design research report sample

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Design Research Report Examples

Design research reports take on many different formats. Notice how each of these research reports (often referred to as “Case Studies”) tells a story. They aren’t just data, charts, and conclusions—they bring the human element into the story.

Research Report Examples

These examples specifically report research.

• Oxford Commuters and the Efficacy of Political Advertising : xdMFA Fall 2016 Students, Mateus & Chen
• Exploring Adult Satisfaction Within Healthcare Facilities : Comm Design Fall 2018 Students, Goheen, Cortez, Eshett
• The Use of Plastic at Miami University Off-Campus Parties : Comm Design Fall 2019 Students, Troyer & Nguyen

Research Reports with Design Prototypes

These reports share research outcomes and take the next step—design prototyping. These students in the xdMFA program conducted research and created outcomes based on their research.

• Conversation Groups & The Intersections of Language & Culture : xdMFA Fall 2018 Students Dean, Huffman, Mauk
• The Anthropomorphizing of Technology : xdMFA 2016 Student Jerry Belich
• Pokémon-Go AR Game: Designing To Match The Pokémon Fans Needs : xdMFA 2015 Students Cela, Chen, Mateus Forero, Mandke
• Teaching Anatomy to Yoga Teacher Trainees : xdMFA Fall 2016 Student Ali Place

Case Studies

The rest of these reports show a wide range of types of reporting. Most are geared toward stakeholders/supporters of each project and their communities.

• City of Owasso Character Initiative : Cheatham, Hicks, Keefer, Yang
• The Design Difference : Japan Society, the Designers Accord, Common Ground, and GOOD
• Valuing Design: Mapping Design Impact and Value in Six Public and 3rd Sector Projects : Yee, White, Lennon

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What is UX Research: The Ultimate Guide for UX Researchers

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How to write and present effective UX research reports

Regardless of how thorough or valuable your user research is, it quickly becomes meaningless if you’re unable to succinctly put it together and present it in a digestible UX research report.

UX research reporting is a skill just as valuable as being able to conduct the research in the first place. It lets you showcase methodology and findings of your research, and ensure a product’s user experience delivers with the first iteration.

Luckily, how to write and present UX research reports is something you can learn. What’s more, this chapter will guide you through it (and provide free templates for your UX report).

What is a UX research report?

A user research report is an easy-to-digest summary of a user research project that aims to update product stakeholders on results, inform product decisions with user data, and harmoniously guide a product build or iteration.

Once upon a time, UX research reporting was a cumbersome, dreaded box to tick. It was notorious for resulting in unnavigable reports that product teams would rather leave at the bottom of their inbox than try to consume.

The word 'report' conjures images of lengthy word documents, a PDF one-pager, or hour-long presentation with an occasional GIF—but a research report doesn't have to mean that.

Kevin Rapley , Senior User Researcher at Justice Digital, explains a UX report as being “about arming our teammates with data that allows them to decide on the direction of a product or service.”

A useful UX report includes:

• The research goals and research process
• Research questions the report is hoping to answer
• A recap of the UX research plan
• What UX research methods were used and why
• Quantitative and qualitative data sets and conclusions
• Key insights & actionable takeaways
• An expanded data appendix

Why do you need a user research report?

Product teams need a user research report to reflect on research activities and accurately guide a product’s scope with key insights. A UX research report helps sort information, defend research, and affirm (or disprove) a hypothesis. No matter how well-organized your research repository is, sometimes simply having the research results available is not enough. A succinct report will align entire teams in one sitting by presenting findings in a unique way.

In short, a research report helps to:

• Positively influence UX design
• Make sense of data sets and explain complicated graphs or other quantitative research results
• Provide actionable recommendations on next steps
• Summarize key findings, so they can be translated into every role and responsibility of the product team

Where UX research enables product teams to understand the user, prove or disprove hypotheses, and prioritize and generate ideas, a UX research report ensures the user is at the center of every product decision. Presenting that UX report then aligns team members on goals and priorities, and provides authentic user insights to inform every product decision.

We’ve covered what a research report is , but what is it not ? A UX research report is not a static, one-time document that your team reads once. It’s an ongoing reference point; the guardrails and guiding insights that guarantees the entire build stays on track.

How to write an effective UX research report: the essential elements

No matter how you choose to present your research study, there are a few elements that every report needs to include for it to be both useful and effective. Let’s look at how to create a report.

Introduction

Your introduction should lay out your research goals, plan, and scope. It should cover your product team’s pain points, and give a clear study overview. You need to answer what you did and why. The introduction can go on to include sales support data and competitive product analysis that inspired or guided this research project.

It’s a good idea to set up how this research helps to support and answer related company goals, team-level goals, and product-dev goals: so all stakeholders know it’s got something for them.

You can include questions from your UX research strategy you had originally hoped to answer, even if your results have gone on to answer other questions as well. Now’s also a good time to introduce research stakeholders: your fellow research team members.

As a secondary step to your introduction, ensure you’re including the approach you took to your UX research process : i.e. what research methods you used, as well as participant profiles and your user personas .

Don’t feel you need to spend too much time on this, says Charlie Herbozo Vidal , Senior User Experience Researcher at CVS Health. “As researchers, it’s not uncommon to dwell on the methodology for longer than needed. While interrogating methods might be valuable to other researchers, business partners might be disengaged by them.”

Ultimately, while methodology is important, it’s the results that most people are here for.

Key findings

This is where you get people on the edge of their seats! Give an overview of your findings, before breaking them down into more detail. Remind your audience ‘what we thought’ vs. what you actually learned.

Artifacts to use are:

• User personas built
• Insights from customer interviews
• User journey maps
• Prototype testing
• Storyboards
• Feedback & satisfaction reports

At the end of this section, and continuing throughout your presentation, you can pepper relevant atomic research nuggets.

Make sure you champion the user's needs throughout, and make special notes of 'offhand' comments users make. Often, it's the random comments that provide the most insight—they must not be forgotten about when writing the report.

Jack Dyer , Designer at Interactive Schools

Summarize your quantitative and qualitative research , and how they’ll both impact your product design and growth. Lay out opportunities versus risks, good-to-knows versus must-knows. Here you’ll want to convey the impact of each suggested step, roadmap designs, and figure out the long and short-term project scope. A few things to cover in your next steps are:

• Long and short-term goals
• ICE framework (Impact, confidence, ease)
• Roles and responsibilities for each task
• A timeline of events and project map
• A request for resources
• Desired outcomes

No matter how you’re presenting your research, be it asynchronously or not, you’ll need to include a Q&A. These can be subjective (based on what you think your team is likely to ask), pre-collected ahead of the presentation, answered live, or an opportunity to build an FAQ later.

What’s important is to acknowledge and be open to receiving questions. After all, questions are a positive thing—it means people are actually listening!

It’s easy to overlook the appendix after putting together a detailed report, but all that glorious research data needs to be accounted for and referenced clearly. Plus, you never know to what extent your team will want to dive into it. Your appendix is also where you’ll want to include secondary research that didn’t make the cut but backs up your research.

9 ways to present UX research findings

UX research reporting will look a little different depending on your internal personas and organizational culture. First, ask yourself: who is your audience? Who needs to see the report, and who will benefit from seeing it? This will help determine how to present your user research report.

A few things to consider:

• Are you working with internal or external stakeholders? Tool limitation and file-sharing will differ for both.
• Are you working with an in-office, fully-remote, or hybrid team?
• Are you sitting in the same time zone or not?
• What are the knowledge levels like within your team?
• How does your team communicate daily/weekly/monthly?
• Are there any predetermined knowledge bases or tools your team is comfortable with?

The most common players across a UX team that need to understand your UX research report are:

• Product Designers (UX/UI)
• Fellow Product Researchers
• UX/UI Writers

However , it doesn’t stop at your product decision-making team. More often than not, there will be other stakeholders that can benefit from your research presentation. Your marketing, finance, sales, and even C-suite executives will massively benefit from your findings too. If you can tailor versions of your report or provide key summaries for each collective, even better!

Psst 👉 This is much easier to do when you have a research team that can host stakeholder interviews ahead of your research process.

Now, let’s get into the report formats to consider:

1. Workshops: for real-time, collaborative reports

First up, workshops. Workshops are a unique way of keeping your report interactive and engaging. They can be held remotely or in-person, but are almost impossible to hold asynchronously—so time zones are a big factor here.

You’ll also want to consider workshopping tools if you’re hosting digitally—a few to consider are: Miro, Mural, FigJam, and Gather.

A plus with workshops is that your stakeholders will actively have a say early on in the product development process , allowing you to foster more diverse inputs, minimize research bias you may have accumulated in your summaries, and build a sense of responsibility for the product’s success early on.

A negative of workshops is that they can be culprits to in-the-room or bandwagon bias. People are quick to ride on the coattails of a strong conclusion, without fully understanding or trialing another (less popular) conclusion or suggestion.

2. Slack channels: for an asynchronous and interactive research repository

Slack is a great option (especially if you’re already using it) if your research team needs to deliver insights to a fully-distributed collection of stakeholders. Slack tends to be the go-to channel for startups and creative companies, and there’s some key features you can tap into:

• Canvas: Store files, images, videos, and more in one place
• Huddles: Jump on a quick chat to fill in any gaps
• Clips: Post audio, video, or screen-sharing clips
• Connect: Team up with freelancers and agencies working on the project with you
• Workflow: Build drag-and-drop processes from your findings
• Knowledge sharing: Tag your data accordingly so it's easy to find later

3. Knowledge bases: for self-serve UX research reports

Knowledge bases can be a great home for your research presentation, and work especially well for distributed teams working across different time zones.

However your team is set up, research repositories are incredibly valuable. Sharing your report in a centralized location, regardless of the other ways you distribute findings, can democratize research , showcase the impact of your work, and disseminate valuable insights throughout your entire organization.

Keep in mind that knowledge bases can be tough to navigate if poorly organized or tagged. If you’re storing your UX research report in a knowledge base, ensure you provide clear instructions on how someone can find it, and how to navigate through the report itself.

If you have the time, run a card sorting test with an internal focus group to see how you can logically sort your research for those who are going to be looking for it.

4. Presentations / slide decks: great for the PAS framework

Live presentations tend to be the most impactful, but do risk being short-lived if you don’t have a follow-up plan for after your presentation.

