swift approvals.
What is the purpose or importance of a research proposal?
A research proposal's purpose is to provide a detailed outline of the process that will be used to answer a specific research problem. Whereas the goal of the research proposal varies from person to person. In some cases, it may be to secure funding, while in others, it may be to obtain a meager approval from the committee or the supervisor to proceed with the research project. Regardless of your research proposal's end goal, you are supposed to write a research proposal that fulfills its intended purpose of presenting the best plan for your research.
While writing a research proposal, you should demonstrate how and why your proposed research is crucial for the domain, especially if it is social and behavioral sciences. It would help if you showed how your work is necessary by addressing some key points like:
- Bridging the gaps in the existing domain of research.
- Adding new and fresh perspectives to the existing understanding of the topic.
- Undervalued data in the current stats of the domain.
Furthermore, your research proposal must demonstrate that you, as an author, are capable of conducting the research and that the results will significantly contribute to the field of knowledge. To do so, include and explain your academic background and significance along with your previous accolades to demonstrate that you and your idea have academic merit.
What is the ideal length of a research proposal?
There are no hard and fast rules about how long a research proposal should be, and it varies dramatically from different institutions and publishers. However, as a standard domain practice, a research proposal is generally between 3000- 4000 words. A majority of globally reputed institutions follow the 3000- 3500 word limit.
Since the research proposal is written well before the research is conducted, you need to outline all the necessary elements your research will entail and accomplish. Once completed, your research proposal must resemble a concise version of a thesis or dissertation without results and a discussion section.
Structure of a research proposal
When you recognize a gap in the existing books of knowledge, you will address it by developing a research problem. A research problem is a question that researchers want to answer. It is the starting point for any research project, and it can be broad or narrow, depending on your objectives. Once you have a problem, it is followed by articulating a research question. After that, you can embark on the process of writing a research proposal.
Whether your goal is to secure funding or just approval, nevertheless, your research proposal needs to follow the basic outline of a research paper, containing all the necessary sections. Therefore, the structure of a research proposal closely resembles and follows a thesis or dissertation or any research paper. It should contain the following sections:
As is well known, the first thing that catches the reader's attention is a catchy title. Therefore, you should try to come up with a catchy yet informative title for your research proposal. Additionally, it should be concise and clear to reflect enough information about your research question.
To create a good research proposal, try writing the title to induce interest and information in your readers. Pro-Tip: Avoid using phrases such as “An investigation of …” or “A review of …” etc. . These have been overused for ages and may reflect your research title as a regular entry. On the other hand, concise and well-defined titles are always something readers like and stand higher chances for a proposal approval.
Write your abstract in a brief yet very informative way. It should summarize the research you intend to conduct. Put an emphasis on the research question, research hypothesis , research design and methods, and the key findings of your proposed research.
If you wish to create a detailed proposal, try including a table of contents. It will help readers navigate easily and catch a glance at your entire proposal writing. Check out this guide if you want to learn more about how to write a research abstract for your scholarly research.
All papers need a striking introduction to set the context of the research question. While framing your research proposal, ensure that the introduction provides rich background and relevant information about the research question.
Your entire research proposal hinges upon your research question. Thus, fit should come out clearly in the intro. Provide a general introduction without clear explanations, and it might render your research proposal insignificant.
Start your research proposal with the research problem, engage your audience with elements that relate to the problem, and then shed some light on the research question. Then, proceed with your study's evidence-based justification, and you'll find that the audience is sticking with your proposal narrative.
While writing your research proposal, ensure that you have covered the following:
- Purpose of your study.
- Background information and significance of your study.
- Introduction to the question, followed by an introduction to the paper.
- Brief mention of the critical issues that you will focus on.
- Declaration of independent and dependent variables of the research hypothesis. (You can learn more about the variables of the research hypothesis here .)
4. Literature Review
Writing a literature review is an important part of the research process. It provides the researcher with a summary of previous studies that have been conducted on a subject, and it helps the researcher determine what areas might need additional investigation in the existing research. Guidelines for the literature review vary for different institutions.
