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Online Guide to Writing and Research
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- Online Guide to Writing
The Research Assignment Introduction
When tasked with writing a research paper, you are able to “dig in” to a topic, idea, theme, or question in greater detail. In your academic career, you will be assigned several assignments that require you to “research” something and then write about it. Sometimes you can choose a topic and sometimes a topic is assigned to you.
Either way, look at this assignment as an opportunity to learn more about something and to add your voice to the discourse community about said topic. Your professor is assigning you the task to give you a chance to learn more about something and then share that newfound knowledge with the professor and your academic peers. In this way, you contribute meaningfully to the existing scholarship in that subject area. You are then creating a research space for yourself and for other researchers who may follow you.
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Table of Contents: Online Guide to Writing
Chapter 1: College Writing
How Does College Writing Differ from Workplace Writing?
What Is College Writing?
Why So Much Emphasis on Writing?
Chapter 2: The Writing Process
Doing Exploratory Research
Getting from Notes to Your Draft
Introduction
Prewriting - Techniques to Get Started - Mining Your Intuition
Prewriting: Targeting Your Audience
Prewriting: Techniques to Get Started
Prewriting: Understanding Your Assignment
Rewriting: Being Your Own Critic
Rewriting: Creating a Revision Strategy
Rewriting: Getting Feedback
Rewriting: The Final Draft
Techniques to Get Started - Outlining
Techniques to Get Started - Using Systematic Techniques
Thesis Statement and Controlling Idea
Writing: Getting from Notes to Your Draft - Freewriting
Writing: Getting from Notes to Your Draft - Summarizing Your Ideas
Writing: Outlining What You Will Write
Chapter 3: Thinking Strategies
A Word About Style, Voice, and Tone
A Word About Style, Voice, and Tone: Style Through Vocabulary and Diction
Critical Strategies and Writing
Critical Strategies and Writing: Analysis
Critical Strategies and Writing: Evaluation
Critical Strategies and Writing: Persuasion
Critical Strategies and Writing: Synthesis
Developing a Paper Using Strategies
Kinds of Assignments You Will Write
Patterns for Presenting Information
Patterns for Presenting Information: Critiques
Patterns for Presenting Information: Discussing Raw Data
Patterns for Presenting Information: General-to-Specific Pattern
Patterns for Presenting Information: Problem-Cause-Solution Pattern
Patterns for Presenting Information: Specific-to-General Pattern
Patterns for Presenting Information: Summaries and Abstracts
Supporting with Research and Examples
Writing Essay Examinations
Writing Essay Examinations: Make Your Answer Relevant and Complete
Writing Essay Examinations: Organize Thinking Before Writing
Writing Essay Examinations: Read and Understand the Question
Chapter 4: The Research Process
Planning and Writing a Research Paper
Planning and Writing a Research Paper: Ask a Research Question
Planning and Writing a Research Paper: Cite Sources
Planning and Writing a Research Paper: Collect Evidence
Planning and Writing a Research Paper: Decide Your Point of View, or Role, for Your Research
Planning and Writing a Research Paper: Draw Conclusions
Planning and Writing a Research Paper: Find a Topic and Get an Overview
Planning and Writing a Research Paper: Manage Your Resources
Planning and Writing a Research Paper: Outline
Planning and Writing a Research Paper: Survey the Literature
Planning and Writing a Research Paper: Work Your Sources into Your Research Writing
Research Resources: Where Are Research Resources Found? - Human Resources
Research Resources: What Are Research Resources?
Research Resources: Where Are Research Resources Found?
Research Resources: Where Are Research Resources Found? - Electronic Resources
Research Resources: Where Are Research Resources Found? - Print Resources
Structuring the Research Paper: Formal Research Structure
Structuring the Research Paper: Informal Research Structure
The Nature of Research
The Research Assignment: How Should Research Sources Be Evaluated?
The Research Assignment: When Is Research Needed?
The Research Assignment: Why Perform Research?
Chapter 5: Academic Integrity
Academic Integrity
Giving Credit to Sources
Giving Credit to Sources: Copyright Laws
Giving Credit to Sources: Documentation
Giving Credit to Sources: Style Guides
Integrating Sources
Practicing Academic Integrity
Practicing Academic Integrity: Keeping Accurate Records
Practicing Academic Integrity: Managing Source Material
Practicing Academic Integrity: Managing Source Material - Paraphrasing Your Source
Practicing Academic Integrity: Managing Source Material - Quoting Your Source
Practicing Academic Integrity: Managing Source Material - Summarizing Your Sources
Types of Documentation
Types of Documentation: Bibliographies and Source Lists
Types of Documentation: Citing World Wide Web Sources
Types of Documentation: In-Text or Parenthetical Citations
Types of Documentation: In-Text or Parenthetical Citations - APA Style
Types of Documentation: In-Text or Parenthetical Citations - CSE/CBE Style
Types of Documentation: In-Text or Parenthetical Citations - Chicago Style
Types of Documentation: In-Text or Parenthetical Citations - MLA Style
Types of Documentation: Note Citations
Chapter 6: Using Library Resources
Finding Library Resources
Chapter 7: Assessing Your Writing
How Is Writing Graded?