While they’re great for sharing metrics and visuals, and can provide a beautiful overview of your research project, presentations can be a little one-sided. This one-way presentation style can prevent collaboration and innovation from the rest of the team. Consider how you can make your presentation interactive or engaging, whether it’s taking questions throughout or doing a ‘choose your own adventure’ session and asking people which sections they want to review first.

Kevin Rapley , Senior User Researcher at Justice Digital, recommends presenting slides using the PAS framework:

• Problem: State the problem you set out to overcome
• Agitate: Detail the impact or opportunity missed by not meeting the problem
• Solution: Offer a route forward from the research findings and insights, the next steps, and likely outcomes by solving the problem

Kevin explains that the PAS framework cuts to the detail people are invested in: “Stakeholders want to know the path forward: Are we on the right track to build this service? Have we uncovered user engagement or uptake issues? Have we learned that our assumptions are incorrect and we now have a better understanding of user needs? Presenting slides in this way delivers what’s needed.”

5. Written reports: for direct and simple sharing

If it’s not broken, don’t fix it. A written report is probably the idea that jumped to the front of your mind when you read the title of this chapter. For many, this may seem like the ‘OG’ of UX reports.

These types of reports often come as a PDF or a word document, making them static, reluctant to change, and resulting in low engagement or re-reads. Delivering a written report via email also means you can’t guarantee your audience is going to read it. On the other hand, written reports can be incredibly detailed, scanable for different stakeholders, and include all kinds of results from visual data to qualitative findings.

For many teams this method still works, especially if you’re trying to communicate findings to a distributed, asynchronous team. Written UX reports enable people to go through things in their own time—and come back to it when they need to.

6. Atomic research nuggets: to eliminate ‘bad research memory’

Deriving from an atom—the smallest unit of matter—atomic UX research nuggets are minute and succinct conclusions from data points. They’re always aligned and tagged with a product direction. Formalized by Tomer Sharon and Daniel Pidcock , it’s described as “the concept of breaking UX research down into its constituent parts”:

Experiments: “We did this…” Facts: “…and we found out this…” Insights: “…which makes us think this…” Conclusions: “…so we’ll do that.”

Atomic research nuggets help to fight ‘bad research memory’—the idea that knowledge gets lost or forgotten amid the depths of a larger report. These nuggets are accessible, usable, and searchable. They can be delivered (or accessed) throughout an entire product build, serving as North Stars for micro goals. Research nuggets can be a firm reminder your team is, or isn’t, taking the right action.

7. Pre-recorded video: for better knowledge retention

People retain 90% of the information they receive via video versus text. There’s no question that, for many, video is a better way of onboarding and remembering information. At the same time, it can be easier to share information via video if your UX researchers aren’t the most confident of writers.

Although pre-recorded video is an easy way to share a UX research report with a team, as with other formats on this list, you’ll need to ensure people actually watch it.

Loom can be a great screen-sharing video recording tool. Some of their features and paid plans will enable you to see who from your team has watched your video, as well as spark conversation and engagement opportunities throughout the video. Alternatively, you can share the video as a watch-along during a synchronous meeting and discuss afterwards, while still sharing the video with those who can’t attend live.

8. Case studies: for sticky storytelling

Case studies aren’t just for winning potential customers. At their very core, case studies are put together to convince someone of something due to a real-life story. This is why they can be great if your UX research report needs to convince a diverse or largely cautious selection of stakeholders.

What’s more, case studies tend to rely on storytelling tactics and a strong narrative to get their point across. They can pull from user personas to further a point and make it more relatable for your design team. Muhammad Ahmad , UX Designer at VentureDive, shares the value presenting reports as case studies holds:

“Case studies show how you think. As a UX Researcher or Designer, how you percieve problems and what framework you use to evaluate them matters a lot. Your case studies are supposed to show just that.”

9. Maze reports: for all-in-one research and reporting

Automate your reporting with Maze. Maze automatically generates a report for each test you run, turning it into an easy-to-navigate dashboard. Add comments to generate conversation, highlight key responses and generate usability scores for your prototype testing .

If you’re working with moderated research, Maze AI can speed up the reporting process with automated sentiment tagging, project naming, and even generating summaries and identifying critical learnings from user interviews . So you can sit back, and let Maze take care of the data processing.

When you’re happy with your report, generate a custom link that you can share with your team, and further internal and external stakeholders.

Using Maze reports will enable you to share:

• Introduction and mission slides
• An analysis of each UX research method: From card sorting to live website testing
• In-depth breakdowns of research data
• Overviews of the report metrics: From misclicks to bounce rates and time-on-screen
• A usability score

These reports will also allow you to download CSV files of your data, and customzie filters and views to bring your stakeholders the numbers they need, fast. Your team will be able to collaborate in a comments section and let AI identify key themes and takeaways if you’re struggling to spot them.

Overall, UX research tools with in-built reporting are a great way to translate and share all of your research into visual data sets that can be digested by the rest of the team in a few clicks.

7 UX research report templates

There are some fantastic research report templates to help get you started on your journey. Here are some of our favorites to help you better present those deliverables, key learnings, and everything in between.

Maze: Usability testing report

Hosted on Pitch, this report template is clear, simple, and follows a lot of the design and framework best practices shared in this chapter.

Access the template here

Aadil Khan: UXR report with examples

A straightforward report template is designed by Aadil Khan , UX Researcher at IBM, who says: “I made this template based on tons of mentoring calls I’ve been in with people looking to land UXR jobs where we discuss how to present UXR case studies during interviews and such. Oftentimes their case studies were too lengthy and lacked some sort of narrative structure to make it easier to present.”

EaTemp: Key findings report

A beautifully-designed template hosted on Figma. Get access to personas, empathy maps, and card sorting. All colors, fonts, and shapes are customizable.

Miro: Research repository template

Build a centralized research hub on Miro. Connect your team in a few clicks and allow them to collaborate with this free template. Note: you’ll need to sign up for a (free) Miro account.

Furquan Ahmad: UX research report template

A sleek and vibrant presentation, this template was created by Furquan Ahmad , Product Designer at Meta, “to help people focus their energy and time on the insights they're providing rather than worry about what the presentation will look like. I'm always shocked at how many people have benefited from the community.”

Estefanía Montaña Buitrago: Atomic UX research canvas

Beautifully designed on FigJam, this canvas by Estefanía Montaña Buitrago , UX Designer at Globant, has been used by over 7,000 people and now comes with several useful remixes too.

Muhammad Ahmad: UX research kit

Muhammad Ahmad , UX Designer at VentureDive, shared this minimalistic template. Here you’ll get 60+ customizable templates in both light and dark modes. There’s a free version, or a (paid) premium version which may be worth the investment for you.

Best practices for writing an effective UX research report

The functionality of your research report will come down to how you write it. Sitting down and being faced with copious amounts of data can make UX reporting feel like a daunting task—here’s some techniques and tips to help you along the way.

Take a leaf from your UX design book with user-friendly copy

No matter the format, you want your UX report to be as accessible and skim-able as possible for your audience. It’s a good idea to mimic some of the same mentalities you would use in UX design.

Gestalt grouping principles are good to consider for UX report writing. Think similarity , proximity , and common-region for grouping relevant information.

Similarly, UI design principles such as the figure-ground and focal point will help direct your readers’ eyes to the most important information first, as well as make for a more accessible read.

Lastly, Gestalt’s continuity principle is a great one to apply to your UX report. Readers naturally follow patterns for easier flows in information, so if you’re including stylistic elements like bolding, italics, asides, indenting, or something else, ensure these run consistently throughout your report.

At the same time, think about the structure, layout, and formatting of your written report. Are you leaving enough negative space for your reader to process information? These are especially important for readers with dyslexia, but will generally lift your readability on the whole:

• Is all of your copy aligned left?
• Is your font choice clear with a good amount of spacing between letters and words?
• Are you bolding important words and sentences rather than underlining them?
• Are you peppering your report with enough headings and subheadings?

Release oxytocin: Follow storytelling tactics

A Forbes article reported that “immersive storytelling releases the empathy-related chemical oxytocin in our brains.” If you’re not familiar with oxytocin, it’s known as a natural ‘feel-good’ chemical, promoting feelings of trust and attachment.

Why else do you think case studies are so effective? They rely on storytelling: they have characters, plots, beginnings, endings, peaks, and pits. User research reports that mimic storytelling threads and tactics are more likely to create sticky data points, as well as hold your readers’ attention throughout. This is why the PAS framework works so well, but whatever format your report takes, bear in mind a story-like structure with a beginning, middle, and end.

Ask your editor to edit your research presentation with the three Cs in mind

Clear , Concise , Compelling . These core principles exist everywhere the written word does, but it can be hard to spot them when editing your own work. Just because something is clear, concise, and compelling for you, doesn’t mean it is for someone else—ask a colleague to read your report (or, better yet—a content editor).

Failing that, if you don’t have access to an editor or are in a time crunch, here are some tools to help you edit your own work.

• Grammarly: Good for catching those little typos and grammatical errors
• Hemingway Editor: Gives a readability score and helps to simplify sentences

Consider your reader, and rethink the jargon

Tailoring your report to meet the needs and knowledge level of each stakeholder is a balancing act. Many will tell you to avoid jargon, acronyms, and technical language at all costs. But, that’s not always the case. Sometimes, using industry jargon is the most direct way of getting your point across, and if you know your reader understands it, go for it.

However, keep in mind that if your report is going to other teams: sales, C-suite, finance, etc, then you may need to find alternative terms that aren’t department-specific—or provide a glossary or acronym dictionary within the report.

Muhammad shares more: “Typically UX folks (or even product folks) are not that well-equipped with research terminologies. So giving them the summary of the research in plain language is the approach that works best for me.”

Wrapping up how to present user research findings

There you have it, a complete guide on how you can write and present your user experience research in a way that everyone can benefit from it.

Remember, be conscious of your audience, your format, and your language. Different stakeholders and team cultures require different reporting styles, it’s up to you to curate the information into a report that delivers the insights you’ve uncovered.

Generate UX reports that have impact

From AI-generated summaries of your user interviews, to usability scores for your prototype tests, automate UX research reporting with Maze.