To effectively conduct and write a literature review check this guide . You can also use tools like SciSpace Copilot , our AI research assistant that makes reading academic papers a much easier task. You can use it to get simple explanations for complex text, maths, or tables. Copilot can be particularly helpful when you’re sifting through papers as you can quickly understand the abstract, get some context around the study, and identify if the paper is relevant to your project or not.
The literature review can either be kept as a separate section or incorporated into the introduction section. A separate section is always favorable and vital in gaining the research proposal approval. Additionally, a separate section for a literature review offers in-depth background data and demonstrates the relevance of your research question by emphasizing the gaps that have remained since the previous study.
Your research proposal’s literature review must contain and serve the following:
- To provide a reference of the studies and the researchers who have previously worked in the same domain.
- To provide the build path of your research question.
- To furnish a critical examination of the previous research works.
- To present the research issues about the current investigation.
- To convince the audience about the importance of your research in the relevant domain.
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5. Research Methodology
Research design and methods is the section where you explain how you will be conducting the proposed research. Ensure that you provide and include a sufficient explanation for the chosen methods. Additionally, include some points explaining how your chosen methods will help you get the desired or expected results.
Provide ample information to the readers about your research procedures so that they can easily comprehend the methodology and its expected results. Through your research methodology, you can easily show your audience whether the results you are promising can be achieved or not.
Most importantly, make sure the methodology you choose—whether qualitative or quantitative—is the best fit for your research. You should also be able to justify your choice.
Additionally, you should properly explain both the quantitative and qualitative components of your research if they are both used. For a qualitative approach, you must offer more elaborate and in-depth theoretical-based evidence. On the other hand, for the quantitative approach, you must describe the survey or lab setup, sample size, tools, and data collection methods.
Make sure you have plenty of explanations for the research methodology to support how you approached the research problem.
6. Expected Research Results
The expected research results section is where the researcher states what they expect to find in their research. The purpose of this section is to provide a summary of the study's goals, as well as give an overview of what the researcher expects will be found out. These results must orient the reader in sync with the methodology section and provide the answers to the research questions.
The limitations section of an academic research paper is a section in which the writers of the paper discuss the weaknesses of their study. They do this by identifying problems with their methods, design, and implementation. This section should also discuss any other factors that may have affected the results or accuracy of the study. This section allows readers to understand how much confidence they can place in the findings, and how applicable they are to other contexts.
Furthermore, it will also showcase your honesty and complete understanding of the topic. Your research proposal’s limitations can include:
- Reasons for the chosen sample size.
- Justifications for the availability of resources at hand.
- Any unexpected error that might occur in the course of research as well.
8. Reference and Bibliography
If you don’t want your efforts to be tagged as plagiarized, ensure that you include the reference section at the end of the research proposal and follow the appropriate citation guidelines while citing different scholarly sources and various other researchers’ work.
For references, use both the in-text and footnote citations. List all the literature you have used to gather the information. However, in the bibliography, apart from including the references you have cited, you should include the sources that you didn't cite.
Reasons why research proposals get rejected
Research proposals often get rejected due to the smallest of mistakes. To keep the chances of getting your research proposal rejection at bay or a minimum, you should be aware of what grounds committees or supervisors often decide on rejection.
Follow through to understand the common reasons why research papers get rejected:
- The proposal stated a flawed hypothesis.
- The readers or the audience don't get convinced that the expected results will be anything new or unique.
- The research methodology lacks the details and may appear unrealistic.
- The research proposal lacks coherence in the problem statement, methodology, and results.
- Inadequate literature review.
- Inaccurate interpretation of expected results from the methodology.
- Plagiarized or copied sections of the research proposal.
Common mistakes to avoid
You must stay aware of the research proposal guidelines and best writing manners. To maximize the approval chances of your research proposal, you should try to avoid some common pitfalls like:
- Making it verbose
Try explaining the various sections of the research proposal economically. Ideally, you should strive to keep your writing as a concise, brief, and to the point as possible. The more concisely you explain the purpose and goal of your research proposal, the better.