How Is Writing Graded?: A General Assessment Tool
The Draft Stage
The Draft Stage: The First Draft
The Draft Stage: The Revision Process and the Final Draft
The Draft Stage: Using Feedback
The Research Stage
Using Assessment to Improve Your Writing
Chapter 8: Other Frequently Assigned Papers
Reviews and Reaction Papers: Article and Book Reviews
Reviews and Reaction Papers: Reaction Papers
Writing Arguments
Writing Arguments: Adapting the Argument Structure
Writing Arguments: Purposes of Argument
Writing Arguments: References to Consult for Writing Arguments
Writing Arguments: Steps to Writing an Argument - Anticipate Active Opposition
Writing Arguments: Steps to Writing an Argument - Determine Your Organization
Writing Arguments: Steps to Writing an Argument - Develop Your Argument
Writing Arguments: Steps to Writing an Argument - Introduce Your Argument
Writing Arguments: Steps to Writing an Argument - State Your Thesis or Proposition
Writing Arguments: Steps to Writing an Argument - Write Your Conclusion
Writing Arguments: Types of Argument
Appendix A: Books to Help Improve Your Writing
Dictionaries
General Style Manuals
Researching on the Internet
Special Style Manuals
Writing Handbooks
Appendix B: Collaborative Writing and Peer Reviewing
Collaborative Writing: Assignments to Accompany the Group Project
Collaborative Writing: Informal Progress Report
Collaborative Writing: Issues to Resolve
Collaborative Writing: Methodology
Collaborative Writing: Peer Evaluation
Collaborative Writing: Tasks of Collaborative Writing Group Members
Collaborative Writing: Writing Plan
General Introduction
Peer Reviewing
Appendix C: Developing an Improvement Plan
Working with Your Instructor’s Comments and Grades
Appendix D: Writing Plan and Project Schedule
Devising a Writing Project Plan and Schedule
Reviewing Your Plan with Others
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Understanding Research Assignments
Before you begin researching and writing, you should spend some time understanding your assignment and preparing your process and workflows. To make the most productive use of your time, you'll need to know what you're trying to accomplish and have a consistent process for gathering information, reading, and note-taking.
1) About Research Assignments
2) avoiding plagiarism, 3) organizing your readings, about research assignments.
Most of your courses will require you to complete a research assignment of one kind or another. In general, the goal of a research assignment is to get you to gather information about a certain topic, analyze that information, and report what you’ve learned as part of a class presentation or research paper/essay.
Types of Research Assignments
You can find useful information about the different types of research and writing assignments at the Online Writing Lab .
Important Things to Note About Your Assignment
Relationship to other assignments : Some professors will design their assignments to flow together. You may find that each assignment requires you to do a little bit more work towards writing a big final paper.
Choice of topic : You may be given a list of possible research topics, or you may be asked to choose a topic of interest to you. In either case, it’s a good idea to chat with your prof and do some preliminary research before deciding.
Number and Type of Sources : Often, professors will ask that you use a minimum number of sources in your paper. Information sources can be almost anything, but you may be required to use only, or mostly, academic/peer-reviewed sources.
Citation/Referencing Style : There are many different styles for referencing your sources. The most commonly used styles are APA, MLA, Chicago, and CSE. Make sure you know which you are expected to use, and take a moment to learn the basics of the style.
Length : You will usually be asked to write a paper of specified length. Be sure to start early and give yourself enough time to do the appropriate amount of research and writing.
Library Access
Completing your assignments will require access to the library’s collection. These are specialized resources you won’t find available freely on the Internet. You can access the library’s online collections (databases) through our website. If you are off-campus, you’ll be required to authenticate with your WebAdvisor username and password.
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Avoiding Plagiarism
The following definition of plagiarism can be found in the University of Winnipeg Academic Misconduct Policy :
“Plagiarism is a form of academic dishonesty in which students present published or unpublished work (written, digital, or other) of another person or persons, or one’s own prior work, in its entirety or in part, as their own original work.”
Every student is expected to produce work that follows the rules of academic integrity, so avoiding plagiarism is a fundamental skill in university. To be clear, you will generally be expected to use other people’s ideas to support the points in your paper, but the source of every idea that isn’t your own needs to be cited in a suitable format.
There are two ways that plagiarism can happen: intentionally and unintentionally. We’ll talk about each here.
Intentional Plagiarism
With the abundance of information available online, it’s incredibly easy to take credit for something you didn’t write, if that’s your intention. However, simply copying information from a website or blog and pasting it into your paper without crediting the source is considered plagiarism. Add this to the act of getting someone (or paying them) to write your paper for you, which is clearly unethical, and you have an idea of how intentional plagiarism happens.
As easy as it is, though, it’s also very easy to detect. If you plagiarize something, your professor only needs to do a couple of simple Google searches or use a plagiarism detection software to figure it out. Plus, your professors often craft their assignments to see how you develop as a researcher and writer during the course. If you are not producing original work, you won’t be effectively demonstrating your development and your grades may suffer, even if you don’t get caught.