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How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On June 24, 2024

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the  research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

• Data type required for research
• Research resources
• Participants required for research
• Hypothesis based upon research question(s)
• Data analysis  methodologies
• Variables (Independent, dependent, and confounding)
• The location and timescale for conducting the data
• The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and  interpretation techniques.  A strong research design reflects a strong  dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a  dissertation analyzing different situations or cases will have more than one research design.

For example:

• Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
• Quantitative research is good for the  statistical part of the project, but it may not provide an in-depth understanding of the  topic .
• Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

• Do you have enough time to gather data and complete the write-up?
• Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
• Do you have in-depth knowledge about the  different statistical analysis and data collection techniques to address the research questions  or test the  hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative Vs. Quantitative Data

Also, see; Research methods, design, and analysis .

Need help with a thesis chapter?

• Hire an expert from ResearchProspect today!
• Statistical analysis, research methodology, discussion of the results or conclusion – our experts can help you no matter how complex the requirements are.

Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the  research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your  dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the  correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results  and  conclusion .

Read our guidelines to write a research proposal  if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The  research methodology  or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to  formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

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Not sure how to approach a company for your primary research study? Don’t worry. Here we have some tips for you to successfully gather primary study.

This article is a step-by-step guide to how to write statement of a problem in research. The research problem will be half-solved by defining it correctly.

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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.

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

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, 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 Research Design?

A Plain-Language Explainer (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental .

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

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Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

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15 Comments

Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

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Research Report

A research report is a deliverable that summarizes insights from a user research study. The report can take various forms, such as a written report or a slide deck. This report should reference the research plan that was created before the study was conducted.

A research report should tell a compelling and accurate story about the users. The findings may be shared across an organization, so they should be digestible and actionable. An effective report helps stakeholders make important decisions about the next steps to take in the project or design.

A research report typically contains the following:

• Executive Summary: The executive summary is an overview included at the beginning of the research report that summarizes the key insights and the purpose of the study. The executive summary should be concise and include enough context to stand on its own. This section introduces the report and helps engage the audience.
• Background: The background includes the what and the why of the project. This section should describe the context, discuss what prompted this research, and explain the problem that the team is trying to solve.
• Research Method: This section describes which user research methods were used and why. The number of participants in the study and the demographic or target audience should be included. Additionally, this section covers how participants were recruited, how the study was facilitated, and how the results were analyzed.
• Research Questions: Research questions provide context about the study’s purpose and indicate the main topics that the report will explore. The research questions should come directly from the research plan .
• Findings: Findings summarize what was learned from the research study. This could be accompanied by a quote from a user interview or a graph from a user survey. What are the essential insights that the audience should take away? Findings can be referenced in a research report more than once. For example, they can appear in the executive summary or be paired with recommendations.
• Recommendations: Recommendations are like a call to action. How might the team solve problems that the research uncovered? What could make a service, product, or process better for users? If research shows that users struggled to complete a task, the recommendations could detail how the platform might be improved to make this task easier.
• What’s Next: The “What’s Next?” section explains what the team plans to do after the research is complete. For example, they may create research-backed personas to define characteristics of the target audience or conduct an additional study to gather more data.

Example Research Report

To see a sample report, check out the Example Research Report slide deck, which captures insights from a user interview study.

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Chapter 11: Presenting Your Research

Writing a Research Report in American Psychological Association (APA) Style

Learning Objectives

• Identify the major sections of an APA-style research report and the basic contents of each section.
• Plan and write an effective APA-style research report.

In this section, we look at how to write an APA-style empirical research report , an article that presents the results of one or more new studies. Recall that the standard sections of an empirical research report provide a kind of outline. Here we consider each of these sections in detail, including what information it contains, how that information is formatted and organized, and tips for writing each section. At the end of this section is a sample APA-style research report that illustrates many of these principles.

Sections of a Research Report

Title page and abstract.

An APA-style research report begins with a  title page . The title is centred in the upper half of the page, with each important word capitalized. The title should clearly and concisely (in about 12 words or fewer) communicate the primary variables and research questions. This sometimes requires a main title followed by a subtitle that elaborates on the main title, in which case the main title and subtitle are separated by a colon. Here are some titles from recent issues of professional journals published by the American Psychological Association.

• Sex Differences in Coping Styles and Implications for Depressed Mood
• Effects of Aging and Divided Attention on Memory for Items and Their Contexts
• Computer-Assisted Cognitive Behavioural Therapy for Child Anxiety: Results of a Randomized Clinical Trial
• Virtual Driving and Risk Taking: Do Racing Games Increase Risk-Taking Cognitions, Affect, and Behaviour?

Below the title are the authors’ names and, on the next line, their institutional affiliation—the university or other institution where the authors worked when they conducted the research. As we have already seen, the authors are listed in an order that reflects their contribution to the research. When multiple authors have made equal contributions to the research, they often list their names alphabetically or in a randomly determined order.

In some areas of psychology, the titles of many empirical research reports are informal in a way that is perhaps best described as “cute.” They usually take the form of a play on words or a well-known expression that relates to the topic under study. Here are some examples from recent issues of the Journal Psychological Science .

• “Smells Like Clean Spirit: Nonconscious Effects of Scent on Cognition and Behavior”
• “Time Crawls: The Temporal Resolution of Infants’ Visual Attention”
• “Scent of a Woman: Men’s Testosterone Responses to Olfactory Ovulation Cues”
• “Apocalypse Soon?: Dire Messages Reduce Belief in Global Warming by Contradicting Just-World Beliefs”
• “Serial vs. Parallel Processing: Sometimes They Look Like Tweedledum and Tweedledee but They Can (and Should) Be Distinguished”
• “How Do I Love Thee? Let Me Count the Words: The Social Effects of Expressive Writing”

Individual researchers differ quite a bit in their preference for such titles. Some use them regularly, while others never use them. What might be some of the pros and cons of using cute article titles?

For articles that are being submitted for publication, the title page also includes an author note that lists the authors’ full institutional affiliations, any acknowledgments the authors wish to make to agencies that funded the research or to colleagues who commented on it, and contact information for the authors. For student papers that are not being submitted for publication—including theses—author notes are generally not necessary.

The  abstract  is a summary of the study. It is the second page of the manuscript and is headed with the word  Abstract . The first line is not indented. The abstract presents the research question, a summary of the method, the basic results, and the most important conclusions. Because the abstract is usually limited to about 200 words, it can be a challenge to write a good one.

Introduction

The  introduction  begins on the third page of the manuscript. The heading at the top of this page is the full title of the manuscript, with each important word capitalized as on the title page. The introduction includes three distinct subsections, although these are typically not identified by separate headings. The opening introduces the research question and explains why it is interesting, the literature review discusses relevant previous research, and the closing restates the research question and comments on the method used to answer it.

The Opening

The  opening , which is usually a paragraph or two in length, introduces the research question and explains why it is interesting. To capture the reader’s attention, researcher Daryl Bem recommends starting with general observations about the topic under study, expressed in ordinary language (not technical jargon)—observations that are about people and their behaviour (not about researchers or their research; Bem, 2003 [1] ). Concrete examples are often very useful here. According to Bem, this would be a poor way to begin a research report:

Festinger’s theory of cognitive dissonance received a great deal of attention during the latter part of the 20th century (p. 191)

The following would be much better:

The individual who holds two beliefs that are inconsistent with one another may feel uncomfortable. For example, the person who knows that he or she enjoys smoking but believes it to be unhealthy may experience discomfort arising from the inconsistency or disharmony between these two thoughts or cognitions. This feeling of discomfort was called cognitive dissonance by social psychologist Leon Festinger (1957), who suggested that individuals will be motivated to remove this dissonance in whatever way they can (p. 191).

After capturing the reader’s attention, the opening should go on to introduce the research question and explain why it is interesting. Will the answer fill a gap in the literature? Will it provide a test of an important theory? Does it have practical implications? Giving readers a clear sense of what the research is about and why they should care about it will motivate them to continue reading the literature review—and will help them make sense of it.

Breaking the Rules

Researcher Larry Jacoby reported several studies showing that a word that people see or hear repeatedly can seem more familiar even when they do not recall the repetitions—and that this tendency is especially pronounced among older adults. He opened his article with the following humourous anecdote:

A friend whose mother is suffering symptoms of Alzheimer’s disease (AD) tells the story of taking her mother to visit a nursing home, preliminary to her mother’s moving there. During an orientation meeting at the nursing home, the rules and regulations were explained, one of which regarded the dining room. The dining room was described as similar to a fine restaurant except that tipping was not required. The absence of tipping was a central theme in the orientation lecture, mentioned frequently to emphasize the quality of care along with the advantages of having paid in advance. At the end of the meeting, the friend’s mother was asked whether she had any questions. She replied that she only had one question: “Should I tip?” (Jacoby, 1999, p. 3)

Although both humour and personal anecdotes are generally discouraged in APA-style writing, this example is a highly effective way to start because it both engages the reader and provides an excellent real-world example of the topic under study.

The Literature Review

Immediately after the opening comes the  literature review , which describes relevant previous research on the topic and can be anywhere from several paragraphs to several pages in length. However, the literature review is not simply a list of past studies. Instead, it constitutes a kind of argument for why the research question is worth addressing. By the end of the literature review, readers should be convinced that the research question makes sense and that the present study is a logical next step in the ongoing research process.

Like any effective argument, the literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that demonstrate it, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or it might describe one phenomenon, then describe another phenomenon that seems inconsistent with the first one, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally suggest a way to test whether it does, in fact, apply to that situation.

Looking at the literature review in this way emphasizes a few things. First, it is extremely important to start with an outline of the main points that you want to make, organized in the order that you want to make them. The basic structure of your argument, then, should be apparent from the outline itself. Second, it is important to emphasize the structure of your argument in your writing. One way to do this is to begin the literature review by summarizing your argument even before you begin to make it. “In this article, I will describe two apparently contradictory phenomena, present a new theory that has the potential to resolve the apparent contradiction, and finally present a novel hypothesis to test the theory.” Another way is to open each paragraph with a sentence that summarizes the main point of the paragraph and links it to the preceding points. These opening sentences provide the “transitions” that many beginning researchers have difficulty with. Instead of beginning a paragraph by launching into a description of a previous study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:

Another example of this phenomenon comes from the work of Williams (2004).

Williams (2004) offers one explanation of this phenomenon.

An alternative perspective has been provided by Williams (2004).