- Focusing on minor issues than tackling the core
While writing the research proposal, you may feel every issue is important, and you should provide an explanatory note for that. However, stay wiser while selecting the importance of issues. Avoid falling into the trap of trivial issues, as it may distract your readers from the core issues.
- Failure to put a strong research argument
The easiest way your readers can undermine your research proposal is by stating it is far more subjective and sounds unrealistic. A potent research argument describing the gaps in the current field, its importance, significance, and contributions to your research is the foremost requirement of a good research proposal.
Remember, even though you are proposing the objective, academic way, the goal is to persuade the audience to provide you with the required research approval.
- Not citing correctly
Understand that when you are going for some research, its outcome will contribute to the existing pool of knowledge. Therefore, always cite some landmark works of your chosen research domain and connect your proposed work with it.
Providing such intricate details will establish your research's importance, relevance, and familiarity with the domain knowledge.
Before You Go,
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- Nov 17, 2022
Be it science and technology , art and culture, media studies, geography , mathematics , and other subjects, research has always been the route towards finding the unknown. In the present gloomy circumstances when Coronavirus has shattered the world, a vast amount of research is being carried out to find vaccines for its treatment. In this blog, we will understand what are the various types of research design and their related components.
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Also Read: How to Make a Career in Research?
This Blog Includes:
What is a research design, elements of research design , characteristics of research design, quantitative research design, qualitative research design, quantitative vs. qualitative research design, fixed vs. flexible research design, descriptive research design, experimental research design, correlational research design, diagnostic research design, explanatory research design, cohort study, cross-sectional study, longitudinal study, cross-sequential study, types of research design pdf, research design ppt, benefits of research .
By the term ‘ research ‘, we can understand that it’s a collection of data that includes critical information by taking research methodologies into consideration. In other words, it is a compilation of information or data explored by setting a hypothesis and consequently coming up with substantive findings in an organised way. Research can be done on an academic as well as on a scientific basis as well. Let’s first understand what a research design actually means.
A Research Design is simply a structural framework of various research methods as well as techniques that are utilised by a researcher.
The research design helps a researcher to pursue their journey into the unknown but with a systematic approach by their side. The way an engineer or architect frames a design for a structure, likewise the researcher picks the design from various approaches in order to check which type of research to be carried out.
Here are the most important elements of a research design-
The essential elements are:
- The method applied for analyzing collected details
- Type of research methodology
- Accurate purpose statement
- Probable objections for research
- Techniques to be implemented for collecting and analyzing research
- Measurement of analysis
- Settings for the research study
Must Read: What does a Research Assistant do?
2 Major Types of Research Design
Keeping its dynamics into consideration, the research design is categorised into two different perspectives, i.e. Quantitative Research Design and Qualitative Research Design . Further, there are four main characteristics of research design which include Reliability, Neutrality, Validity as well as Generalization. Further, a researcher should have a clear understanding of how their project can be implemented in the research design. Let’s explore what Quantitative and Qualitative Research Designs mean:
In Quantitative Research Design, a researcher examines the various variables while including numbers as well as statistics in a project to analyze its findings. The use of graphics, figures, pie charts is the main form of data collection measurement and meta-analysis (it is information about the data by the data).
This type of research is quite contrary to quantitative research design. It is explanatory in nature and always seeks answers to “What’s” and “How’s”. It mainly focuses on why a specific theory exists and what would be the respondent’s answer to it. This allows a researcher to draw a conclusion with proper findings. Case studies are mainly used in Qualitative Research Design in order to understand various social complexities.
Know All About Business Research !