Unintentional Plagiarism
Plagiarism can also happen by accident. This usually results from sloppy note-taking or by writing your paper in a rush. Even if you accidentally use another person’s idea without credit, you are still plagiarizing them. Also, most students don’t realize it’s possible to plagiarize yourself, by using your own published ideas without citation.
Basically, any idea that comes from a source (books, articles, websites, videos, previous papers, etc.) needs to be cited.
There can be serious penalties for plagiarism (again, see the Academic Misconduct Policy ). It isn’t worth it to try, and taking the time to properly cite and reference your sources isn’t too difficult once you get in the habit.
Tips for Avoiding Plagiarism
- Don’t procrastinate.
- Create a reference for all your sources, in the format outlined by your prof.
- Take detailed notes as your read each source, noting the page numbers for each idea.
- Paraphrase major points and indicate if an idea is a direct quote.
- In your paper, properly cite all the ideas from your sources.
- Create a bibliography or works cited, including references for all your sources.
Organizing Your Readings
Writing a research paper can be difficult and frustrating if you don’t keep your sources organized. Here’s some advice to keep your readings, notes, and bibliographies organized so you don’t run into trouble later.
- Create a separate folder on your computer for each research project you’re working on.
- Place all your full-text articles (PDFs) in this folder.
- Create a complete bibliography entry for each of your sources (including books and other non-digital sources) and save the file to this folder.
- As you read your sources, take notes under the bibliography entry. Be sure to note the page numbers as appropriate.
When it comes time to put these ideas together into a first draft of your paper, it will be easy to see which ideas came from which source. This will make writing a lot easier, but also help you to see how your sources agree or disagree on your topic, and make sure you avoid accidentally plagiarizing any of your sources.
Many students and researchers like to use a citation management tool to help keep their sources organized, and to create citations and references. If you're interested in this, you may want to have a look at this information about using Zotero , which is one example of a citation manager.
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- USC Libraries
- Research Guides
Organizing Your Social Sciences Research Paper
- Types of Research Designs
- Purpose of Guide
- Design Flaws to Avoid
- Independent and Dependent Variables
- Glossary of Research Terms
- Reading Research Effectively
- Narrowing a Topic Idea
- Broadening a Topic Idea
- Extending the Timeliness of a Topic Idea
- Academic Writing Style
- Applying Critical Thinking
- Choosing a Title
- Making an Outline
- Paragraph Development
- Research Process Video Series
- Executive Summary
- The C.A.R.S. Model
- Background Information
- The Research Problem/Question
- Theoretical Framework
- Citation Tracking
- Content Alert Services
- Evaluating Sources
- Primary Sources
- Secondary Sources
- Tiertiary Sources
- Scholarly vs. Popular Publications
- Qualitative Methods
- Quantitative Methods
- Insiderness
- Using Non-Textual Elements
- Limitations of the Study
- Common Grammar Mistakes
- Writing Concisely
- Avoiding Plagiarism
- Footnotes or Endnotes?
- Further Readings
- Generative AI and Writing
- USC Libraries Tutorials and Other Guides
- Bibliography
Introduction
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. Writing@CSU. 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.
Causal Design
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.
Cohort Design
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 Design
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 Design
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.
Experimental Design
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.
Exploratory Design
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.
Historical Design
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.
Longitudinal Design
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 Design
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.
Mixed-Method Design
- 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 .
Observational Design
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.
Philosophical Design
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.
Sequential Design
- 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.
Systematic Review
- 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); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; 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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Research Design | Step-by-Step Guide with Examples
Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.
A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about:
- Your overall aims and approach
- The type of research design you’ll use
- Your sampling methods or criteria for selecting subjects
- Your data collection methods
- The procedures you’ll follow to collect data
- Your data analysis methods
A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.
Table of contents
Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.
- Introduction
Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.
There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.
The first choice you need to make is whether you’ll take a qualitative or quantitative approach.
Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.
Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.
It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.
Practical and ethical considerations when designing research
As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .
- How much time do you have to collect data and write up the research?
- Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
- Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
- Will you need ethical approval ?
At each stage of the research design process, make sure that your choices are practically feasible.
Prevent plagiarism, run a free check.
Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.
Types of quantitative research designs
Quantitative designs can be split into four main types. Experimental and quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.
With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).
Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.
Types of qualitative research designs
Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.
The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.
Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.
In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.
Defining the population
A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.
For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?
The more precisely you define your population, the easier it will be to gather a representative sample.
Sampling methods
Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.
To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.
Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.
For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.
Case selection in qualitative research
In some types of qualitative designs, sampling may not be relevant.
For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.
In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.
For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.
Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.
You can choose just one data collection method, or use several methods in the same study.
Survey methods
Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.
Observation methods
Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.
Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.
Other methods of data collection
There are many other ways you might collect data depending on your field and topic.
If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.
Secondary data
If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.
With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.
Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.
However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.
As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.
Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.
Operationalisation
Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.
If you’re using observations , which events or actions will you count?
If you’re using surveys , which questions will you ask and what range of responses will be offered?
You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.
Reliability and validity
Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.
For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.
If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.
Sampling procedures
As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.
That means making decisions about things like:
- How many participants do you need for an adequate sample size?
- What inclusion and exclusion criteria will you use to identify eligible participants?
- How will you contact your sample – by mail, online, by phone, or in person?