We used a method based on the one used by Williams (2004).

Finally, remember that your goal is to construct an argument for why your research question is interesting and worth addressing—not necessarily why your favourite answer to it is correct. In other words, your literature review must be balanced. If you want to emphasize the generality of a phenomenon, then of course you should discuss various studies that have demonstrated it. However, if there are other studies that have failed to demonstrate it, you should discuss them too. Or if you are proposing a new theory, then of course you should discuss findings that are consistent with that theory. However, if there are other findings that are inconsistent with it, again, you should discuss them too. It is acceptable to argue that the  balance  of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in psychology can hope for), but it is not acceptable to  ignore contradictory evidence. Besides, a large part of what makes a research question interesting is uncertainty about its answer.

The Closing

The  closing  of the introduction—typically the final paragraph or two—usually includes two important elements. The first is a clear statement of the main research question or hypothesis. This statement tends to be more formal and precise than in the opening and is often expressed in terms of operational definitions of the key variables. The second is a brief overview of the method and some comment on its appropriateness. Here, for example, is how Darley and Latané (1968) [2] concluded the introduction to their classic article on the bystander effect:

These considerations lead to the hypothesis that the more bystanders to an emergency, the less likely, or the more slowly, any one bystander will intervene to provide aid. To test this proposition it would be necessary to create a situation in which a realistic “emergency” could plausibly occur. Each subject should also be blocked from communicating with others to prevent his getting information about their behaviour during the emergency. Finally, the experimental situation should allow for the assessment of the speed and frequency of the subjects’ reaction to the emergency. The experiment reported below attempted to fulfill these conditions. (p. 378)

Thus the introduction leads smoothly into the next major section of the article—the method section.

The  method section  is where you describe how you conducted your study. An important principle for writing a method section is that it should be clear and detailed enough that other researchers could replicate the study by following your “recipe.” This means that it must describe all the important elements of the study—basic demographic characteristics of the participants, how they were recruited, whether they were randomly assigned, how the variables were manipulated or measured, how counterbalancing was accomplished, and so on. At the same time, it should avoid irrelevant details such as the fact that the study was conducted in Classroom 37B of the Industrial Technology Building or that the questionnaire was double-sided and completed using pencils.

The method section begins immediately after the introduction ends with the heading “Method” (not “Methods”) centred on the page. Immediately after this is the subheading “Participants,” left justified and in italics. The participants subsection indicates how many participants there were, the number of women and men, some indication of their age, other demographics that may be relevant to the study, and how they were recruited, including any incentives given for participation.

After the participants section, the structure can vary a bit. Figure 11.1 shows three common approaches. In the first, the participants section is followed by a design and procedure subsection, which describes the rest of the method. This works well for methods that are relatively simple and can be described adequately in a few paragraphs. In the second approach, the participants section is followed by separate design and procedure subsections. This works well when both the design and the procedure are relatively complicated and each requires multiple paragraphs.

What is the difference between design and procedure? The design of a study is its overall structure. What were the independent and dependent variables? Was the independent variable manipulated, and if so, was it manipulated between or within subjects? How were the variables operationally defined? The procedure is how the study was carried out. It often works well to describe the procedure in terms of what the participants did rather than what the researchers did. For example, the participants gave their informed consent, read a set of instructions, completed a block of four practice trials, completed a block of 20 test trials, completed two questionnaires, and were debriefed and excused.

In the third basic way to organize a method section, the participants subsection is followed by a materials subsection before the design and procedure subsections. This works well when there are complicated materials to describe. This might mean multiple questionnaires, written vignettes that participants read and respond to, perceptual stimuli, and so on. The heading of this subsection can be modified to reflect its content. Instead of “Materials,” it can be “Questionnaires,” “Stimuli,” and so on.

The  results section  is where you present the main results of the study, including the results of the statistical analyses. Although it does not include the raw data—individual participants’ responses or scores—researchers should save their raw data and make them available to other researchers who request them. Several journals now encourage the open sharing of raw data online.

Although there are no standard subsections, it is still important for the results section to be logically organized. Typically it begins with certain preliminary issues. One is whether any participants or responses were excluded from the analyses and why. The rationale for excluding data should be described clearly so that other researchers can decide whether it is appropriate. A second preliminary issue is how multiple responses were combined to produce the primary variables in the analyses. For example, if participants rated the attractiveness of 20 stimulus people, you might have to explain that you began by computing the mean attractiveness rating for each participant. Or if they recalled as many items as they could from study list of 20 words, did you count the number correctly recalled, compute the percentage correctly recalled, or perhaps compute the number correct minus the number incorrect? A third preliminary issue is the reliability of the measures. This is where you would present test-retest correlations, Cronbach’s α, or other statistics to show that the measures are consistent across time and across items. A final preliminary issue is whether the manipulation was successful. This is where you would report the results of any manipulation checks.

The results section should then tackle the primary research questions, one at a time. Again, there should be a clear organization. One approach would be to answer the most general questions and then proceed to answer more specific ones. Another would be to answer the main question first and then to answer secondary ones. Regardless, Bem (2003) [3] suggests the following basic structure for discussing each new result:

• Remind the reader of the research question.
• Give the answer to the research question in words.
• Present the relevant statistics.
• Qualify the answer if necessary.
• Summarize the result.

Notice that only Step 3 necessarily involves numbers. The rest of the steps involve presenting the research question and the answer to it in words. In fact, the basic results should be clear even to a reader who skips over the numbers.

The  discussion  is the last major section of the research report. Discussions usually consist of some combination of the following elements:

• Summary of the research
• Theoretical implications
• Practical implications
• Limitations
• Suggestions for future research

The discussion typically begins with a summary of the study that provides a clear answer to the research question. In a short report with a single study, this might require no more than a sentence. In a longer report with multiple studies, it might require a paragraph or even two. The summary is often followed by a discussion of the theoretical implications of the research. Do the results provide support for any existing theories? If not, how  can  they be explained? Although you do not have to provide a definitive explanation or detailed theory for your results, you at least need to outline one or more possible explanations. In applied research—and often in basic research—there is also some discussion of the practical implications of the research. How can the results be used, and by whom, to accomplish some real-world goal?

The theoretical and practical implications are often followed by a discussion of the study’s limitations. Perhaps there are problems with its internal or external validity. Perhaps the manipulation was not very effective or the measures not very reliable. Perhaps there is some evidence that participants did not fully understand their task or that they were suspicious of the intent of the researchers. Now is the time to discuss these issues and how they might have affected the results. But do not overdo it. All studies have limitations, and most readers will understand that a different sample or different measures might have produced different results. Unless there is good reason to think they  would have, however, there is no reason to mention these routine issues. Instead, pick two or three limitations that seem like they could have influenced the results, explain how they could have influenced the results, and suggest ways to deal with them.

Most discussions end with some suggestions for future research. If the study did not satisfactorily answer the original research question, what will it take to do so? What  new  research questions has the study raised? This part of the discussion, however, is not just a list of new questions. It is a discussion of two or three of the most important unresolved issues. This means identifying and clarifying each question, suggesting some alternative answers, and even suggesting ways they could be studied.

Finally, some researchers are quite good at ending their articles with a sweeping or thought-provoking conclusion. Darley and Latané (1968) [4] , for example, ended their article on the bystander effect by discussing the idea that whether people help others may depend more on the situation than on their personalities. Their final sentence is, “If people understand the situational forces that can make them hesitate to intervene, they may better overcome them” (p. 383). However, this kind of ending can be difficult to pull off. It can sound overreaching or just banal and end up detracting from the overall impact of the article. It is often better simply to end when you have made your final point (although you should avoid ending on a limitation).

The references section begins on a new page with the heading “References” centred at the top of the page. All references cited in the text are then listed in the format presented earlier. They are listed alphabetically by the last name of the first author. If two sources have the same first author, they are listed alphabetically by the last name of the second author. If all the authors are the same, then they are listed chronologically by the year of publication. Everything in the reference list is double-spaced both within and between references.

Appendices, Tables, and Figures

Appendices, tables, and figures come after the references. An  appendix  is appropriate for supplemental material that would interrupt the flow of the research report if it were presented within any of the major sections. An appendix could be used to present lists of stimulus words, questionnaire items, detailed descriptions of special equipment or unusual statistical analyses, or references to the studies that are included in a meta-analysis. Each appendix begins on a new page. If there is only one, the heading is “Appendix,” centred at the top of the page. If there is more than one, the headings are “Appendix A,” “Appendix B,” and so on, and they appear in the order they were first mentioned in the text of the report.

After any appendices come tables and then figures. Tables and figures are both used to present results. Figures can also be used to illustrate theories (e.g., in the form of a flowchart), display stimuli, outline procedures, and present many other kinds of information. Each table and figure appears on its own page. Tables are numbered in the order that they are first mentioned in the text (“Table 1,” “Table 2,” and so on). Figures are numbered the same way (“Figure 1,” “Figure 2,” and so on). A brief explanatory title, with the important words capitalized, appears above each table. Each figure is given a brief explanatory caption, where (aside from proper nouns or names) only the first word of each sentence is capitalized. More details on preparing APA-style tables and figures are presented later in the book.

Sample APA-Style Research Report

Figures 11.2, 11.3, 11.4, and 11.5 show some sample pages from an APA-style empirical research report originally written by undergraduate student Tomoe Suyama at California State University, Fresno. The main purpose of these figures is to illustrate the basic organization and formatting of an APA-style empirical research report, although many high-level and low-level style conventions can be seen here too.

Key Takeaways

• An APA-style empirical research report consists of several standard sections. The main ones are the abstract, introduction, method, results, discussion, and references.
• The introduction consists of an opening that presents the research question, a literature review that describes previous research on the topic, and a closing that restates the research question and comments on the method. The literature review constitutes an argument for why the current study is worth doing.
• The method section describes the method in enough detail that another researcher could replicate the study. At a minimum, it consists of a participants subsection and a design and procedure subsection.
• The results section describes the results in an organized fashion. Each primary result is presented in terms of statistical results but also explained in words.
• The discussion typically summarizes the study, discusses theoretical and practical implications and limitations of the study, and offers suggestions for further research.
• Practice: Look through an issue of a general interest professional journal (e.g.,  Psychological Science ). Read the opening of the first five articles and rate the effectiveness of each one from 1 ( very ineffective ) to 5 ( very effective ). Write a sentence or two explaining each rating.
• Practice: Find a recent article in a professional journal and identify where the opening, literature review, and closing of the introduction begin and end.
• Practice: Find a recent article in a professional journal and highlight in a different colour each of the following elements in the discussion: summary, theoretical implications, practical implications, limitations, and suggestions for future research.