Following is the difference between Quantitative vs. Qualitative Research Design
A contrast between fixed and flexible research design can also be drawn. Quantitative (fixed design) and qualitative (flexible design) data gathering are frequently associated with these two study design categories. The research design is pre-determined and understood with a set study design even before you begin collecting data. Flexible designs, on the other hand, provide for more flexibility in data collection — for example, you don’t provide fixed answer alternatives, so respondents must put in their own responses.
The 5 Types of Research Designs
Now that we know the broadly classified types of research, Quantitative and Qualitative Research can be divided into the following 4 major types of Research Designs:
These 5 types of Research Designs are considered the closest and exact to true experiments and are preferred in terms of accuracy, relevance as well as quality.
In Descriptive Research Design, the scholar explains/describes the situation or case in depth in their research materials. This type of research design is purely on a theoretical basis where the individual collects data, analyses, prepares and then presents it in an understandable manner. It is the most generalised form of research design. To explore one or more variables, a descriptive design might employ a wide range of research approaches. Unlike in experimental research, the researcher does not control or change any of the variables in a descriptive research design; instead, he or she just observes and measures them. In other words, while qualitative research may also be utilised for descriptive reasons, a descriptive method of research design is typically regarded as a sort of quantitative research. To guarantee that the results are legitimate and dependable, the study design should be properly constructed. Here are some examples for the descriptive design of research type:
- How has the Delhi housing market changed over the past 20 years?
- Do customers of company A prefer product C or product D?
- What are the main genetic, behavioural and morphological differences between Indian wildcows and hybrid-cows?
- How prevalent is disease 1 in population Z?
Experimental research is a type of research design in which the study is carried out utilising a scientific approach and two sets of variables. The first set serves as a constant against which the variations in the second set are measured. Experimentation is used in quantitative research methodologies, for example. If you lack sufficient evidence to back your conclusions, you must first establish the facts. Experimental research collects data to assist you in making better judgments. Experimentation is used in any research undertaken under scientifically appropriate settings. The effectiveness of experimental investigations is dependent on researchers verifying that a variable change is due only to modification of the constant variable. The study should identify a noticeable cause and effect. The traditional definition of experimental design is “the strategies employed to collect data in experimental investigations.” There are three types of experimental designs:
- Pre-experimental research design
- True experimental research design
- Quasi-experimental research design
A correlational research design looks into correlations between variables without allowing the researcher to control or manipulate any of them. Correlational studies reveal the magnitude and/or direction of a link between two (or more) variables. Correlational studies or correlational study design might have either a positive, negative or zero.
Correlational research design is great for swiftly collecting data from natural settings. This allows you to apply your results to real-world circumstances in an externally legitimate manner. Correlational studies research is a viable choice in a few scenarios like:
- To investigate non-causal relationships
- To explore causal relationships between variables
- To test new measurement tools
Recommended Read: Scope of Operation Research
Diagnostic research design is a type of research design that tries to investigate the underlying cause of a certain condition or phenomena. It can assist you in learning more about the elements that contribute to certain difficulties or challenges that your clients may be experiencing. This design typically consists of three research stages, which are as follows:
- Inception of the issue
- Diagnosis of the issue
- Solution for the issue
Explanatory research is a method established to explore phenomena that have not before been researched or adequately explained. Its primary goal is to notify us about where we may get a modest bit of information. With this strategy, the researcher obtains a broad notion and use research as a tool to direct them more quickly to concerns that may be addressed in the future. Its purpose is to discover the why and what of a subject under investigation. In short, it is a type of research design that is responsible for finding the why of the events through the establishment of cause-effect relationships. The most popular methods of explanatory research are:
- Literature research
- In-depth interview
- Focus groups
- Case studies
Research Design Types by Grouping
Another classification of study design types is based on how participants are categorized. In most situations, grouping is determined by the research premise and the method used to sample individuals. There is generally at least one experimental and one control group in a typical study based on experimental research design. In medical research, for example, one group can be given therapy while the other receives none. You get my drift. We can differentiate four types of study designs based on participant grouping:
A cohort study is a sort of longitudinal research that takes a cross-section of a cohort (a group of people who have a common trait) at predetermined time intervals. It’s a form of panel research in which all of the people in the group have something in common.