If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?
If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?
Data management
It’s also important to create a data management plan for organising and storing your data.
Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.
Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.
On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.
Quantitative data analysis
In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.
Using descriptive statistics , you can summarise your sample data in terms of:
- The distribution of the data (e.g., the frequency of each score on a test)
- The central tendency of the data (e.g., the mean to describe the average score)
- The variability of the data (e.g., the standard deviation to describe how spread out the scores are)
The specific calculations you can do depend on the level of measurement of your variables.
Using inferential statistics , you can:
- Make estimates about the population based on your sample data.
- Test hypotheses about a relationship between variables.
Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.
Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.
Qualitative data analysis
In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.
Two of the most common approaches to doing this are thematic analysis and discourse analysis .
There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.
A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.
For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.
Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.
Operationalisation means turning abstract conceptual ideas into measurable observations.
For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.
Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.
The research methods you use depend on the type of data you need to answer your research question .
- If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
- If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
- If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.
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What Is A Research Proposal?
Plain Language Explainer With Examples + Free Template
By: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020 (Updated April 2023)
Overview: Research Proposal Basics
- What a research proposal is
- What a research proposal needs to cover
- How to structure your research proposal
- Example /sample proposals
- Proposal writing FAQs
- Key takeaways & additional resources
What is a research proposal?
Simply put, a research proposal is a structured, formal document that explains what you plan to research (your research topic), why it’s worth researching (your justification), and how you plan to investigate it (your methodology).
The purpose of the research proposal (its 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?
A good dissertation or thesis proposal needs to cover the “ what “, “ why ” and” how ” of the proposed study. Let’s look at each of these attributes 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 of a well-articulated research 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 or advocate for a brand of a specific makeup brand
- Who it involves – female Gen-Y consumers
- In what context – the United Kingdom
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 achieve your research aims?
As an 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 valuable, but you’re not going to convince anyone to approve it without discussing the practicalities – in other words:
- How will you actually undertake your research (i.e., your methodology)?
- Is your research methodology appropriate given your research aims?
- Is your approach manageable given your constraints (time, money, etc.)?
While it’s generally not expected that you’ll have a fully fleshed-out methodology at the proposal stage, you’ll likely still need to provide a high-level overview of your research methodology . Here are some important questions you’ll need to address in your research proposal:
- Will you take a qualitative , quantitative or mixed -method approach?
- What sampling strategy will you adopt?
- How will you collect your data (e.g., interviews , surveys, etc)?
- How will you analyse your data (e.g., descriptive and inferential statistics , content analysis, discourse analysis, etc, .)?
- What potential limitations will your methodology carry?
So, be sure to give some thought to the practicalities of your research and have at least a basic methodological plan before you start writing up your proposal. If this all sounds rather intimidating, the video below provides a good introduction to research methodology and the key choices you’ll need to make.
How To Structure A Research Proposal
Now that we’ve covered the key points that need to be addressed in a proposal, you may be wondering, “ But how is a research proposal structured? “.
While the exact structure and format required for a research proposal differs from university to university, there are four “essential ingredients” that commonly make up the structure of a research proposal:
- A rich introduction and background to the proposed research
- An initial literature review covering the existing research
- An overview of the proposed research methodology
- A discussion regarding the practicalities (project plans, timelines, etc.)
In the video below, we unpack each of these four sections, step by step.
Research Proposal Examples/Samples
In the video below, we provide a detailed walkthrough of two successful research proposals (Master’s and PhD-level), as well as our popular free proposal template.
Proposal Writing FAQs
How long should a research proposal be.
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 do I choose a topic for my research proposal?
Finding a good research topic is a process that involves multiple steps. We cover the topic ideation process in this video post.
How do I write a literature review for my proposal?
While you typically won’t need a comprehensive literature review at the proposal stage, you still need to demonstrate that you’re familiar with the key literature and are able to synthesise it. We explain the literature review process here.
How do I create a timeline and budget for my proposal?
We explain how to craft a project plan/timeline and budget in Research Proposal Bootcamp .
Which referencing format should I use in my research proposal?
The expectations and requirements regarding formatting and referencing vary from institution to institution. Therefore, you’ll need to check this information with your university.
What common proposal writing mistakes do I need to look out for?
We’ve create a video post about some of the most common mistakes students make when writing a proposal – you can access that here . If you’re short on time, here’s a quick summary:
- The research topic is too broad (or just poorly articulated).
- The research aims, objectives and questions don’t align.
- The research topic is not well justified.
- The study has a weak theoretical foundation.
- The research design is not well articulated well enough.
- Poor writing and sloppy presentation.
- Poor project planning and risk management.
- Not following the university’s specific criteria.
Key Takeaways & Additional Resources
As you write up your research proposal, remember the all-important core purpose: to convince . Your research proposal needs to sell your study in terms of suitability and viability. So, focus on crafting a convincing narrative to ensure a strong proposal.
At the same time, pay close attention to your university’s requirements. While we’ve covered the essentials here, every institution has its own set of expectations and it’s essential that you follow these to maximise your chances of approval.