Long Descriptions

Figure 11.1 long description: Table showing three ways of organizing an APA-style method section.

In the simple method, there are two subheadings: “Participants” (which might begin “The participants were…”) and “Design and procedure” (which might begin “There were three conditions…”).

In the typical method, there are three subheadings: “Participants” (“The participants were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”).

In the complex method, there are four subheadings: “Participants” (“The participants were…”), “Materials” (“The stimuli were…”), “Design” (“There were three conditions…”), and “Procedure” (“Participants viewed each stimulus on the computer screen…”). [Return to Figure 11.1]

• Bem, D. J. (2003). Writing the empirical journal article. In J. M. Darley, M. P. Zanna, & H. R. Roediger III (Eds.),  The compleat academic: A practical guide for the beginning social scientist  (2nd ed.). Washington, DC: American Psychological Association. ↵
• Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility.  Journal of Personality and Social Psychology, 4 , 377–383. ↵

A type of research article which describes one or more new empirical studies conducted by the authors.

The page at the beginning of an APA-style research report containing the title of the article, the authors’ names, and their institutional affiliation.

A summary of a research study.

The third page of a manuscript containing the research question, the literature review, and comments about how to answer the research question.

An introduction to the research question and explanation for why this question is interesting.

A description of relevant previous research on the topic being discusses and an argument for why the research is worth addressing.

The end of the introduction, where the research question is reiterated and the method is commented upon.

The section of a research report where the method used to conduct the study is described.

The main results of the study, including the results from statistical analyses, are presented in a research article.

Section of a research report that summarizes the study's results and interprets them by referring back to the study's theoretical background.

Part of a research report which contains supplemental material.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Organizing Your Social Sciences Research Paper

• Types of Research Designs
• Purpose of Guide
• Design Flaws to Avoid
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• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
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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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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

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Research report guide: Definition, types, and tips

Last updated

5 March 2024

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From successful product launches or software releases to planning major business decisions, research reports serve many vital functions. They can summarize evidence and deliver insights and recommendations to save companies time and resources. They can reveal the most value-adding actions a company should take.

However, poorly constructed reports can have the opposite effect! Taking the time to learn established research-reporting rules and approaches will equip you with in-demand skills. You’ll be able to capture and communicate information applicable to numerous situations and industries, adding another string to your resume bow.

• What are research reports?

A research report is a collection of contextual data, gathered through organized research, that provides new insights into a particular challenge (which, for this article, is business-related). Research reports are a time-tested method for distilling large amounts of data into a narrow band of focus.

Their effectiveness often hinges on whether the report provides:

Strong, well-researched evidence

Comprehensive analysis

Well-considered conclusions and recommendations

Though the topic possibilities are endless, an effective research report keeps a laser-like focus on the specific questions or objectives the researcher believes are key to achieving success. Many research reports begin as research proposals, which usually include the need for a report to capture the findings of the study and recommend a course of action.

A description of the research method used, e.g., qualitative, quantitative, or other

Statistical analysis

Causal (or explanatory) research (i.e., research identifying relationships between two variables)

Inductive research, also known as ‘theory-building’

Deductive research, such as that used to test theories

Action research, where the research is actively used to drive change

• Importance of a research report

Research reports can unify and direct a company's focus toward the most appropriate strategic action. Of course, spending resources on a report takes up some of the company's human and financial resources. Choosing when a report is called for is a matter of judgment and experience.

Some development models used heavily in the engineering world, such as Waterfall development, are notorious for over-relying on research reports. With Waterfall development, there is a linear progression through each step of a project, and each stage is precisely documented and reported on before moving to the next.

The pace of the business world is faster than the speed at which your authors can produce and disseminate reports. So how do companies strike the right balance between creating and acting on research reports?

The answer lies, again, in the report's defined objectives. By paring down your most pressing interests and those of your stakeholders, your research and reporting skills will be the lenses that keep your company's priorities in constant focus.

Honing your company's primary objectives can save significant amounts of time and align research and reporting efforts with ever-greater precision.

Some examples of well-designed research objectives are:

Proving whether or not a product or service meets customer expectations

Demonstrating the value of a service, product, or business process to your stakeholders and investors

Improving business decision-making when faced with a lack of time or other constraints

Clarifying the relationship between a critical cause and effect for problematic business processes

Prioritizing the development of a backlog of products or product features

Comparing business or production strategies

Evaluating past decisions and predicting future outcomes

• Features of a research report

Research reports generally require a research design phase, where the report author(s) determine the most important elements the report must contain.

Just as there are various kinds of research, there are many types of reports.

Here are the standard elements of almost any research-reporting format:

Report summary. A broad but comprehensive overview of what readers will learn in the full report. Summaries are usually no more than one or two paragraphs and address all key elements of the report. Think of the key takeaways your primary stakeholders will want to know if they don’t have time to read the full document.

Introduction. Include a brief background of the topic, the type of research, and the research sample. Consider the primary goal of the report, who is most affected, and how far along the company is in meeting its objectives.

Methods. A description of how the researcher carried out data collection, analysis, and final interpretations of the data. Include the reasons for choosing a particular method. The methods section should strike a balance between clearly presenting the approach taken to gather data and discussing how it is designed to achieve the report's objectives.

Data analysis. This section contains interpretations that lead readers through the results relevant to the report's thesis. If there were unexpected results, include here a discussion on why that might be. Charts, calculations, statistics, and other supporting information also belong here (or, if lengthy, as an appendix). This should be the most detailed section of the research report, with references for further study. Present the information in a logical order, whether chronologically or in order of importance to the report's objectives.

Conclusion. This should be written with sound reasoning, often containing useful recommendations. The conclusion must be backed by a continuous thread of logic throughout the report.

• How to write a research paper

With a clear outline and robust pool of research, a research paper can start to write itself, but what's a good way to start a research report?

Research report examples are often the quickest way to gain inspiration for your report. Look for the types of research reports most relevant to your industry and consider which makes the most sense for your data and goals.

The research report outline will help you organize the elements of your report. One of the most time-tested report outlines is the IMRaD structure:

Introduction

...and Discussion

Pay close attention to the most well-established research reporting format in your industry, and consider your tone and language from your audience's perspective. Learn the key terms inside and out; incorrect jargon could easily harm the perceived authority of your research paper.

Along with a foundation in high-quality research and razor-sharp analysis, the most effective research reports will also demonstrate well-developed:

Internal logic

Narrative flow

Conclusions and recommendations

Readability, striking a balance between simple phrasing and technical insight

How to gather research data for your report

The validity of research data is critical. Because the research phase usually occurs well before the writing phase, you normally have plenty of time to vet your data.

However, research reports could involve ongoing research, where report authors (sometimes the researchers themselves) write portions of the report alongside ongoing research.

One such research-report example would be an R&D department that knows its primary stakeholders are eager to learn about a lengthy work in progress and any potentially important outcomes.

However you choose to manage the research and reporting, your data must meet robust quality standards before you can rely on it. Vet any research with the following questions in mind:

Does it use statistically valid analysis methods?

Do the researchers clearly explain their research, analysis, and sampling methods?

Did the researchers provide any caveats or advice on how to interpret their data?

Have you gathered the data yourself or were you in close contact with those who did?

Is the source biased?

Usually, flawed research methods become more apparent the further you get through a research report.

It's perfectly natural for good research to raise new questions, but the reader should have no uncertainty about what the data represents. There should be no doubt about matters such as:

Whether the sampling or analysis methods were based on sound and consistent logic

What the research samples are and where they came from

The accuracy of any statistical functions or equations

Validation of testing and measuring processes

When does a report require design validation?

A robust design validation process is often a gold standard in highly technical research reports. Design validation ensures the objects of a study are measured accurately, which lends more weight to your report and makes it valuable to more specialized industries.

Product development and engineering projects are the most common research-report examples that typically involve a design validation process. Depending on the scope and complexity of your research, you might face additional steps to validate your data and research procedures.

If you’re including design validation in the report (or report proposal), explain and justify your data-collection processes. Good design validation builds greater trust in a research report and lends more weight to its conclusions.

Choosing the right analysis method

Just as the quality of your report depends on properly validated research, a useful conclusion requires the most contextually relevant analysis method. This means comparing different statistical methods and choosing the one that makes the most sense for your research.

Most broadly, research analysis comes down to quantitative or qualitative methods (respectively: measurable by a number vs subjectively qualified values). There are also mixed research methods, which bridge the need for merging hard data with qualified assessments and still reach a cohesive set of conclusions.

Some of the most common analysis methods in research reports include:

Significance testing (aka hypothesis analysis), which compares test and control groups to determine how likely the data was the result of random chance.

Regression analysis , to establish relationships between variables, control for extraneous variables , and support correlation analysis.

Correlation analysis (aka bivariate testing), a method to identify and determine the strength of linear relationships between variables. It’s effective for detecting patterns from complex data, but care must be exercised to not confuse correlation with causation.

With any analysis method, it's important to justify which method you chose in the report. You should also provide estimates of the statistical accuracy (e.g., the p-value or confidence level of quantifiable data) of any data analysis.

This requires a commitment to the report's primary aim. For instance, this may be achieving a certain level of customer satisfaction by analyzing the cause and effect of changes to how service is delivered. Even better, use statistical analysis to calculate which change is most positively correlated with improved levels of customer satisfaction.

• Tips for writing research reports

There's endless good advice for writing effective research reports, and it almost all depends on the subjective aims of the people behind the report. Due to the wide variety of research reports, the best tips will be unique to each author's purpose.

Consider the following research report tips in any order, and take note of the ones most relevant to you:

No matter how in depth or detailed your report might be, provide a well-considered, succinct summary. At the very least, give your readers a quick and effective way to get up to speed.

Pare down your target audience (e.g., other researchers, employees, laypersons, etc.), and adjust your voice for their background knowledge and interest levels

For all but the most open-ended research, clarify your objectives, both for yourself and within the report.

Leverage your team members’ talents to fill in any knowledge gaps you might have. Your team is only as good as the sum of its parts.

Justify why your research proposal’s topic will endure long enough to derive value from the finished report.

Consolidate all research and analysis functions onto a single user-friendly platform. There's no reason to settle for less than developer-grade tools suitable for non-developers.

What's the format of a research report?

The research-reporting format is how the report is structured—a framework the authors use to organize their data, conclusions, arguments, and recommendations. The format heavily determines how the report's outline develops, because the format dictates the overall structure and order of information (based on the report's goals and research objectives).

What's the purpose of a research-report outline?

A good report outline gives form and substance to the report's objectives, presenting the results in a readable, engaging way. For any research-report format, the outline should create momentum along a chain of logic that builds up to a conclusion or interpretation.

What's the difference between a research essay and a research report?

There are several key differences between research reports and essays:

Research report:

Ordered into separate sections

More commercial in nature

Often includes infographics

Heavily descriptive

More self-referential

Usually provides recommendations

Research essay

Does not rely on research report formatting

More academically minded

Normally text-only

Less detailed

Omits discussion of methods

Usually non-prescriptive 

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• Types of Research Designs Compared | Guide & Examples

Types of Research Designs Compared | Guide & Examples

Published on June 20, 2019 by Shona McCombes . Revised on June 22, 2023.

When you start planning a research project, developing research questions and creating a  research design , you will have to make various decisions about the type of research you want to do.

There are many ways to categorize different types of research. The words you use to describe your research depend on your discipline and field. In general, though, the form your research design takes will be shaped by:

• The type of knowledge you aim to produce
• The type of data you will collect and analyze
• The sampling methods , timescale and location of the research

This article takes a look at some common distinctions made between different types of research and outlines the key differences between them.

Table of contents

Types of research aims, types of research data, types of sampling, timescale, and location, other interesting articles.

The first thing to consider is what kind of knowledge your research aims to contribute.

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Professional editors proofread and edit your paper by focusing on:

• Academic style
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The next thing to consider is what type of data you will collect. Each kind of data is associated with a range of specific research methods and procedures.

Finally, you have to consider three closely related questions: how will you select the subjects or participants of the research? When and how often will you collect data from your subjects? And where will the research take place?

Keep in mind that the methods that you choose bring with them different risk factors and types of research bias . Biases aren’t completely avoidable, but can heavily impact the validity and reliability of your findings if left unchecked.

Choosing between all these different research types is part of the process of creating your research design , which determines exactly how your research will be conducted. But the type of research is only the first step: next, you have to make more concrete decisions about your research methods and the details of the study.

Read more about creating a research design

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

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Technical Report Examples

50 professional technical report examples (+format samples).

A technical report example is a written document made by a researcher which contains the details about a project’s results . After creating the technical report, the researcher submits it to the project’s sponsor. Such a report may contain procedures, design criteria, research history, images or illustrations, and other data relevant to the project.

Table of Contents

• 1 Technical Report Examples
• 2 Elements of a technical report example
• 3 Technical Reports Format
• 4 Language, formatting, and design tips for your technical report example
• 5 Technical Report Samples
• 6 Technical Report Templates
• 7 Avoid these common mistakes when making your technical report example

Elements of a technical report example

When you’re tasked to write a technical report example, you must take note of the technical report format because this is very important. The format of such a report makes it unique from other types of written reports because it contains technical information thus, you need to plan it well.

When writing this report, you must understand its structure so that you can achieve your objective. Make sure the document contains the following elements:

• Title page This page must come first in any technical report sample. It contains the title of your report, the date, the details of the institution, and the supervisor. This page is also known as a cover page . Any content you place here isn’t included on your report’s word count. This page is a separate entity in terms of word count so keep this in mind.
• Introduction Here, you highlight the main objectives of your technical report example for the reader. This helps your reader understand why you wrote the report in the first place. You can also include a comment about the report’s flow to give the reader an idea of what to expect.
• Summary For this part of the technical report format, come up with an overview of the entire report including any results or conclusions you’ve made. It’s best to write this part after you’ve finished the rest of the content.
• Details of the experiment Here, include each of the details about the experiment you’ve conducted starting from the materials and equipment you used then the procedure or the steps you took. If you didn’t perform any experiment, then you may omit this part from the technical report format.
• Results and discussions If you performed any kind of experiment for the technical report, you would have to provide all of the results along with an explanation of the results you obtained. This gives the reader a better idea of the results you’ve provided.
• Body This is the most important part of your technical report sample since it contains the “meat” of your document. Here, create subheadings to emphasize the most important points. Also, adding subheadings makes the report easier to reads your readers can use the subheadings to guide them. Also, placing your points in a bulleted or numbered list makes it easier for the readers to understand the points you’re trying to convey. To make it even better, separate the points under their individual subtopics to avoid confusion.
• Conclusions When writing your conclusions, create a summary of all the main points of your report’s body. This serves as a wrap-up of the main content of your document. Also, use words which indicate that you’re concluding the report so the reader is psychologically prepared that the report is now coming to an end.
• Recommendations Here, you can give your suggested solutions for any of the challenges you’ve stated in the body of the report. This is the best place to write your opinions for the readers to know about them.
• References In this section, make a list of all the materials you used throughout your research. If you have quoted any text, list those references here to ensure that your report isn’t considered plagiarism. When writing the references, you’re acknowledging that you’ve obtained your content from certain sources.
• Acknowledgments Make a list of everyone who helped you come up with the report. From the people who proofread your report to those who helped you with the experiments and more, mention them in this section.
• Appendices If you used other materials like diagrams and graphs to emphasize the information in your report, include them in this section. If you didn’t use any such materials or information, you don’t have to include this section.

Technical Reports Format

Language, formatting, and design tips for your technical report example

If you have a message that’s extremely important, you can communicate it right away even when you present it in an unorganized way. Generally though, technical report examples don’t contain any findings which you may consider “groundbreaking.” Still, you must pay attention to the contents of your report along with how you make it.

Technical Report Samples

Here are some tips for you regarding the language, formatting, and design of technical report samples:

• Spelling and grammar Since technical reports are more academic in nature, you must be very careful with your spelling and grammar. If your report contains these mistakes, it might decrease the credibility of the document and your own credibility too. This is why proofreading is an extremely important step for this type of report and for other academic reports you plan to make. Ask more than just one person to proofread your report to ensure that there are no spelling and grammar errors on it.
• Style Technical reports follow a specific style. You must follow a formal style for this type of report so as not to confuse or irritate your readers. Informal writing isn’t appropriate for technical reports so you must keep this in mind. In some cases, you may inject humor in your report. Make sure that the type of humor you use isn’t inappropriate and you include it in a proper manner. For instance, it’s probably not a good idea if the subject of your report is something sensitive or taboo. In such a case, injecting humor might reflect badly on you or on the message you want to convey. Of course, there are times when this works and it’s up to you to determine whether or not to include humor as part of your document’s style. Also, try not to write the content of your document the same way you speak. One reason for this is that you may use a lot of ungrammatical or colloquial expressions when you speak which might confuse your readers. Keep in mind that your readers can’t ask you questions while they read your report, especially if you’re not around. Another reason is that when it comes to writing, you can’t have the same tone or emphasis to explain what you want to say unlike when you’re speaking. For written documents, you the reader only relies on the words on the page so you must choose these carefully.
• Presentation Although the presentation of your document isn’t as important as the technical content, you should still place some emphasis on it. After all, no matter how well-written your document is, if it’s presented poorly, your readers won’t appreciate it. How you present your report gives the first impression to the readers so you must make sure it’s a good one.
• Graphic material Most technical report examples contain more than just text. They typically include images, graphics, charts, and more to illustrate or explain the content more effectively. Here are some tips when it comes to graphic material: Make sure to label everything. Use captions, titles, and other kinds of text to tell the reader about the graphic material you’ve inserted. Think about whether you plan to print your report in color or grayscale. If you choose the latter, make sure that the images you use are either in grayscale too or your readers can still understand them even when printed without colors. Only include relevant graphic material. Adding too many images might make your report look cluttered so choose these elements wisely.

Technical Report Templates

Avoid these common mistakes when making your technical report example

Apart from being very careful when writing the format of your technical report example, there are some common mistakes you must avoid too. These are:

• Using too stock phrases or clichés Although these are very common, you may want to avoid using such phrases because they’re so over-used. When your readers keep encountering these phrases in your report, they might feel annoyed. It’s better to use direct sentences to make the information simpler and easier to comprehend.
• Providing too much data Yes, the technical report should contain a lot of information. But you don’t have to provide data which isn’t directly relevant to the report or the project you’re reporting on. Stick to the facts and only include the important information so your readers don’t get confused.
• Using non-technical content or material Such content may be quite annoying when it’s not related to the subject. But even if the content relates to the subject, including such material may come off as offensive to your readers.
• Using long mathematical equations or computer program listings Although you may understand such information, it’s unlikely that other people will understand this too. Unless you think that such content is extremely essential to your report, avoid adding it.
• Stating how challenging it was to create the report Including such statements isn’t professional. No matter how difficult a time you had, never state this in the report. Again, stick to the facts and only include information that’s relevant to the subject of your report.

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Report Writing Format with Templates and Sample Report

Written by: Orana Velarde

If you’re probably wondering how to write a good report, you’re not alone. Many individuals face difficulties when it comes to report writing, as it requires a specific format and structure that can be confusing to navigate.

With so many types of reports -  sales reports , marketing reports , school reports, social media reports and more, how do you know the best structure and organize your thoughts or data that would positively reflect your work?

It all lies in following the right report writing format. With the right format, you’ll be able to write your report with guidelines and make it easy to read and understand and make it easier for you to write as well.

Just as there are different types of reports, there are also different report formats and ways to deliver them. In this article, we’ll walk you through the best report writing formats, examples of reports, report layouts and templates for report writing.

Here's a short selection of 6 easy-to-edit report templates you can edit, share and download with Visme. View more templates below:

Table of Contents

6 types of reports, the ultimate report writing format, top report writing tips, how to write a report, sample report in standard report writing format, report writing format faqs.