In social science, medical research, and biology, a cross-sectional study is prevalent. This study approach examines data from a population or a representative sample of the population at a specific point in time.
A longitudinal study is a type of study in which the same variables are observed repeatedly over a short or long period of time. It’s usually observational research, although it can also take the form of a long-term randomized experiment.
Cross-sequential research design combines longitudinal and cross-sectional research methods, with the goal of compensating for some of the flaws inherent in both.
Since we are dealing with the types of research design, it is imperative to understand how beneficial the practise of doing research is and some of its major advantages are:
- Research helps in getting a deeper understanding of the subject.
- You will learn about its varied aspects as well as its different sources like primary and secondary.
- It helps to resolve the complex problems in any field through critical analysis and measurement of unsolved problems.
- You will also get to know about how a hypothesis is created by weighing preserved assumptions.
Also Read: Research Institutes in India
Certainly, research is the fuel that can potentially drive the solutions to redress all the world’s problems. In order to help to gain a deeper understanding of any subject matter, knowing types of research design plays a critical role in carrying out your thesis. If you are aspiring to pursue your career in the field of research and aim to pursue a PhD , call us at 1800572000 for a free 30-minute career counselling session with our Leverage Edu experts and we will help you find a suitable program and university that fit your aspirations, interests and preferences and can guide you towards a fulfilling career in this domain.
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Organizing Your Social Sciences Research Paper
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Before beginning your paper, you need to decide how you plan to design the study .
The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!
De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.
General Structure and Writing Style
The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.
With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.
The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :
- Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
- Review and synthesize previously published literature associated with the research problem,
- Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
- Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
- Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.
The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.
NOTE : Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.
Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.
Action Research Design
Definition and Purpose
The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.
What do these studies tell you ?
- This is a collaborative and adaptive research design that lends itself to use in work or community situations.
- Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
- When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
- Action research studies often have direct and obvious relevance to improving practice and advocating for change.
- There are no hidden controls or preemption of direction by the researcher.
What these studies don't tell you ?
- It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
- Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
- Personal over-involvement of the researcher may bias research results.
- The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
- Advocating for change usually requires buy-in from study participants.
Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA: Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.
Case Study Design
A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.
- Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
- A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
- Design can extend experience or add strength to what is already known through previous research.
- Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
- The design can provide detailed descriptions of specific and rare cases.
- A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
- Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
- Design does not facilitate assessment of cause and effect relationships.
- Vital information may be missing, making the case hard to interpret.
- The case may not be representative or typical of the larger problem being investigated.
- If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.
Case Studies. [email protected] Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.
Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.
Conditions necessary for determining causality:
- Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
- Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
- Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
- Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
- Replication is possible.
- There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
- Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
- Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
- If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the actual effect.
Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.
Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."
- Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
- Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
- The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
- Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
- Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
- Either original data or secondary data can be used in this design.
- In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
- Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
- Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.
Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.
Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.
- Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
- Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
- Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
- Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
- Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
- Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
- Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
- Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
- Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
- Studies cannot be utilized to establish cause and effect relationships.
- This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
- There is no follow up to the findings.
Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.
Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.
- The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
- Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
- If the limitations are understood, they can be a useful tool in developing a more focused study.
- Descriptive studies can yield rich data that lead to important recommendations in practice.
- Appoach collects a large amount of data for detailed analysis.
- The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
- Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
- The descriptive function of research is heavily dependent on instrumentation for measurement and observation.
Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.
A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.
- Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
- Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
- Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
- Approach provides the highest level of evidence for single studies.
- The design is artificial, and results may not generalize well to the real world.
- The artificial settings of experiments may alter the behaviors or responses of participants.
- Experimental designs can be costly if special equipment or facilities are needed.
- Some research problems cannot be studied using an experiment because of ethical or technical reasons.
- Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.
Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.
An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.
The goals of exploratory research are intended to produce the following possible insights:
- Familiarity with basic details, settings, and concerns.
- Well grounded picture of the situation being developed.