By the way, we’ve got plenty more resources to help you fast-track your research proposal. Here are some of our most popular resources to get you started:
- Proposal Writing 101 : A Introductory Webinar
- Research Proposal Bootcamp : The Ultimate Online Course
- Template : A basic template to help you craft your proposal
If you’re looking for 1-on-1 support with your research proposal, be sure to check out our private coaching service , where we hold your hand through the proposal development process (and the entire research journey), step by step.
Ace Your Research Proposal
How To Choose A Tutor For Your Dissertation
Hiring the right tutor for your dissertation or thesis can make the difference between passing and failing. Here’s what you need to consider.
5 Signs You Need A Dissertation Helper
Discover the 5 signs that suggest you need a dissertation helper to get unstuck, finish your degree and get your life back.
How To Choose A Research Topic: 5 Key Criteria
How To Choose A Research Topic Step-By-Step Tutorial With Examples + Free Topic...
Writing A Research Proposal: 4 Hacks To Fast-Track The Process
🎙️ PODCAST: Writing A Research Proposal 4 Time-Saving Tips To Fast-Track Your...
Research Proposal Essentials: 5 Critical Dos & Don’ts
Learn about 5 critically important things that you need to do (or avoid doing) when writing a research proposal for a dissertation or thesis.
📄 FREE TEMPLATES
Research Topic Ideation
Proposal Writing
Literature Review
Methodology & Analysis
Academic Writing
Referencing & Citing
Apps, Tools & Tricks
The Grad Coach Podcast
53 Comments
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You’re most welcome. We don’t have any research proposals that we can share (the students own the intellectual property), but you might find our research proposal template useful: https://gradcoach.com/research-proposal-template/
Cheruiyot Moses Kipyegon
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Thank you. This is a great insight. I am a student preparing for a PhD program. I am requested to write my Research Proposal as part of what I am required to submit before my unconditional admission. I am grateful having listened to this video which will go a long way in helping me to actually choose a topic of interest and not just any topic as well as to narrow down the topic and be specific about it. I indeed need more of this especially as am trying to choose a topic suitable for a DBA am about embarking on. Thank you once more. The video is indeed helpful.
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Home » Assignment – Types, Examples and Writing Guide
Assignment – Types, Examples and Writing Guide
Table of Contents
Definition:
Assignment is a task given to students by a teacher or professor, usually as a means of assessing their understanding and application of course material. Assignments can take various forms, including essays, research papers, presentations, problem sets, lab reports, and more.
Assignments are typically designed to be completed outside of class time and may require independent research, critical thinking, and analysis. They are often graded and used as a significant component of a student’s overall course grade. The instructions for an assignment usually specify the goals, requirements, and deadlines for completion, and students are expected to meet these criteria to earn a good grade.
History of Assignment
The use of assignments as a tool for teaching and learning has been a part of education for centuries. Following is a brief history of the Assignment.
- Ancient Times: Assignments such as writing exercises, recitations, and memorization tasks were used to reinforce learning.
- Medieval Period : Universities began to develop the concept of the assignment, with students completing essays, commentaries, and translations to demonstrate their knowledge and understanding of the subject matter.
- 19th Century : With the growth of schools and universities, assignments became more widespread and were used to assess student progress and achievement.
- 20th Century: The rise of distance education and online learning led to the further development of assignments as an integral part of the educational process.
- Present Day: Assignments continue to be used in a variety of educational settings and are seen as an effective way to promote student learning and assess student achievement. The nature and format of assignments continue to evolve in response to changing educational needs and technological innovations.
Types of Assignment
Here are some of the most common types of assignments:
An essay is a piece of writing that presents an argument, analysis, or interpretation of a topic or question. It usually consists of an introduction, body paragraphs, and a conclusion.
Essay structure:
- Introduction : introduces the topic and thesis statement
- Body paragraphs : each paragraph presents a different argument or idea, with evidence and analysis to support it
- Conclusion : summarizes the key points and reiterates the thesis statement
Research paper
A research paper involves gathering and analyzing information on a particular topic, and presenting the findings in a well-structured, documented paper. It usually involves conducting original research, collecting data, and presenting it in a clear, organized manner.
Research paper structure:
- Title page : includes the title of the paper, author’s name, date, and institution
- Abstract : summarizes the paper’s main points and conclusions
- Introduction : provides background information on the topic and research question
- Literature review: summarizes previous research on the topic
- Methodology : explains how the research was conducted
- Results : presents the findings of the research
- Discussion : interprets the results and draws conclusions
- Conclusion : summarizes the key findings and implications
A case study involves analyzing a real-life situation, problem or issue, and presenting a solution or recommendations based on the analysis. It often involves extensive research, data analysis, and critical thinking.
Case study structure:
- Introduction : introduces the case study and its purpose
- Background : provides context and background information on the case
- Analysis : examines the key issues and problems in the case
- Solution/recommendations: proposes solutions or recommendations based on the analysis
- Conclusion: Summarize the key points and implications
A lab report is a scientific document that summarizes the results of a laboratory experiment or research project. It typically includes an introduction, methodology, results, discussion, and conclusion.
Lab report structure:
- Title page : includes the title of the experiment, author’s name, date, and institution
- Abstract : summarizes the purpose, methodology, and results of the experiment
- Methods : explains how the experiment was conducted
- Results : presents the findings of the experiment
Presentation
A presentation involves delivering information, data or findings to an audience, often with the use of visual aids such as slides, charts, or diagrams. It requires clear communication skills, good organization, and effective use of technology.
Presentation structure:
- Introduction : introduces the topic and purpose of the presentation
- Body : presents the main points, findings, or data, with the help of visual aids
- Conclusion : summarizes the key points and provides a closing statement
Creative Project
A creative project is an assignment that requires students to produce something original, such as a painting, sculpture, video, or creative writing piece. It allows students to demonstrate their creativity and artistic skills.
Creative project structure:
- Introduction : introduces the project and its purpose
- Body : presents the creative work, with explanations or descriptions as needed
- Conclusion : summarizes the key elements and reflects on the creative process.
Examples of Assignments
Following are Examples of Assignment templates samples:
Essay template:
I. Introduction
- Hook: Grab the reader’s attention with a catchy opening sentence.
- Background: Provide some context or background information on the topic.
- Thesis statement: State the main argument or point of your essay.
II. Body paragraphs
- Topic sentence: Introduce the main idea or argument of the paragraph.
- Evidence: Provide evidence or examples to support your point.
- Analysis: Explain how the evidence supports your argument.
- Transition: Use a transition sentence to lead into the next paragraph.
III. Conclusion
- Restate thesis: Summarize your main argument or point.
- Review key points: Summarize the main points you made in your essay.
- Concluding thoughts: End with a final thought or call to action.
Research paper template:
I. Title page
- Title: Give your paper a descriptive title.
- Author: Include your name and institutional affiliation.
- Date: Provide the date the paper was submitted.
II. Abstract
- Background: Summarize the background and purpose of your research.
- Methodology: Describe the methods you used to conduct your research.
- Results: Summarize the main findings of your research.
- Conclusion: Provide a brief summary of the implications and conclusions of your research.
III. Introduction
- Background: Provide some background information on the topic.
- Research question: State your research question or hypothesis.
- Purpose: Explain the purpose of your research.
IV. Literature review
- Background: Summarize previous research on the topic.
- Gaps in research: Identify gaps or areas that need further research.
V. Methodology
- Participants: Describe the participants in your study.
- Procedure: Explain the procedure you used to conduct your research.
- Measures: Describe the measures you used to collect data.
VI. Results
- Quantitative results: Summarize the quantitative data you collected.
- Qualitative results: Summarize the qualitative data you collected.
VII. Discussion
- Interpretation: Interpret the results and explain what they mean.
- Implications: Discuss the implications of your research.
- Limitations: Identify any limitations or weaknesses of your research.
VIII. Conclusion
- Review key points: Summarize the main points you made in your paper.
Case study template:
- Background: Provide background information on the case.
- Research question: State the research question or problem you are examining.
- Purpose: Explain the purpose of the case study.
II. Analysis
- Problem: Identify the main problem or issue in the case.
- Factors: Describe the factors that contributed to the problem.
- Alternative solutions: Describe potential solutions to the problem.
III. Solution/recommendations
- Proposed solution: Describe the solution you are proposing.
- Rationale: Explain why this solution is the best one.
- Implementation: Describe how the solution can be implemented.
IV. Conclusion
- Summary: Summarize the main points of your case study.
Lab report template:
- Title: Give your report a descriptive title.
- Date: Provide the date the report was submitted.
- Background: Summarize the background and purpose of the experiment.
- Methodology: Describe the methods you used to conduct the experiment.
- Results: Summarize the main findings of the experiment.
- Conclusion: Provide a brief summary of the implications and conclusions
- Background: Provide some background information on the experiment.
- Hypothesis: State your hypothesis or research question.
- Purpose: Explain the purpose of the experiment.
IV. Materials and methods
- Materials: List the materials and equipment used in the experiment.
- Procedure: Describe the procedure you followed to conduct the experiment.
- Data: Present the data you collected in tables or graphs.
- Analysis: Analyze the data and describe the patterns or trends you observed.
VI. Discussion
- Implications: Discuss the implications of your findings.
- Limitations: Identify any limitations or weaknesses of the experiment.
VII. Conclusion
- Restate hypothesis: Summarize your hypothesis or research question.
- Review key points: Summarize the main points you made in your report.
Presentation template:
- Attention grabber: Grab the audience’s attention with a catchy opening.
- Purpose: Explain the purpose of your presentation.
- Overview: Provide an overview of what you will cover in your presentation.
II. Main points
- Main point 1: Present the first main point of your presentation.
- Supporting details: Provide supporting details or evidence to support your point.
- Main point 2: Present the second main point of your presentation.
- Main point 3: Present the third main point of your presentation.
- Summary: Summarize the main points of your presentation.
- Call to action: End with a final thought or call to action.
Creative writing template:
- Setting: Describe the setting of your story.
- Characters: Introduce the main characters of your story.
- Rising action: Introduce the conflict or problem in your story.
- Climax: Present the most intense moment of the story.
- Falling action: Resolve the conflict or problem in your story.
- Resolution: Describe how the conflict or problem was resolved.
- Final thoughts: End with a final thought or reflection on the story.
How to Write Assignment
Here is a general guide on how to write an assignment:
- Understand the assignment prompt: Before you begin writing, make sure you understand what the assignment requires. Read the prompt carefully and make note of any specific requirements or guidelines.
- Research and gather information: Depending on the type of assignment, you may need to do research to gather information to support your argument or points. Use credible sources such as academic journals, books, and reputable websites.
- Organize your ideas : Once you have gathered all the necessary information, organize your ideas into a clear and logical structure. Consider creating an outline or diagram to help you visualize your ideas.
- Write a draft: Begin writing your assignment using your organized ideas and research. Don’t worry too much about grammar or sentence structure at this point; the goal is to get your thoughts down on paper.
- Revise and edit: After you have written a draft, revise and edit your work. Make sure your ideas are presented in a clear and concise manner, and that your sentences and paragraphs flow smoothly.
- Proofread: Finally, proofread your work for spelling, grammar, and punctuation errors. It’s a good idea to have someone else read over your assignment as well to catch any mistakes you may have missed.
- Submit your assignment : Once you are satisfied with your work, submit your assignment according to the instructions provided by your instructor or professor.
Applications of Assignment
Assignments have many applications across different fields and industries. Here are a few examples:
- Education : Assignments are a common tool used in education to help students learn and demonstrate their knowledge. They can be used to assess a student’s understanding of a particular topic, to develop critical thinking skills, and to improve writing and research abilities.
- Business : Assignments can be used in the business world to assess employee skills, to evaluate job performance, and to provide training opportunities. They can also be used to develop business plans, marketing strategies, and financial projections.
- Journalism : Assignments are often used in journalism to produce news articles, features, and investigative reports. Journalists may be assigned to cover a particular event or topic, or to research and write a story on a specific subject.
- Research : Assignments can be used in research to collect and analyze data, to conduct experiments, and to present findings in written or oral form. Researchers may be assigned to conduct research on a specific topic, to write a research paper, or to present their findings at a conference or seminar.
- Government : Assignments can be used in government to develop policy proposals, to conduct research, and to analyze data. Government officials may be assigned to work on a specific project or to conduct research on a particular topic.
- Non-profit organizations: Assignments can be used in non-profit organizations to develop fundraising strategies, to plan events, and to conduct research. Volunteers may be assigned to work on a specific project or to help with a particular task.
Purpose of Assignment
The purpose of an assignment varies depending on the context in which it is given. However, some common purposes of assignments include:
- Assessing learning: Assignments are often used to assess a student’s understanding of a particular topic or concept. This allows educators to determine if a student has mastered the material or if they need additional support.
- Developing skills: Assignments can be used to develop a wide range of skills, such as critical thinking, problem-solving, research, and communication. Assignments that require students to analyze and synthesize information can help to build these skills.
- Encouraging creativity: Assignments can be designed to encourage students to be creative and think outside the box. This can help to foster innovation and original thinking.
- Providing feedback : Assignments provide an opportunity for teachers to provide feedback to students on their progress and performance. Feedback can help students to understand where they need to improve and to develop a growth mindset.
- Meeting learning objectives : Assignments can be designed to help students meet specific learning objectives or outcomes. For example, a writing assignment may be designed to help students improve their writing skills, while a research assignment may be designed to help students develop their research skills.
When to write Assignment
Assignments are typically given by instructors or professors as part of a course or academic program. The timing of when to write an assignment will depend on the specific requirements of the course or program, but in general, assignments should be completed within the timeframe specified by the instructor or program guidelines.
It is important to begin working on assignments as soon as possible to ensure enough time for research, writing, and revisions. Waiting until the last minute can result in rushed work and lower quality output.
It is also important to prioritize assignments based on their due dates and the amount of work required. This will help to manage time effectively and ensure that all assignments are completed on time.
In addition to assignments given by instructors or professors, there may be other situations where writing an assignment is necessary. For example, in the workplace, assignments may be given to complete a specific project or task. In these situations, it is important to establish clear deadlines and expectations to ensure that the assignment is completed on time and to a high standard.
Characteristics of Assignment
Here are some common characteristics of assignments:
- Purpose : Assignments have a specific purpose, such as assessing knowledge or developing skills. They are designed to help students learn and achieve specific learning objectives.
- Requirements: Assignments have specific requirements that must be met, such as a word count, format, or specific content. These requirements are usually provided by the instructor or professor.
- Deadline: Assignments have a specific deadline for completion, which is usually set by the instructor or professor. It is important to meet the deadline to avoid penalties or lower grades.
- Individual or group work: Assignments can be completed individually or as part of a group. Group assignments may require collaboration and communication with other group members.
- Feedback : Assignments provide an opportunity for feedback from the instructor or professor. This feedback can help students to identify areas of improvement and to develop their skills.
- Academic integrity: Assignments require academic integrity, which means that students must submit original work and avoid plagiarism. This includes citing sources properly and following ethical guidelines.
- Learning outcomes : Assignments are designed to help students achieve specific learning outcomes. These outcomes are usually related to the course objectives and may include developing critical thinking skills, writing abilities, or subject-specific knowledge.
Advantages of Assignment
There are several advantages of assignment, including:
- Helps in learning: Assignments help students to reinforce their learning and understanding of a particular topic. By completing assignments, students get to apply the concepts learned in class, which helps them to better understand and retain the information.
- Develops critical thinking skills: Assignments often require students to think critically and analyze information in order to come up with a solution or answer. This helps to develop their critical thinking skills, which are important for success in many areas of life.
- Encourages creativity: Assignments that require students to create something, such as a piece of writing or a project, can encourage creativity and innovation. This can help students to develop new ideas and perspectives, which can be beneficial in many areas of life.
- Builds time-management skills: Assignments often come with deadlines, which can help students to develop time-management skills. Learning how to manage time effectively is an important skill that can help students to succeed in many areas of life.
- Provides feedback: Assignments provide an opportunity for students to receive feedback on their work. This feedback can help students to identify areas where they need to improve and can help them to grow and develop.
Limitations of Assignment
There are also some limitations of assignments that should be considered, including:
- Limited scope: Assignments are often limited in scope, and may not provide a comprehensive understanding of a particular topic. They may only cover a specific aspect of a topic, and may not provide a full picture of the subject matter.
- Lack of engagement: Some assignments may not engage students in the learning process, particularly if they are repetitive or not challenging enough. This can lead to a lack of motivation and interest in the subject matter.
- Time-consuming: Assignments can be time-consuming, particularly if they require a lot of research or writing. This can be a disadvantage for students who have other commitments, such as work or extracurricular activities.
- Unreliable assessment: The assessment of assignments can be subjective and may not always accurately reflect a student’s understanding or abilities. The grading may be influenced by factors such as the instructor’s personal biases or the student’s writing style.
- Lack of feedback : Although assignments can provide feedback, this feedback may not always be detailed or useful. Instructors may not have the time or resources to provide detailed feedback on every assignment, which can limit the value of the feedback that students receive.
About the author
Muhammad Hassan
Researcher, Academic Writer, Web developer
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What is Research Methodology? Definition, Types, and Examples
Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.
The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.
What is research methodology ?
A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.
Having a good research methodology in place has the following advantages: 3
- Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
- You can easily answer any questions about your research if they arise at a later stage.
- A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
- It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
- A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
- It also helps ensure that ethical guidelines are followed while conducting research.
- A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.
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Types of research methodology.
There are three types of research methodology based on the type of research and the data required. 1
- Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
- Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
- Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.
What are the types of sampling designs in research methodology?
Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.
- Probability sampling
In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:
- Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
- Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
- Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
- Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
- Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
- Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
- Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.
What are data collection methods?
During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.
Qualitative research 5
- One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
- Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
- Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
- Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).
Quantitative research 6
- Sampling: The most common type is probability sampling.
- Interviews: Commonly telephonic or done in-person.
- Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
- Document review: Reviewing existing research or documents to collect evidence for supporting the research.
- Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.
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What are data analysis methods.
The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.
Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.
Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:
- Measures of frequency (count, percent, frequency)
- Measures of central tendency (mean, median, mode)
- Measures of dispersion or variation (range, variance, standard deviation)
- Measure of position (percentile ranks, quartile ranks)
Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:
- Correlation: To understand the relationship between two or more variables.
- Cross-tabulation: Analyze the relationship between multiple variables.
- Regression analysis: Study the impact of independent variables on the dependent variable.
- Frequency tables: To understand the frequency of data.
- Analysis of variance: To test the degree to which two or more variables differ in an experiment.
Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:
- Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
- Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
- Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
- Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
- Thematic analysis: To identify important themes or patterns in data and use these to address an issue.
How to choose a research methodology?
Here are some important factors to consider when choosing a research methodology: 8
- Research objectives, aims, and questions —these would help structure the research design.
- Review existing literature to identify any gaps in knowledge.
- Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
- Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
- Constraints —constraints of time, geography, and resources can help define the appropriate methodology.
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How to write a research methodology .
A research methodology should include the following components: 3,9
- Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
- Research method —this can be quantitative, qualitative, or mixed-method.
- Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
- Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
- Sampling —this involves selecting a representative subset of the population being studied.
- Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
- Data analysis —describe the data analysis methods you will use once you’ve collected the data.
- Research limitations —mention any limitations you foresee while conducting your research.
- Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
- Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.
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Frequently Asked Questions
Q1. What are the key components of research methodology?
A1. A good research methodology has the following key components:
- Research design
- Data collection procedures
- Data analysis methods
- Ethical considerations
Q2. Why is ethical consideration important in research methodology?
A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10
- Participants should not be subjected to harm.
- Respect for the dignity of participants should be prioritized.
- Full consent should be obtained from participants before the study.
- Participants’ privacy should be ensured.
- Confidentiality of the research data should be ensured.
- Anonymity of individuals and organizations participating in the research should be maintained.
- The aims and objectives of the research should not be exaggerated.
- Affiliations, sources of funding, and any possible conflicts of interest should be declared.
- Communication in relation to the research should be honest and transparent.
- Misleading information and biased representation of primary data findings should be avoided.
Q3. What is the difference between methodology and method?
A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.
Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.
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- Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
- Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
- The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
- Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
- What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
- What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
- Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
- Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
- What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
- Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/
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