• A report is unlike an essay, blog post or journalistic article. The main idea of a report is to present facts about a specific topic, situation, or event. It should always be in a clear and concise way.
• There are six main types of reports: annual reports, weekly reports, project reports, sales and marketing reports, research reports and academic reports.
• A report writing format includes a title, table of contents, summary, introduction, body, conclusion, recommendations and appendices.
• Top report writing tips include writing a report outline, creating the body of the report before the introduction or conclusion, sticking to facts, and keeping your appendix at a reasonable size.
• Visme offers not only hundreds of pre-made report templates but an initiative online report maker to provide you with everything you need to create high-quality reports for any niche, topic or industry.

There are six main types of reports you might encounter based on your goal or niche. In this section we’ll highlight and showcase what these reports are along with reports writing samples, each populated with a similar reporting writing format to what we'll cover further in this article.

1. Annual Reports

The first type of report we'll cover is an annual report . This type of company report format typically rounds up a business's year of progress and performance to let supervisors and team members know what they've accomplished.

It can include anything from website analytics to sales profits, depending on who the report is meant for.

2. Weekly Reports

One report that is helpful to provide your team is a weekly report based on your progress in various projects and goals. This can be a simple one-pager, or a more in-depth report with specific updates.

3. Project Reports

Keep clients and team members up-to-date on the status of various projects you're working on by providing them with a project report. This can include a timeline of your report progress and the deadline for each segment to keep everyone on the same page.

4. Sales/Marketing Reports

It's essential to keep your team updated on how your sales and/or marketing strategies are going. Put together graphs showing profit margins, increases in engagement and more.

These types of reports are also a great way to determine whether your strategies are working or if they need some tweaking in the future.

5. Research Report

Sometimes if you need to do some in-depth research, the best way to present that information is with a research report. Whether it's scientific findings, data and statistics from a study, etc., a research report is a great way to share your results.

For the visuals in your research report, Visme offers millions of free stock photos . But if you can’t find what you need, or are looking for something out of the box, try the Visme AI image generator . Prompt the AI tool to quickly create an image that matches your research, your brand and your report.

6. Academic Report

An academic report is one created for a class, often in a graduate or undergraduate university. This report format follows a formal writing style and dives into a topic related to the student's academic studies.

For more report examples you can learn from, check out our guide on Report Examples With Sample Templates .

Now we're getting to the good part — the ultimate report writing format. While this may vary based on the data and information you pull, it provides enough leeway for you to follow standard report formats.

Keep in mind that good report writing depends on first writing a report outline to start organizing the content in the best way possible.

A standard report format goes a little something like this:

• Title: A clear and concise report title.
• Table of Contents: A page dedicated to the contents of your report.
• Summary: An overview of your entire report — you'll need to wait until you've completed the full report to write this section.
• Introduction: Introduce your report topic and what readers will find throughout the pages.
• Body: The longest section of your report — compile all of your information and use data visualization to help present it.
• Conclusion: Different from the summary, this concludes the report body and summarizes all of your findings.
• Recommendations: A set of recommended goals or steps to complete with the information provided in this report.
• Appendices: A list of your sources used to compile the information in your report.

Each of these eight elements ensures that you leave no stone unturned and that your reader knows exactly what they're learning in your report and how you gathered this information.

Your next step is to get started with an outline. At each point of the outline, use one or two sentences to describe what will go in there. It doesn’t need to say much, just an idea for you to follow later. Input some design ideas for the overall design and report layout as well.

For example, in the Table of Contents section, simply add that you want it to only cover one page or slide, make a note if you’d like to add the pages for only the main sections or maybe also the subsections. 

In the Appendices section, list all the links to the sources you used and add on as you do more research. Every source you reference in your report must be listed here.

The most important part of your outline is the Body section. In there, create an internal outline of sections and subsections that you can follow later when writing.

After you’ve drafted the outline, it’s time to put together all of the content into the report. The outline we provided above is the only report writing format you’ll ever need. You can add sections if needed but don’t take any away.

Let’s take a look at every section in detail. 

Create your own Report with this easy-to-edit template! Edit and Download

The title of your report should be clear in its wording. It must say exactly what the report is about. Remember that this isn’t a novel. Include a subtitle if necessary, making sure the font size of each subtitle is smaller than the title.

In terms of design , your title can be designed as an inviting cover page. There needs to be a clear hierarchy in how the title looks.

On your title or cover page , be sure to include the following:

• Report title
• Report subtitle (if necessary)
• Author of the report
• Who the report is meant for
• Date the report was written

If you’re having trouble coming up with an interesting title or report content, you can get some help from the Visme AI Writer . Describe your report in the text prompt and ask the AI to write a few optional titles. If the first results aren’t to your liking, ask it to do some edits until you have just what you need.

Always leave the Table of Contents page until the end. After all, you can’t write a table of contents if you don’t know all of your page numbers yet. 

However, if your Body outline already has each of your section and subsection titles defined, you can add those to the contents and leave the numbering for later.

Having a Table of Content pages makes it easy for your readers to find the information they're most interested in quickly and easily, improving overall readability. So you absolutely do not want to skip this step.

Likewise, the summary (also known as the abstract) of the report is best done after you’ve finished writing the report. You can draft a summary at the beginning to help guide your work, but you’ll definitely want to revisit it at the end. When you do, try using different paraphrasing techniques to ensure that you're not using repetitive phrases already present throughout the report.

A summary is a blurb of the entire report . It must include the purpose, the process and a snippet of the resolution. This should be no longer than a single paragraph or two.

Alternatively, if your report is data-heavy, the summary can also be a detail report where you share detailed data. Plus, you can add a hyperlink to further data analysis regarding what you’re reporting about.

Introduction

In the introduction, state what the report is about and why it has been created. Depending on the length of your report, the introduction format could range from one single paragraph to an entire page long.

For example, one paragraph is enough for a social media report introduction while an entire page would be more suitable for an annual report .

Take this time to introduce why your topic is so important, especially if it's a research report. You need to focus on why your readers should care about what you have uncovered.

The body of your report is where all the information is put together and will be the longest section of your report. This will likely span several (anywhere from 5-50) pages. Follow your initial outline to maintain consistent flow in the content creation. Write the body content as sections and subsections.

Furthermore, use bullet points and data visualization as visual cues . These will help your audience to better understand the content of your report. 

Check out this video from Visme for some tips on visualizing all that data!

Close your report with a well-crafted conclusion . Formulate it as a brief summary of what was covered within the report, and be sure to include a mention to the recommendations section and the resources in the appendix.

This section should never bring new information to the table — instead, it should simply summarize all of the findings you've already mentioned into one concise final section.

Recommendations

Craft the recommendations section as a set of actionable steps with smart goals associated along with possible solutions. This section is irrelevant for school reports or book reports, but is essential for business reports or corporate settings. 

This is the section where you list all your sources if it’s a research report. You should also add any links that are relevant to the report — or previous reports about the same topic. 

You could even link an interactive version of the report you just created with Visme. Visme allows you to create interactive and animated documents that can be published to the web with a single click, offering a new dimension to your report.

A good rule of thumb when creating your appendices is to only add information that is relevant to the report or that you referenced when writing your report. Use reference annotations inside the report to link to the content in the appendix.

The report content used in this sample report design can be found here .

Following a report writing format is only a portion of the report writing process. When it comes to the content being placed in that context, it needs to be executed in a professional manner that will not only inform your reader but engage them from start to finish as well.

Here are some writing tips and best practices you should follow to complete your report in style.

Looking to create a stand-out visual report?

• Choose from dozens of professionally designed templates
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• Customize anything to fit your brand image and content needs

Start With the Body of the Report

It's helpful to write the body of the report before the introduction or conclusion so you have a comprehensive overview of what key points should be covered in each section. This rule applies whether you're writing the report independently or as a team.

For the body of your report, you can assign specific sections to your team members and then appoint someone to write the conclusion and intro once it's complete.

Visme provides a space for team collaboration where you and your team members can work on your report simultaneously, adding comments, real-time updates and more. This feature helps to ensure everyone contributes and each section of your report is completed and well-rounded.

Use Visuals with Purpose

Don’t simply add visuals for the sake of adding them. Instead, by adding data visualization, you can condense complex information, pinpoint relationships and showcase values and risk. Not to mention a single chart can save you from adding unnecessary text to your report. Give each visual a strong purpose in your report.

Next to data visualization, you should also be mindful of what images you choose to include in your report, whether they’re used as a backdrop or illustration of the topic at hand. You can dive into Visme’s extensive library of royalty-free images, upload your own or create your own with Visme’s AI-powered Image Generator .

Tap into the infinite possibilities of AI image generation right inside your Visme editor. Available inside any project, old or new, just type in your prompts and generate creative and unique visuals for your report.

Write a Well Crafted Report

To ensure your report holds credibility, it must be error-free with proper spelling, grammar and tone. You should only use acronyms or jargon that are associated with your industry or profession, only if needed.

Try to use simple language and avoid adding unnecessary fluff. Lastly, before you send off your report, be sure to review it or ask for a colleague's opinion to ensure everything is in place.

You can send your report as a shareable link for a quick review or invite your colleague directly into your Visme project to decide if they can view, edit or comment on it. Make updates and share changes in real-time to streamline a faster editing process and have your report polished and ready to share with your audience.

Keep Your Appendix Short

Avoid creating a large appendix, as it can be intimidating or burdensome for the reader. It’s best only to add information or sources relevant to the report’s main points. One way to implement this tip is to review your appendix only after your report’s been completed, then do an extensive review to see what needs to stay or be removed until you're satisfied with the size of your appendix.

Use a Grammar Checker

If it’s accessible, ask an editor or writer to review your article. You can also use tools like Hemmingway, ProWritingAid or Grammarly . Even your best KPIs and ROIs won’t save you from bad grammar.

Writing a report may seem challenging, but anyone can do it with a proper plan, the right tools and some practice. You can sign up for Visme's AI Report Writer and follow these simple steps to write your own report.

Step 1: Define Your Objective

Before you put pen to paper, identify your reasons for writing the report. What do you want to accomplish with it? What is the purpose of your research, and why will it be important to others?

You might need to create a monthly , weekly , or annual report . Or, it could be a business report, including sales, marketing or social media reports .

No matter what type of report you are writing, the objective will guide you through the rest of the process.

Also, consider your target audience who will be reading it. For example, if you are writing a sales repor t for your team, it might be important to include data that shows their performance compared to the previous month, like the example below.

If you are writing a project status report like this, you must focus on showing the project's performance over a period of time.

In either case, your objective will help you determine what information is essential in your report and how much should be included.

Step 2: Conduct Research

Start by gathering relevant data and information from various sources, such as books, articles, interviews and online resources. Also, you can find data from your company's files, sheets, CRM or sales software and any other source you can.

As you explore different perspectives and evidence, you'll better understand the topic and be equipped to present a comprehensive analysis.

While researching, take notes and keep track of your sources for easy referencing later. In-depth research lays a solid foundation for a credible and insightful report.

Step 3: Prepare an Outline

Creating an outline provides a structured framework that guides your writing and keeps you focused. Start with the main headings like introduction, body and conclusion. Under each, add subheadings of key points or arguments you will cover.

An outline organizes your thoughts and lets you see where information fits best, ensuring a logical flow of ideas in your report. This planning tool ultimately makes the writing process easier and more efficient.

Step 4: Write the First Draft

After conducting research and preparing an outline, it's time to write your first draft. Start by stating your purpose in the introduction. Expand on your main points and provide necessary information and arguments in the body section.

Lastly, summarize and conclude your ideas. Don't focus on perfection in this stage; just get your thoughts down. It might look rough, but that's okay. This draft is your starting point, where you'll improve in the next revision and editing stages.

You can use Visme's AI writer to simplify the report writing process. It can help you prepare structured outlines, generate compelling report content and proofread text to ensure it's error-free. Just explain what you want to generate, and the AI writer will do the rest.

Step 5: Revise and Edit

This is one of the most important steps in this whole process. It involves reviewing the structure, flow and content of your report. Check your arguments, their logical presentation and if your evidence supports the claims.

Also, focus on editing the report by checking language, spelling, punctuation, style and formatting. You can use grammar checker tools like Grammarly and Hemmingway editor.

The more time you spend editing your report, the more clearly it conveys your message.

Step 6: Share the Report

Once your report is complete and you are satisfied with the results, it’s time to share it with your audience. You may need to share your report in various file formats and channels.

If you use Visme to write your report, you can download and share your report in many different ways:

• Download your report in various formats, including PDF, JPG, PNG and HTLM5.
• Publish it on social media or share it via email using a shareable link generated in the editor.
• Generate a code snippet in Visme to embed it anywhere online.

Click through the image below to use this customizable template to create your report. It follows the standard report writing format so you won’t get confused or miss a section.

Do you still have questions about good report writing and the best report writing formats? These FAQs will help.

What Are the Five Steps in Report Writing?

Writing a report effectively is best done by following a format and a set of guidelines. These are the five steps to follow to create a good report.

1. Understand your report’s purpose: Begin by having a clear understanding of the report's intent.

Whether it's an annual summary, weekly update, or research findings, knowing your report's purpose is crucial for effective writing. Compile and write the content with the purpose in mind as if it were a problem to be solved.

2. Follow the Right Report Writing Format: Adhere to a structured format, including a clear title, table of contents, summary, introduction, body, conclusion, recommendations, and appendices. This ensures clarity and coherence. Follow the format suggestions in this article to start off on the right foot.

3. Plan Your Writing: Create an outline to organize your thoughts and prioritize the body of the report. Stick to factual information, providing accuracy and reliability throughout. Be as detailed as possible in the outline; this will help build the report effectively.

4. Choose the Right Report Template: Utilize templates tailored to your report type, whether it's annual, weekly, project-related, sales/marketing, research, or academic. Templates streamline formatting and enhance professionalism. Visme has hundreds of report templates to choose from. Browse the gallery to find the perfect one.

5. Keep Your Audience in Mind: Tailor your report to meet your audience's needs. Whether it's supervisors, team members, clients, or peers, consider what information is most relevant and valuable to them. Make it easy for them to skim the report with clear headlines, titles and data visualizations.

How Do You Format a Report Nicely?

Formatting a report nicely involves attention to detail and adherence to specific guidelines. Here are some key characteristics that will ensure your report looks polished and professional:

1. Consistent Font and Size: Use a readable font like Arial or Verdana, and maintain consistency in font size throughout the report. Typically, a 12-point font is standard for most reports.

2. Clear Headings and Subheadings: Employ clear and descriptive headings and subheadings to organize your content. Use a consistent hierarchy, i.e., Heading 1, Heading 2, body text, etc, for a neat structure.

3. Adequate Margins: Ensure proper margins on all sides of the page (usually 1 inch or 2.54 cm) to provide white space and enhance readability.

4. Line Spacing: Use 1.5 or double spacing for the main text to prevent overcrowding and improve readability. Single spacing is acceptable for footnotes, references, and captions.

5. Page Numbers: Include page numbers, typically in the header or footer, to aid navigation. Ensure they are placed consistently and formatted appropriately.

6. Bullet Points and Numbering : When listing items or creating outlines, use bullet points or numbering for clarity. Maintain uniformity in style and indentation.

7. Tables and Figures: Format tables and figures consistently by providing clear labels and captions. Ensure they are properly aligned within the text.

8. Alignment: Align text and paragraphs consistently. Use left-justified text for most reports, as it's the easiest to read. Justify text only when necessary.

9. Page Breaks: Insert page breaks as needed to avoid awkward page transitions within sections or paragraphs.

10. Use of Color: If your report allows for color, use it sparingly and consistently. Ensure that text and background colors provide sufficient contrast for readability.

11. Proofreading and Editing: Always proofread and edit your report for grammar, spelling, and formatting errors. Consistency in formatting is essential for a polished look

12. Citations and References: If your report includes citations and references, follow a specific citation style guide (e.g., APA, MLA, Chicago) consistently throughout the document.

13. Review for Accessibility: Consider accessibility guidelines, such as providing alternative text for images and using accessible color choices, to ensure all readers can access your report.

What Are the Five Qualities of a Good Report?

A well-crafted report possesses five key qualities that make it effective and valuable. Here they are:

1. Clarity and Conciseness: A good report is clear and concise. It presents information in a straightforward manner, avoiding unnecessary jargon or overly complex language. Readers should easily understand the content without confusion.

2. Relevance: Every piece of information in a good report is relevant to the report's purpose and objectives. Irrelevant or extraneous details are omitted, ensuring that the report focuses on what truly matters.

3. Structure and Organization: Reports are structured logically, with a clear beginning, middle, and end. They typically include sections like an introduction, body, and conclusion, ensuring a logical flow of information. Headings and subheadings help organize content effectively.

4. Accuracy and Reliability: Accurate and reliable data is a hallmark of a good report. Information presented should be based on thorough research, sound methodology, and credible sources. Any data or facts should be verifiable.

5. Actionable Recommendations: In many cases, a good report includes actionable recommendations or insights. After presenting the data and analysis, the report should offer practical suggestions or solutions that readers can implement or consider for decision-making.

Over to You

Hopefully, this post has helped you to better understand the best way to put together a report using a standard report format and layout.  Following a standard report writing format is just what you need to create engaging, memorable reports . Follow the tips above and you’ll never make a boring report again.

Just how following a report writing format will help you create a better report, a Visme subscription will help you create a full suite of visual content.

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Sample applications and documents.

As you gain experience writing your own applications and progress reports, examples of how others presented their ideas can help. NIH also provides attachment format examples, sample language, and more resources below.

Sample Grant Applications

With the gracious permission of successful investigators, some NIH institutes have provided samples of funded applications, summary statements, and more. When referencing these examples, it is important to remember:

• The best way to present your science may differ substantially from the approaches shown here. Seek feedback on your draft application from mentors and others.
• Samples are not available for all grant programs. Because many programs have common elements, the available samples can still be helpful as a demonstration of effective ways to present information.

National Institute of Allergy and Infectious Diseases (NIAID)

• Sample Applications and Summary Statements (R01, R03, R15, R21, R33, SBIR, STTR, K, F, G11, and U01)
• NIAID Sample Forms, Plans, Letters, Emails, and More

National Cancer Institute (NCI)

• Behavioral Research Grant Applications (R01, R03, R21)
• Cancer Epidemiology Grant Applications (R01, R03, R21, R37)
• Implementation Science Grant Applications (R01, R21, R37) 
• Healthcare Delivery Research Grant Applications (R01, R03, R21, R50)

National Human Genome Research Institute (NHGRI)

• Ethical, Legal, and Social Implications (ELSI) Applications and Summary Statements (K99/R00, K01, R01, R03, and R21)
• NHGRI Sample Consent Forms

National Institute on Aging (NIA)

• K99/R00: Pathway to Independence Awards Sample Applications and summary statements
• NIA Small Business Sample Applications (SBIR and STTR Phase 1, Phase 2, and Fast-Track)

National Institute on Deafness and Other Communication Disorders (NIDCD)

• Research Project Grants (R01) Sample Applications and Summary Statements
• Early Career Research (ECR) R21 Sample Applications and Summary Statements
• Exploratory/Developmental Research Grant (R21) Sample Applications and Summary Statements

NIH Formats, Sample Language, and Other Examples

NIH provides additional examples of completed forms, templates, plans, and other sample language for reference. Your chosen approach must follow the instructions in your funding opportunity and the How to Apply – Application Guide .

Formats and Templates

• Application Format Pages for biographical sketches, other support, fellowship and training data tables, Data Management and Sharing (DMS) plans, reference letters, additional senior/key persons, additional performance sites, and more 
• Animal Documents for animal welfare assurances, checklist, study proposal, and more from the Office of Laboratory Animal Welfare (OLAW) 

Sample Plans

• Authentication of Key Biological and/or Chemical Resources Plans
• Data Management and Sharing (DMS) Plans
• Model Organism Sharing Plans
• Multiple Principal Investigators, Project Leadership Plans

Other Examples

• Allowable Appendix Materials
• Application Titles, Abstracts, and Public Health Relevance Statements: Communicating Research Intent and Value
• Biosketches
• Informed Consent for Certificates of Confidentiality
• Informed Consent for Secondary and Genomic Research
• Other Support
• Scientific Rigor
• Person Months FAQ on Calculations
• Project Outcomes for Research Performance Progress Report (RPPR)

Looking for application forms?

• For a preview, go to Annotated Form Sets .
• To access fillable forms for your opportunity, you must use one of the Submission Options .

Check online guidance and direct your questions to staff in your organization's sponsored programs office. If you still need assistance, find NIH contacts at Need Help?