- Generation of new ideas and assumptions.
- Development of tentative theories or hypotheses.
- Determination about whether a study is feasible in the future.
- Issues get refined for more systematic investigation and formulation of new research questions.
- Direction for future research and techniques get developed.
- Design is a useful approach for gaining background information on a particular topic.
- Exploratory research is flexible and can address research questions of all types (what, why, how).
- Provides an opportunity to define new terms and clarify existing concepts.
- Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
- In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
- Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
- The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
- The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
- Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.
Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.
Field Research Design
Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .
- Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
- The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
- Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
- Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
- Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.
What these studies don't tell you
- A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
- Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
- The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
- Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field [i.e., the act of triangulating the data].
- Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
- The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.
The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.
- The historical research design is unobtrusive; the act of research does not affect the results of the study.
- The historical approach is well suited for trend analysis.
- Historical records can add important contextual background required to more fully understand and interpret a research problem.
- There is often no possibility of researcher-subject interaction that could affect the findings.
- Historical sources can be used over and over to study different research problems or to replicate a previous study.
- The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
- Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
- Interpreting historical sources can be very time consuming.
- The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
- Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
- Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
- It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.
Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58; Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.
A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.
- Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
- Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
- The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
- Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
- The data collection method may change over time.
- Maintaining the integrity of the original sample can be difficult over an extended period of time.
- It can be difficult to show more than one variable at a time.
- This design often needs qualitative research data to explain fluctuations in the results.
- A longitudinal research design assumes present trends will continue unchanged.
- It can take a long period of time to gather results.
- There is a need to have a large sample size and accurate sampling to reach representativness.
Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.
Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:
- Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
- A well-reasoned and well-documented justification for identification and selection of the studies;
- Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
- Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
- Justification of the techniques used to evaluate the studies.
- Can be an effective strategy for determining gaps in the literature.
- Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
- Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
- Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
- Can be used to generate new hypotheses or highlight research problems for future studies.
- Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
- A large sample size can yield reliable, but not necessarily valid, results.
- A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
- Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.
Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.
- Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
- Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
- A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
- The strengths of one method can be used to overcome the inherent weaknesses of another method.
- Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
- May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
- Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
- A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
- Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
- Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
- Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
- Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
- Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.
Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .
This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.
- Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
- The researcher is able to collect in-depth information about a particular behavior.
- Can reveal interrelationships among multifaceted dimensions of group interactions.
- You can generalize your results to real life situations.
- Observational research is useful for discovering what variables may be important before applying other methods like experiments.
- Observation research designs account for the complexity of group behaviors.
- Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
- In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
- There can be problems with bias as the researcher may only "see what they want to see."
- There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
- Sources or subjects may not all be equally credible.
- Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.
Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.
Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:
- Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
- Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
- Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
- Can provide a basis for applying ethical decision-making to practice.
- Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
- Brings clarity to general guiding practices and principles of an individual or group.
- Philosophy informs methodology.
- Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
- Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
- Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
- Limited application to specific research problems [answering the "So What?" question in social science research].
- Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
- While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
- There are limitations in the use of metaphor as a vehicle of philosophical analysis.
- There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.
Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.
- The researcher has a limitless option when it comes to sample size and the sampling schedule.
- Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
- This is a useful design for exploratory studies.
- There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
- Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
- The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
- The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
- Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.
Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.
- A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
- The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
- They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
- Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
- The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
- Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
- The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
- Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
- Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
- The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
- The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.
Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods . David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research." Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102;Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.
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Introduction. It is also sometimes termed as 'need for study' or 'abstract'. · Review of literature. It refers to all sources of scientific evidence pertaining
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
A research proposal aims to show why your project is worthwhile. It should explain the context, objectives, and methods of your research.
The research design is a strategy for answering your research questions. It determines how you will collect and analyze your data.
In addition to providing a rationale, a proposal describes detailed methodology for conducting the research consistent with requirements of the
A research proposal is a document that proposes a particular research project, usually in academia or sciences, intending to get funding
A research proposal is an initial pitch, or theoretical framework that serves to introduce the topic and anticipated results of a project
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The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical