research plan and design

How to write a research plan: Step-by-step guide

Last updated

30 January 2024

Reviewed by

Today’s businesses and institutions rely on data and analytics to inform their product and service decisions. These metrics influence how organizations stay competitive and inspire innovation. However, gathering data and insights requires carefully constructed research, and every research project needs a roadmap. This is where a research plan comes into play.

There’s general research planning; then there’s an official, well-executed research plan. Whatever data-driven research project you’re gearing up for, the research plan will be your framework for execution. The plan should also be detailed and thorough, with a diligent set of criteria to formulate your research efforts. Not including these key elements in your plan can be just as harmful as having no plan at all.

Read this step-by-step guide for writing a detailed research plan that can apply to any project, whether it’s scientific, educational, or business-related.

• What is a research plan?

A research plan is a documented overview of a project in its entirety, from end to end. It details the research efforts, participants, and methods needed, along with any anticipated results. It also outlines the project’s goals and mission, creating layers of steps to achieve those goals within a specified timeline.

Without a research plan, you and your team are flying blind, potentially wasting time and resources to pursue research without structured guidance.

The principal investigator, or PI, is responsible for facilitating the research oversight. They will create the research plan and inform team members and stakeholders of every detail relating to the project. The PI will also use the research plan to inform decision-making throughout the project.

• Why do you need a research plan?

Create a research plan before starting any official research to maximize every effort in pursuing and collecting the research data. Crucially, the plan will model the activities needed at each phase of the research project.

Like any roadmap, a research plan serves as a valuable tool providing direction for those involved in the project—both internally and externally. It will keep you and your immediate team organized and task-focused while also providing necessary definitions and timelines so you can execute your project initiatives with full understanding and transparency.

External stakeholders appreciate a working research plan because it’s a great communication tool, documenting progress and changing dynamics as they arise. Any participants of your planned research sessions will be informed about the purpose of your study, while the exercises will be based on the key messaging outlined in the official plan.

Here are some of the benefits of creating a research plan document for every project:

Project organization and structure

Well-informed participants

All stakeholders and teams align in support of the project

Clearly defined project definitions and purposes

Distractions are eliminated, prioritizing task focus

Timely management of individual task schedules and roles

Costly reworks are avoided

• What should a research plan include?

The different aspects of your research plan will depend on the nature of the project. However, most official research plan documents will include the core elements below. Each aims to define the problem statement, devising an official plan for seeking a solution.

Specific project goals and individual objectives

Ideal strategies or methods for reaching those goals

Required resources

Descriptions of the target audience, sample sizes, demographics, and scopes

Key performance indicators (KPIs)

Project background

Research and testing support

Preliminary studies and progress reporting mechanisms

Cost estimates and change order processes

Depending on the research project’s size and scope, your research plan could be brief—perhaps only a few pages of documented plans. Alternatively, it could be a fully comprehensive report. Either way, it’s an essential first step in dictating your project’s facilitation in the most efficient and effective way.

• How to write a research plan for your project

When you start writing your research plan, aim to be detailed about each step, requirement, and idea. The more time you spend curating your research plan, the more precise your research execution efforts will be.

Account for every potential scenario, and be sure to address each and every aspect of the research.

Consider following this flow to develop a great research plan for your project:

Define your project’s purpose

Start by defining your project’s purpose. Identify what your project aims to accomplish and what you are researching. Remember to use clear language.

Thinking about the project’s purpose will help you set realistic goals and inform how you divide tasks and assign responsibilities. These individual tasks will be your stepping stones to reach your overarching goal.

Additionally, you’ll want to identify the specific problem, the usability metrics needed, and the intended solutions.

Know the following three things about your project’s purpose before you outline anything else:

What you’re doing

Why you’re doing it

What you expect from it

Identify individual objectives

With your overarching project objectives in place, you can identify any individual goals or steps needed to reach those objectives. Break them down into phases or steps. You can work backward from the project goal and identify every process required to facilitate it.

Be mindful to identify each unique task so that you can assign responsibilities to various team members. At this point in your research plan development, you’ll also want to assign priority to those smaller, more manageable steps and phases that require more immediate or dedicated attention.

Select research methods

Research methods might include any of the following:

User interviews: this is a qualitative research method where researchers engage with participants in one-on-one or group conversations. The aim is to gather insights into their experiences, preferences, and opinions to uncover patterns, trends, and data.

Field studies: this approach allows for a contextual understanding of behaviors, interactions, and processes in real-world settings. It involves the researcher immersing themselves in the field, conducting observations, interviews, or experiments to gather in-depth insights.

Card sorting: participants categorize information by sorting content cards into groups based on their perceived similarities. You might use this process to gain insights into participants’ mental models and preferences when navigating or organizing information on websites, apps, or other systems.

Focus groups: use organized discussions among select groups of participants to provide relevant views and experiences about a particular topic.

Diary studies: ask participants to record their experiences, thoughts, and activities in a diary over a specified period. This method provides a deeper understanding of user experiences, uncovers patterns, and identifies areas for improvement.

Five-second testing: participants are shown a design, such as a web page or interface, for just five seconds. They then answer questions about their initial impressions and recall, allowing you to evaluate the design’s effectiveness.

Surveys: get feedback from participant groups with structured surveys. You can use online forms, telephone interviews, or paper questionnaires to reveal trends, patterns, and correlations.

Tree testing: tree testing involves researching web assets through the lens of findability and navigability. Participants are given a textual representation of the site’s hierarchy (the “tree”) and asked to locate specific information or complete tasks by selecting paths.

Usability testing: ask participants to interact with a product, website, or application to evaluate its ease of use. This method enables you to uncover areas for improvement in digital key feature functionality by observing participants using the product.

Live website testing: research and collect analytics that outlines the design, usability, and performance efficiencies of a website in real time.

There are no limits to the number of research methods you could use within your project. Just make sure your research methods help you determine the following:

What do you plan to do with the research findings?

What decisions will this research inform? How can your stakeholders leverage the research data and results?

Recruit participants and allocate tasks

Next, identify the participants needed to complete the research and the resources required to complete the tasks. Different people will be proficient at different tasks, and having a task allocation plan will allow everything to run smoothly.

Prepare a thorough project summary

Every well-designed research plan will feature a project summary. This official summary will guide your research alongside its communications or messaging. You’ll use the summary while recruiting participants and during stakeholder meetings. It can also be useful when conducting field studies.

Ensure this summary includes all the elements of your research project. Separate the steps into an easily explainable piece of text that includes the following:

An introduction: the message you’ll deliver to participants about the interview, pre-planned questioning, and testing tasks.

Interview questions: prepare questions you intend to ask participants as part of your research study, guiding the sessions from start to finish.

An exit message: draft messaging your teams will use to conclude testing or survey sessions. These should include the next steps and express gratitude for the participant’s time.

Create a realistic timeline

While your project might already have a deadline or a results timeline in place, you’ll need to consider the time needed to execute it effectively.

Realistically outline the time needed to properly execute each supporting phase of research and implementation. And, as you evaluate the necessary schedules, be sure to include additional time for achieving each milestone in case any changes or unexpected delays arise.

For this part of your research plan, you might find it helpful to create visuals to ensure your research team and stakeholders fully understand the information.

Determine how to present your results

A research plan must also describe how you intend to present your results. Depending on the nature of your project and its goals, you might dedicate one team member (the PI) or assume responsibility for communicating the findings yourself.

In this part of the research plan, you’ll articulate how you’ll share the results. Detail any materials you’ll use, such as:

Presentations and slides

A project report booklet

A project findings pamphlet

Documents with key takeaways and statistics

Graphic visuals to support your findings

• Format your research plan

As you create your research plan, you can enjoy a little creative freedom. A plan can assume many forms, so format it how you see fit. Determine the best layout based on your specific project, intended communications, and the preferences of your teams and stakeholders.

Find format inspiration among the following layouts:

Written outlines

Narrative storytelling

Visual mapping

Graphic timelines

Remember, the research plan format you choose will be subject to change and adaptation as your research and findings unfold. However, your final format should ideally outline questions, problems, opportunities, and expectations.

• Research plan example

Imagine you’ve been tasked with finding out how to get more customers to order takeout from an online food delivery platform. The goal is to improve satisfaction and retain existing customers. You set out to discover why more people aren’t ordering and what it is they do want to order or experience. 

You identify the need for a research project that helps you understand what drives customer loyalty. But before you jump in and start calling past customers, you need to develop a research plan—the roadmap that provides focus, clarity, and realistic details to the project.

Here’s an example outline of a research plan you might put together:

Project title

Project members involved in the research plan

Purpose of the project (provide a summary of the research plan’s intent)

Objective 1 (provide a short description for each objective)

Objective 2

Objective 3

Proposed timeline

Audience (detail the group you want to research, such as customers or non-customers)

Budget (how much you think it might cost to do the research)

Risk factors/contingencies (any potential risk factors that may impact the project’s success)

Remember, your research plan doesn’t have to reinvent the wheel—it just needs to fit your project’s unique needs and aims.

Customizing a research plan template

Some companies offer research plan templates to help get you started. However, it may make more sense to develop your own customized plan template. Be sure to include the core elements of a great research plan with your template layout, including the following:

Introductions to participants and stakeholders

Background problems and needs statement

Significance, ethics, and purpose

Research methods, questions, and designs

Preliminary beliefs and expectations

Implications and intended outcomes

Realistic timelines for each phase

Conclusion and presentations

How many pages should a research plan be?

Generally, a research plan can vary in length between 500 to 1,500 words. This is roughly three pages of content. More substantial projects will be 2,000 to 3,500 words, taking up four to seven pages of planning documents.

What is the difference between a research plan and a research proposal?

A research plan is a roadmap to success for research teams. A research proposal, on the other hand, is a dissertation aimed at convincing or earning the support of others. Both are relevant in creating a guide to follow to complete a project goal.

What are the seven steps to developing a research plan?

While each research project is different, it’s best to follow these seven general steps to create your research plan:

Defining the problem

Identifying goals

Choosing research methods

Recruiting participants

Preparing the brief or summary

Establishing task timelines

Defining how you will present the findings

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Research Design 101

Everything You Need To Get Started (With Examples)

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

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

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 . 

Descriptive Research Design

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).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

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Experimental Research Design

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.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

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 Research 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 .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

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.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

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 .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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10 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

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

how can I put this blog as my reference(APA style) in bibliography part?

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What is UX Research: The Ultimate Guide for UX Researchers

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How to create a UX research plan (examples, tactics, and templates)

Conducting UX research without a plan is like moving to another country without knowing the language—confusing and exhausting.

To avoid wasting time and resources, it’s crucial to set achievable research goals and work on developing a research plan that’s clear, comprehensive, and aligned with your overarching business goals and research strategy.

A good UX research plan sets out the parameters for your research, and guides how you’ll gather insights to inform product development. In this chapter, we share a step-by-step guide to creating a research plan, including templates and tactics for you to try. You’ll also find expert tips from Paige Bennett, Senior User Research Manager at Affirm, and Sinéad Davis Cochrane, Research Manager at Workday.

What is a UX research plan?

A UX research plan—not to be confused with a UX research strategy —is a plan to guide individual user experience (UX) research projects.

It's a living document that includes a detailed explanation of tactics, methods, timeline, scope, and task owners. It should be co-created and shared with key stakeholders, so everyone is familiar with the project plan, and product teams can meet strategic goals.

While the UX research plan should be based on strategy, it’s not the same thing. A strategy is a high-level document that contains goals, budget, vision, and expectations. Meanwhile, a plan is a detailed document explaining how the team will achieve those strategic goals. In short, a strategy is a guide, but a plan is what drives action.

What are the benefits of using a UX research plan?

Conducting research without goals and parameters is aimless. A UX research plan is beneficial for your product, user, and business—by building a plan for conducting UX research, you can:

Streamline processes and add structure

Work toward specific, measurable goals, align and engage stakeholders, save time by avoiding rework.

The structure of a research plan allows you to set timelines, expectations, and task owners, so everyone on your team is aligned and empowered to make decisions. Since there’s no second guessing what to do next or which methods to use, you’ll find your process becomes simpler and more efficient. It’s also worth standardizing your process to turn your plan into a template that you can reuse for future projects.

When you set research goals based on strategy, you’ll find it easier to track your team’s progress and keep the project in scope, on time, and on budget. With a solid, strategy-based UX research plan you can also track metrics at different stages of the project and adjust future tactics to get better research findings.

“It’s important to make sure your stakeholders are on the same page with regards to scope, timeline, and goals before you start," explains Paige Bennett, Senior User Research Manager at Affirm. That's because, when stakeholders are aligned, they're much more likely to sign off on product changes that result from UX research.

A written plan is a collaborative way to involve stakeholders in your research and turn them into active participants rather than passive observers. As they get involved, they'll make useful contributions and get a better understanding of your goals.

A UX research plan helps you save time and money quite simply because it’s easier and less expensive to make design or prototype changes than it is to fix usability issues once the product is coded or fully launched. Additionally, having a plan gives your team direction, which means they won’t be conducting research and talking to users without motive, and you’ll be making better use of your resources. What’s more, when everyone is aligned on goals, they’re empowered to make informed decisions instead of waiting for their managers’ approval.

What should a UX research plan include?

In French cuisine, the concept of mise en place—putting in place—allows chefs to plan and set up their workspace with all the required ingredients before cooking. Think of your research plan like this—laying out the key steps you need to go through during research, to help you run a successful and more efficient study.

Here’s what you should include in a UX research plan:

• A brief reminder of the strategy and goals
• An outline of the research objectives
• The purpose of the plan and studies
• A short description of the target audience, sample size, scope, and demographics
• A detailed list of expectations including deliverables, timings, and type of results
• An overview of the test methods and a short explanation of why you chose them
• The test set up or guidelines to outline everything that needs to happen before the study: scenarios, screening questions, and duration of pilot tests
• Your test scripts, questions to ask, or samples to follow
• When and how you’ll present the results
• Cost estimations or requests to go over budget

Collect all UX research findings in one place

Use Maze to run quantitative and qualitative research, influence product design, and shape user-centered products.

How to create a UX research plan

Now we’ve talked through why you need a research plan, let’s get into the how. Here’s a short step-by-step guide on how to write a research plan that will drive results.

• Define the problem statement
• Get stakeholders’ buy-in
• Identify your objectives
• Choose the right research method
• Recruit participants
• Prepare the brief
• Establish the timeline
• Decide how you’ll present your findings

1. Define the problem statement

One of the most important purposes of a research plan is to identify what you’re trying to achieve with the research, and clarify the problem statement. For Paige Bennett , Senior User Research Manager at Affirm, this process begins by sitting together with stakeholders and looking at the problem space.

“We do an exercise called FOG, which stands for ‘Fact, Observation, Guess’, to identify large gaps in knowledge,” says Paige. “Evaluating what you know illuminates questions you still have, which then serves as the foundation of the UX research project.”

You can use different techniques to identify the problem statement, such as stakeholder interviews, team sessions, or analysis of customer feedback. The problem statement should explain what the project is about—helping to define the research scope with clear deliverables and objectives.

2. Identify your objectives

Research objectives need to align with the UX strategy and broader business goals, but you also need to define specific targets to achieve within the research itself—whether that’s understanding a specific problem, or measuring usability metrics . So, before you get into a room with your users and customers, “Think about the research objectives: what you’re doing, why you’re doing it, and what you expect from the UX research process ,” explains Sinéad Davis Cochrane , Research Manager at Workday.

Examples of research objectives might be:

• Learn at what times users interact with your product
• Understand why users return (or not) to your website/app
• Discover what competitor products your users are using
• Uncover any pain points or challenges users find when navigating with your product
• Gauge user interest in and prioritize potential new features

A valuable purpose of setting objectives is ensuring your project doesn't suffer from scope creep. This can happen when stakeholders see your research as an opportunity to ask any question. As a researcher , Sinéad believes your objectives can guide the type of research questions you ask and give your research more focus. Otherwise, anything and everything becomes a research question—which will confuse your findings and be overwhelming to manage.

Sinéad shares a list of questions you should ask yourself and the research team to help set objectives:

• What are you going to do with this information?
• What decisions is it going to inform?
• How are you going to leverage these insights?

Another useful exercise to help identify research objectives is by asking questions that help you get to the core of a problem. Ask these types of questions before starting the planning process:

• Who are the users you’re designing this for?
• What problems and needs do they have?
• What are the pain points of using the product?
• Why are they not using a product like yours?

3. Get stakeholders buy-in

It’s good practice to involve stakeholders at early stages of plan creation to get everyone on board. Sharing your UX research plan with relevant stakeholders means you can gather context, adjust based on comments, and gauge what’s truly important to them. When you present the research plan to key stakeholders, remember to align on the scope of research, and how and when you’ll get back to them with results.

Stakeholders usually have a unique vision of the product, and it’s crucial that you’re able to capture it early on—this doesn’t mean saying yes to everything, but listening to their ideas and having a conversation. Seeing the UX research plan as a living document makes it much easier to edit based on team comments. Plus, the more you listen to other ideas, the easier it will be to evangelize research and get stakeholders to see the value behind it.

I expect my stakeholders to be participants, and I outline how I expect that to happen. That includes observing interviews, participating in synthesis exercises, or co-presenting research recommendations.

Paige Bennett , Senior User Research Manager at Affirm

4. Choose the right research method

Choose between the different UX research methods to capture different insights from users.

To define the research methods you’ll use, circle back to your research objectives, what stage of the product development process you’re in, and the constraints, resources, and timeline of the project. It’s good research practice to use a mix of different methods to get a more complete perspective of users’ struggles.

For example, if you’re at the start of the design process, a generative research method such as user interviews or field studies will help you generate new insights about the target audience. Or, if you need to evaluate how a new design performs with users, you can run usability tests to get actionable feedback.

It’s also good practice to mix methods that drive quantitative and qualitative results so you can understand context, and catch the user sentiment behind a metric. For instance, if during a remote usability test, you hear a user go ‘Ugh! Where’s the sign up button?’ you’ll get a broader perspective than if you were just reviewing the number of clicks on the same test task.

Examples of UX research methods to consider include:

• Five-second testing
• User interviews
• Field studies
• Card sorting
• Tree testing
• Focus groups
• Usability testing
• Diary studies
• Live website testing

Check out our top UX research templates . Use them as a shortcut to get started on your research.

5. Determine how to recruit participants

Every research plan should include information about the participants you need for your study, and how you’ll recruit them. To identify your perfect candidate, revisit your goals and the questions that need answering, then build a target user persona including key demographics and use cases. Consider the resources you have available already, by asking yourself:

• Do you have a user base you can tap into to collect data?
• Do you need to hire external participants?
• What’s your budget to recruit users?
• How many users do you need to interact with?

When selecting participants, make sure they represent all your target personas. If different types of people will be using a certain product, you need to make sure that the people you research represent these personas. This means not just being inclusive in your recruitment, but considering secondary personas—the people who may not be your target user base, but interact with your product incidentally.

You should also consider recruiting research participants to test the product on different devices. Paige explains: “If prior research has shown that behavior differs greatly between those who use a product on their phone versus their tablet, I need to better understand those differences—so I’m going to make sure my participants include people who have used a product on both devices.”

During this step, make sure to include information about the required number of participants, how you’ll get them to participate, and how much time you need per user. The main ways to recruit testers are:

• Using an online participant recruitment tool like Maze’s panel
• Putting out physical or digital adverts in spaces that are relevant to your product and user
• Reaching out to existing users
• Using participants from previous research
• Recruiting directly from your website or app with a tool like In-Product Prompts

5.1. Determine how you’ll pay them

You should always reward your test participants for their time and insights. Not only because it’s the right thing to do, but also because if they have an incentive they’re more likely to give you complete and insightful answers. If you’re hosting the studies in person, you’ll also need to cover your participants' travel expenses and secure a research space. Running remote moderated or unmoderated research is often considered to be less expensive and faster to complete.

If you’re testing an international audience, remember to check your proposed payment system works worldwide—this might be an Amazon gift card or prepaid Visa cards.

6. Prepare the brief

The next component of a research plan is to create a brief or guide for your research sessions. The kind of brief you need will vary depending on your research method, but for moderated methods like user interviews, field studies, or focus groups, you’ll need a detailed guide and script. The brief is there to remind you which questions to ask and keep the sessions on track.

Your script should cover:

• Introduction: A short message you’ll say to participants before the session begins. This works as a starting point for conversations and helps set the tone for the meeting. If you’re testing without a moderator, you should also include an introductory message to explain what the research is about and the type of answers they should give (in terms of length and specificity).
• Interview questions: Include your list of questions you’ll ask participants during the sessions. These could be examples to help guide the interviews, specific pre-planned questions, or test tasks you’ll ask participants to perform during unmoderated sessions.
• Outro message: Outline what you'll say at the end of the session, including the next steps, asking participants if they are open to future research, and thanking them for their time. This can be a form you share at the end of asynchronous sessions.

It’s crucial you remember to ask participants for their consent. You should do this at the beginning of the test by asking if they’re okay with you recording the session. Use this space to lay out any compensation agreements as well. Then, ask again at the end of the session if they agree with you keeping the results and using the data for research purposes. If possible, explain exactly what you’ll do with their data. Double check and get your legal team’s sign-off on these forms.

7. Establish the timeline

Next in your plan, estimate how long the research project will take and when you should expect to review the findings. Even if not exact, determining an approximate timeline (e.g., two-three weeks) will enable you to manage stakeholders’ expectations of the process and results.

Many people believe UX research is a lengthy process, so they skip it. When you set up a timeline and get stakeholders aligned with it, you can debunk assumptions and put stakeholders’ minds at ease. Plus, if you’re using a product discovery tool like Maze, you can get answers to your tests within days.

8. Decide how you’ll present your findings

When it comes to sharing your findings with your team, presentation matters. You need to make a clear presentation and demonstrate how user insights will influence design and development. If you’ve conducted UX research in the past, share data that proves how implementing user insights has improved product adoption.

Examples of ways you can present your results include:

• A physical or digital PDF report with key statistics and takeaways
• An interactive online report of the individual research questions and their results
• A presentation explaining the results and your findings
• A digital whiteboard, like Miro, to display the results

In your plan, mention how you’ll share insights with the product team. For example, if you’re using Maze, you can start by emailing everyone the ready-to-share report and setting up a meeting with the team to identify how to bring those insights to life. This is key, because your research should be the guiding light for new products or updates, if you want to keep development user-centric. Taking care over how you present your findings will impact whether they’re taken seriously and implemented by other stakeholders.

Templates for UX research

Whether you’re creating the plan yourself or are delegating this responsibility to your team, here are six research templates to get started:

• UX research plan template : This editable Miro research project plan example helps you brainstorm user and business-facing problems, objectives, and questions
• UX research brief : You need a clear brief before you conduct UX research—Milanote shares a template that will help you simplify the writing process
• User testing synthesis : Trello put together a sample board to organize user testing notes—you can use this as a guide, but change the titles to fit your UX research purposes
• Usability testing templates : At Maze, we’ve created multiple templates for conducting specific UX research methods—this list will help you create different remote usability tests
• Information architecture (IA) tests template : The way you organize the information in your website or app can improve or damage the user experience—use this template to run IA tests easily
• Feedback survey templates : Ask users anything through a survey, and use these templates to get creative and simplify creation

Everything you need to know about UX research plans

We all know that a robust plan is essential for conducting successful UX research. But, in case you want a quick refresher on what we’ve covered:

• Using a UX research strategy as a starting point will make your plan more likely to succeed
• Determine your research objectives before anything else
• Use a mix of qualitative and quantitative research methods
• Come up with clear personas so you can recruit and test a group of individuals that’s representative of your real end users
• Involve stakeholders from the beginning to get buy-in
• Be vocal about timelines, budget, and expected research findings
• Use the insights to power your product decisions and wow your users; building the solution they genuinely want and need

UX research can happen at any stage of the development lifecycle. When you build products with and for users, you need to include them continuously at various stages of the process.

It’s helpful to explore the need for continuous discovery in your UX research plan and look for a tool like Maze that simplifies the process for you. We’ll cover more about the different research methods and UX research tools in the upcoming chapters—ready to go?

Elevate your UX research workflow

Discover how Maze can streamline and operationalize your research plans to drive real product innovation while saving on costs.

Frequently asked questions

What’s the difference between a UX research plan and a UX research strategy?

The difference between a UX research plan and a UX research strategy is that they cover different levels of scope and detail. A UX research plan is a document that guides individual user experience (UX) research projects. UX research plans are shared documents that everyone on the product team can and should be familiar with. The UX research strategy, on the other hand, outlines the high-level goals, expectations, and demographics of the discovery.

What should you include in a user research plan?

Here’s what to include in a user research plan:

• Problem statement
• Research objectives
• Research methods
• Participants' demographics
• Recruitment plan
• User research brief
• Expected timeline
• How to present findings

How do you write a research plan for UX design?

Creating a research plan for user experience (UX) requires a clear problem statement and objectives, choosing the right research method, recruiting participants and briefing them, and establishing a timeline for your project. You'll also need to plan how you'll analyze and present your findings.

Generative Research: Definition, Methods, and Examples

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Research Design | Step-by-Step Guide with Examples

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

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

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

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

Table of contents

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

• Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

Prevent plagiarism, run a free check.

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

Types of quantitative research designs

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

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

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

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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

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

Operationalisation

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

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

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

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

Reliability and validity

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

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

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

Sampling procedures

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

That means making decisions about things like:

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

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

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

Data management

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

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

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

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

Quantitative data analysis

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

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

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

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

Using inferential statistics , you can:

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

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

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

Qualitative data analysis

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

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

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

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

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

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

Operationalisation means turning abstract conceptual ideas into measurable observations.

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

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

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

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

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FLEET LIBRARY | Research Guides

Rhode island school of design, create a research plan: research plan.

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A research plan is a framework that shows how you intend to approach your topic. The plan can take many forms: a written outline, a narrative, a visual/concept map or timeline. It's a document that will change and develop as you conduct your research. Components of a research plan

1. Research conceptualization - introduces your research question

2. Research methodology - describes your approach to the research question

3. Literature review, critical evaluation and synthesis - systematic approach to locating,

    reviewing and evaluating the work (text, exhibitions, critiques, etc) relating to your topic

4. Communication - geared toward an intended audience, shows evidence of your inquiry

Research conceptualization refers to the ability to identify specific research questions, problems or opportunities that are worthy of inquiry. Research conceptualization also includes the skills and discipline that go beyond the initial moment of conception, and which enable the researcher to formulate and develop an idea into something researchable ( Newbury 373).

Research methodology refers to the knowledge and skills required to select and apply appropriate methods to carry through the research project ( Newbury 374) .

Method describes a single mode of proceeding; methodology describes the overall process.

Method - a way of doing anything especially according to a defined and regular plan; a mode of procedure in any activity

Methodology - the study of the direction and implications of empirical research, or the sustainability of techniques employed in it; a method or body of methods used in a particular field of study or activity *Browse a list of research methodology books  or this guide on Art & Design Research

Literature Review, critical evaluation & synthesis

A literature review is a systematic approach to locating, reviewing, and evaluating the published work and work in progress of scholars, researchers, and practitioners on a given topic.

Critical evaluation and synthesis is the ability to handle (or process) existing sources. It includes knowledge of the sources of literature and contextual research field within which the person is working ( Newbury 373).

Literature reviews are done for many reasons and situations. Here's a short list:

Sources to consult while conducting a literature review:

Online catalogs of local, regional, national, and special libraries

meta-catalogs such as worldcat , Art Discovery Group , europeana , world digital library or RIBA

subject-specific online article databases (such as the Avery Index, JSTOR, Project Muse)

digital institutional repositories such as Digital Commons @RISD ; see Registry of Open Access Repositories

Open Access Resources recommended by RISD Research LIbrarians

works cited in scholarly books and articles

print bibliographies

the internet-locate major nonprofit, research institutes, museum, university, and government websites

search google scholar to locate grey literature & referenced citations

trade and scholarly publishers

fellow scholars and peers

Communication                              

Communication refers to the ability to

• structure a coherent line of inquiry
• communicate your findings to your intended audience
• make skilled use of visual material to express ideas for presentations, writing, and the creation of exhibitions ( Newbury 374)

Research plan framework: Newbury, Darren. "Research Training in the Creative Arts and Design." The Routledge Companion to Research in the Arts . Ed. Michael Biggs and Henrik Karlsson. New York: Routledge, 2010. 368-87. Print.

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• Types of Research Designs
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

• Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
• Review and synthesize previously published literature associated with the research problem,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
• Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
• Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE : Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

• This is a collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
• When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
• Action research studies often have direct and obvious relevance to improving practice and advocating for change.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

• It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
• Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
• Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA:  Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
• Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the  actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In  The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
• Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations in practice.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter the behaviors or responses of participants.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings, and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumptions.
• Development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

• Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
• The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
• Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
• Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
• Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

• A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
• Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
• The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
• Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field  [i.e., the act of triangulating the data].
• Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
• The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is often no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

• Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research data to explain fluctuations in the results.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

• Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
• A well-reasoned and well-documented justification for identification and selection of the studies;
• Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
• Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
• Justification of the techniques used to evaluate the studies.
• Can be an effective strategy for determining gaps in the literature.
• Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
• Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
• Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
• Can be used to generate new hypotheses or highlight research problems for future studies.
• Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
• A large sample size can yield reliable, but not necessarily valid, results.
• A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
• Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

• Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
• Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
• A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
• The strengths of one method can be used to overcome the inherent weaknesses of another method.
• Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
• May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
• Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
• A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
• Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
• Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
• Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
• Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
• Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
• The researcher is able to collect in-depth information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation research designs account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• This is a useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
• The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

• A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
• The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
• They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
• Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
• The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
• Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
• The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
• Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
• Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
• The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
• The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods .  David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research."  Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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Illustration by James Round

How to plan a research project

Whether for a paper or a thesis, define your question, review the work of others – and leave yourself open to discovery.

by Brooke Harrington   + BIO

is professor of sociology at Dartmouth College in New Hampshire. Her research has won international awards both for scholarly quality and impact on public life. She has published dozens of articles and three books, most recently the bestseller Capital without Borders (2016), now translated into five languages.

Edited by Sam Haselby

Need to know

‘When curiosity turns to serious matters, it’s called research.’ – From Aphorisms (1880-1905) by Marie von Ebner-Eschenbach

Planning research projects is a time-honoured intellectual exercise: one that requires both creativity and sharp analytical skills. The purpose of this Guide is to make the process systematic and easy to understand. While there is a great deal of freedom and discovery involved – from the topics you choose, to the data and methods you apply – there are also some norms and constraints that obtain, no matter what your academic level or field of study. For those in high school through to doctoral students, and from art history to archaeology, research planning involves broadly similar steps, including: formulating a question, developing an argument or predictions based on previous research, then selecting the information needed to answer your question.

Some of this might sound self-evident but, as you’ll find, research requires a different way of approaching and using information than most of us are accustomed to in everyday life. That is why I include orienting yourself to knowledge-creation as an initial step in the process. This is a crucial and underappreciated phase in education, akin to making the transition from salaried employment to entrepreneurship: suddenly, you’re on your own, and that requires a new way of thinking about your work.

What follows is a distillation of what I’ve learned about this process over 27 years as a professional social scientist. It reflects the skills that my own professors imparted in the sociology doctoral programme at Harvard, as well as what I learned later on as a research supervisor for Ivy League PhD and MA students, and then as the author of award-winning scholarly books and articles. It can be adapted to the demands of both short projects (such as course term papers) and long ones, such as a thesis.

At its simplest, research planning involves the four distinct steps outlined below: orienting yourself to knowledge-creation; defining your research question; reviewing previous research on your question; and then choosing relevant data to formulate your own answers. Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won’t delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis. Instead, the fourth part of this section will outline some basic strategies you could use in planning a data-selection and analysis process appropriate to your research question.

Step 1: Orient yourself

Planning and conducting research requires you to make a transition, from thinking like a consumer of information to thinking like a producer of information. That sounds simple, but it’s actually a complex task. As a practical matter, this means putting aside the mindset of a student, which treats knowledge as something created by other people. As students, we are often passive receivers of knowledge: asked to do a specified set of readings, then graded on how well we reproduce what we’ve read.

Researchers, however, must take on an active role as knowledge producers . Doing research requires more of you than reading and absorbing what other people have written: you have to engage in a dialogue with it. That includes arguing with previous knowledge and perhaps trying to show that ideas we have accepted as given are actually wrong or incomplete. For example, rather than simply taking in the claims of an author you read, you’ll need to draw out the implications of those claims: if what the author is saying is true, what else does that suggest must be true? What predictions could you make based on the author’s claims?

In other words, rather than treating a reading as a source of truth – even if it comes from a revered source, such as Plato or Marie Curie – this orientation step asks you to treat the claims you read as provisional and subject to interrogation. That is one of the great pieces of wisdom that science and philosophy can teach us: that the biggest advances in human understanding have been made not by being correct about trivial things, but by being wrong in an interesting way . For example, Albert Einstein was wrong about quantum mechanics, but his arguments about it with his fellow physicist Niels Bohr have led to some of the biggest breakthroughs in science, even a century later.

Step 2: Define your research question

Students often give this step cursory attention, but experienced researchers know that formulating a good question is sometimes the most difficult part of the research planning process. That is because the precise language of the question frames the rest of the project. It’s therefore important to pose the question carefully, in a way that’s both possible to answer and likely to yield interesting results. Of course, you must choose a question that interests you, but that’s only the beginning of what’s likely to be an iterative process: most researchers come back to this step repeatedly, modifying their questions in light of previous research, resource limitations and other considerations.

Researchers face limits in terms of time and money. They, like everyone else, have to pose research questions that they can plausibly answer given the constraints they face. For example, it would be inadvisable to frame a project around the question ‘What are the roots of the Arab-Israeli conflict?’ if you have only a week to develop an answer and no background on that topic. That’s not to limit your imagination: you can come up with any question you’d like. But it typically does require some creativity to frame a question that you can answer well – that is, by investigating thoroughly and providing new insights – within the limits you face.

In addition to being interesting to you, and feasible within your resource constraints, the third and most important characteristic of a ‘good’ research topic is whether it allows you to create new knowledge. It might turn out that your question has already been asked and answered to your satisfaction: if so, you’ll find out in the next step of this process. On the other hand, you might come up with a research question that hasn’t been addressed previously. Before you get too excited about breaking uncharted ground, consider this: a lot of potentially researchable questions haven’t been studied for good reason ; they might have answers that are trivial or of very limited interest. This could include questions such as ‘Why does the area of a circle equal π r²?’ or ‘Did winter conditions affect Napoleon’s plans to invade Russia?’ Of course, you might be able to make the argument that a seemingly trivial question is actually vitally important, but you must be prepared to back that up with convincing evidence. The exercise in the ‘Learn More’ section below will help you think through some of these issues.

Finally, scholarly research questions must in some way lead to new and distinctive insights. For example, lots of people have studied gender roles in sports teams; what can you ask that hasn’t been asked before? Reinventing the wheel is the number-one no-no in this endeavour. That’s why the next step is so important: reviewing previous research on your topic. Depending on what you find in that step, you might need to revise your research question; iterating between your question and the existing literature is a normal process. But don’t worry: it doesn’t go on forever. In fact, the iterations taper off – and your research question stabilises – as you develop a firm grasp of the current state of knowledge on your topic.

Step 3: Review previous research

In academic research, from articles to books, it’s common to find a section called a ‘literature review’. The purpose of that section is to describe the state of the art in knowledge on the research question that a project has posed. It demonstrates that researchers have thoroughly and systematically reviewed the relevant findings of previous studies on their topic, and that they have something novel to contribute.

Your own research project should include something like this, even if it’s a high-school term paper. In the research planning process, you’ll want to list at least half a dozen bullet points stating the major findings on your topic by other people. In relation to those findings, you should be able to specify where your project could provide new and necessary insights. There are two basic rhetorical positions one can take in framing the novelty-plus-importance argument required of academic research:

• Position 1 requires you to build on or extend a set of existing ideas; that means saying something like: ‘Person A has argued that X is true about gender; this implies Y, which has not yet been tested. My project will test Y, and if I find evidence to support it, that will change the way we understand gender.’
• Position 2 is to argue that there is a gap in existing knowledge, either because previous research has reached conflicting conclusions or has failed to consider something important. For example, one could say that research on middle schoolers and gender has been limited by being conducted primarily in coeducational environments, and that findings might differ dramatically if research were conducted in more schools where the student body was all-male or all-female.

Your overall goal in this step of the process is to show that your research will be part of a larger conversation: that is, how your project flows from what’s already known, and how it advances, extends or challenges that existing body of knowledge. That will be the contribution of your project, and it constitutes the motivation for your research.

Two things are worth mentioning about your search for sources of relevant previous research. First, you needn’t look only at studies on your precise topic. For example, if you want to study gender-identity formation in schools, you shouldn’t restrict yourself to studies of schools; the empirical setting (schools) is secondary to the larger social process that interests you (how people form gender identity). That process occurs in many different settings, so cast a wide net. Second, be sure to use legitimate sources – meaning publications that have been through some sort of vetting process, whether that involves peer review (as with academic journal articles you might find via Google Scholar) or editorial review (as you’d find in well-known mass media publications, such as The Economist or The Washington Post ). What you’ll want to avoid is using unvetted sources such as personal blogs or Wikipedia. Why? Because anybody can write anything in those forums, and there is no way to know – unless you’re already an expert – if the claims you find there are accurate. Often, they’re not.

Step 4: Choose your data and methods

Whatever your research question is, eventually you’ll need to consider which data source and analytical strategy are most likely to provide the answers you’re seeking. One starting point is to consider whether your question would be best addressed by qualitative data (such as interviews, observations or historical records), quantitative data (such as surveys or census records) or some combination of both. Your ideas about data sources will, in turn, suggest options for analytical methods.

You might need to collect your own data, or you might find everything you need readily available in an existing dataset someone else has created. A great place to start is with a research librarian: university libraries always have them and, at public universities, those librarians can work with the public, including people who aren’t affiliated with the university. If you don’t happen to have a public university and its library close at hand, an ordinary public library can still be a good place to start: the librarians are often well versed in accessing data sources that might be relevant to your study, such as the census, or historical archives, or the Survey of Consumer Finances.

Because your task at this point is to plan research, rather than conduct it, the purpose of this step is not to commit you irrevocably to a course of action. Instead, your goal here is to think through a feasible approach to answering your research question. You’ll need to find out, for example, whether the data you want exist; if not, do you have a realistic chance of gathering the data yourself, or would it be better to modify your research question? In terms of analysis, would your strategy require you to apply statistical methods? If so, do you have those skills? If not, do you have time to learn them, or money to hire a research assistant to run the analysis for you?

Please be aware that qualitative methods in particular are not the casual undertaking they might appear to be. Many people make the mistake of thinking that only quantitative data and methods are scientific and systematic, while qualitative methods are just a fancy way of saying: ‘I talked to some people, read some old newspapers, and drew my own conclusions.’ Nothing could be further from the truth. In the final section of this guide, you’ll find some links to resources that will provide more insight on standards and procedures governing qualitative research, but suffice it to say: there are rules about what constitutes legitimate evidence and valid analytical procedure for qualitative data, just as there are for quantitative data.

Circle back and consider revising your initial plans

As you work through these four steps in planning your project, it’s perfectly normal to circle back and revise. Research planning is rarely a linear process. It’s also common for new and unexpected avenues to suggest themselves. As the sociologist Thorstein Veblen wrote in 1908 : ‘The outcome of any serious research can only be to make two questions grow where only one grew before.’ That’s as true of research planning as it is of a completed project. Try to enjoy the horizons that open up for you in this process, rather than becoming overwhelmed; the four steps, along with the two exercises that follow, will help you focus your plan and make it manageable.

Key points – How to plan a research project

• Planning a research project is essential no matter your academic level or field of study. There is no one ‘best’ way to design research, but there are certain guidelines that can be helpfully applied across disciplines.
• Orient yourself to knowledge-creation. Make the shift from being a consumer of information to being a producer of information.
• Define your research question. Your question frames the rest of your project, sets the scope, and determines the kinds of answers you can find.
• Review previous research on your question. Survey the existing body of relevant knowledge to ensure that your research will be part of a larger conversation.
• Choose your data and methods. For instance, will you be collecting qualitative data, via interviews, or numerical data, via surveys?
• Circle back and consider revising your initial plans. Expect your research question in particular to undergo multiple rounds of refinement as you learn more about your topic.

Good research questions tend to beget more questions. This can be frustrating for those who want to get down to business right away. Try to make room for the unexpected: this is usually how knowledge advances. Many of the most significant discoveries in human history have been made by people who were looking for something else entirely. There are ways to structure your research planning process without over-constraining yourself; the two exercises below are a start, and you can find further methods in the Links and Books section.

The following exercise provides a structured process for advancing your research project planning. After completing it, you’ll be able to do the following:

• describe clearly and concisely the question you’ve chosen to study
• summarise the state of the art in knowledge about the question, and where your project could contribute new insight
• identify the best strategy for gathering and analysing relevant data

In other words, the following provides a systematic means to establish the building blocks of your research project.

Exercise 1: Definition of research question and sources

This exercise prompts you to select and clarify your general interest area, develop a research question, and investigate sources of information. The annotated bibliography will also help you refine your research question so that you can begin the second assignment, a description of the phenomenon you wish to study.

Jot down a few bullet points in response to these two questions, with the understanding that you’ll probably go back and modify your answers as you begin reading other studies relevant to your topic:

• What will be the general topic of your paper?
• What will be the specific topic of your paper?

b) Research question(s)

Use the following guidelines to frame a research question – or questions – that will drive your analysis. As with Part 1 above, you’ll probably find it necessary to change or refine your research question(s) as you complete future assignments.

• Your question should be phrased so that it can’t be answered with a simple ‘yes’ or ‘no’.
• Your question should have more than one plausible answer.
• Your question should draw relationships between two or more concepts; framing the question in terms of How? or What? often works better than asking Why ?

c) Annotated bibliography

Most or all of your background information should come from two sources: scholarly books and journals, or reputable mass media sources. You might be able to access journal articles electronically through your library, using search engines such as JSTOR and Google Scholar. This can save you a great deal of time compared with going to the library in person to search periodicals. General news sources, such as those accessible through LexisNexis, are acceptable, but should be cited sparingly, since they don’t carry the same level of credibility as scholarly sources. As discussed above, unvetted sources such as blogs and Wikipedia should be avoided, because the quality of the information they provide is unreliable and often misleading.

To create an annotated bibliography, provide the following information for at least 10 sources relevant to your specific topic, using the format suggested below.

Name of author(s):

Publication date:

Title of book, chapter, or article:

If a chapter or article, title of journal or book where they appear:

Brief description of this work, including main findings and methods ( c 75 words):

Summary of how this work contributes to your project ( c 75 words):

Brief description of the implications of this work ( c 25 words):

Identify any gap or controversy in knowledge this work points up, and how your project could address those problems ( c 50 words):

Exercise 2: Towards an analysis

Develop a short statement ( c 250 words) about the kind of data that would be useful to address your research question, and how you’d analyse it. Some questions to consider in writing this statement include:

• What are the central concepts or variables in your project? Offer a brief definition of each.
• Do any data sources exist on those concepts or variables, or would you need to collect data?
• Of the analytical strategies you could apply to that data, which would be the most appropriate to answer your question? Which would be the most feasible for you? Consider at least two methods, noting their advantages or disadvantages for your project.

Links & books

One of the best texts ever written about planning and executing research comes from a source that might be unexpected: a 60-year-old work on urban planning by a self-trained scholar. The classic book The Death and Life of Great American Cities (1961) by Jane Jacobs (available complete and free of charge via this link ) is worth reading in its entirety just for the pleasure of it. But the final 20 pages – a concluding chapter titled ‘The Kind of Problem a City Is’ – are really about the process of thinking through and investigating a problem. Highly recommended as a window into the craft of research.

Jacobs’s text references an essay on advancing human knowledge by the mathematician Warren Weaver. At the time, Weaver was director of the Rockefeller Foundation, in charge of funding basic research in the natural and medical sciences. Although the essay is titled ‘A Quarter Century in the Natural Sciences’ (1960) and appears at first blush to be merely a summation of one man’s career, it turns out to be something much bigger and more interesting: a meditation on the history of human beings seeking answers to big questions about the world. Weaver goes back to the 17th century to trace the origins of systematic research thinking, with enthusiasm and vivid anecdotes that make the process come alive. The essay is worth reading in its entirety, and is available free of charge via this link .

For those seeking a more in-depth, professional-level discussion of the logic of research design, the political scientist Harvey Starr provides insight in a compact format in the article ‘Cumulation from Proper Specification: Theory, Logic, Research Design, and “Nice” Laws’ (2005). Starr reviews the ‘research triad’, consisting of the interlinked considerations of formulating a question, selecting relevant theories and applying appropriate methods. The full text of the article, published in the scholarly journal Conflict Management and Peace Science , is available, free of charge, via this link .

Finally, the book Getting What You Came For (1992) by Robert Peters is not only an outstanding guide for anyone contemplating graduate school – from the application process onward – but it also includes several excellent chapters on planning and executing research, applicable across a wide variety of subject areas. It was an invaluable resource for me 25 years ago, and it remains in print with good reason; I recommend it to all my students, particularly Chapter 16 (‘The Thesis Topic: Finding It’), Chapter 17 (‘The Thesis Proposal’) and Chapter 18 (‘The Thesis: Writing It’).

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Creating A User Research Plan (with Examples)

UX research helps to test hypothesis you have about users prior to design. Sadly, not every UX design project starts with user research, and that’s because it takes a lot of time to recruit participants, run UX research projects, and sumamrize findings.

Good research, nevertheless, ensures that your product team doesn’t build the wrong functionality that would cost you valuable resources and make you vulnerable to losing customers.

In this article, you’ll see how you can use UX research plan to get stakeholder’s buy-in and create research reports that’s full of valuable advice for product design. Let’s go.

At the end, when you have your research complete, launch the right tool for your design process. For that, try UXPin, an end-to-end design tool for interactive prototyping that brings design and product development together.

Designers can create a powerful prototypes, show them to product managers who can interact with the design instead of just looking at it. Then, they give the design to engineers who can get all the specs and some code to kickstart front-end design with.

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What is a UX Research Plan?

A UX research plan helps to set expectations and document the essentials you need to communicate to stakeholders and clients. Your company needs a strong business case for every user research session, complete with research objectives, goals, methods, and logistical needs for the study.

UX Research Plan Elements

Every UX research plan should start with a solid outline. That’s where templates come in handy. They help you structure your UX research project in a way that team members and stakeholders see value in completing research process.

Master templates are the best way to create a successful and effective UX research plan. Using a template as a starting point makes planning and writing easier and helps you and your team stay focused on the who, what, why, and when of research. Read on for tips and examples for how you can build a user research plan that works.

UX Research Plan Background

The background section should offer your clients and stakeholders a few sentences on why you are creating a user research plan and what it will accomplish. It should orient readers to the needs and expectations behind the purpose of the study. It should also include a problem statement, which is the primary question you’re setting out to answer with your research findings. 

Example Background

The purpose of this study is to understand the major pain points users experience in using our website/app and how these contribute to issues such as cart abandonment, returned items, and low customer loyalty. 

We will be using usability testing to follow the user’s experience of our website/app and the obstacles they encounter leading up to the point of purchase. We will also be using generative research techniques to better understand the customer’s experience of our brand and the challenges and needs they face in making a purchase. 

UX Research Plan Objectives

Before getting into the nitty-gritty of your user research plan, you first want to focus on your research objectives. This step outlines the reasons you are conducting a UX research plan in the first place. Why are you carrying out this research? What are the end goals you have after completing all the work?

Seeking out answers to these questions should be a collaborative effort between you and your stakeholders. It’s also helpful to consider discussions and learnings from past clients and projects to create metrics for your UX research plan. 

Objectives and Success Metrics

Research objectives will be different for every project, but they should always be actionable and specific. 

Example Objectives

• Understand how users currently go about tracking orders on our website
• Understand what actions customers take when they consider buying a new [product we offer]
• Learn about competitor websites/apps customers are using to buy [product we offer]
• Evaluate pain points customers are experiencing in using our website/app

And here are some examples to help you determine the success of your UX research plan.

Example Success Metrics

• What information are we trying to collect about users?
• What scales/documents/statistics do we intend to create?
• What decisions will these materials help to make? 

UX Research Plan Methodology

This step should be a short and sweet description of the research methods you will use to answer the research objectives. It should include both secondary and primary methods. Generative methods, such as user interviews and open-ended questions, help uncover motivations or more general insights, while UX testing helps to evaluate the usability and experience of your product. 

Research Scope & Focus Areas

Clearly outlining the research scope and focus areas helps to facilitate efficient user research planning. The more you’re able to hone in on the specifics of what information you are wanting to collect, the less overwhelmed you will be in the process. It also helps avoid inundating your clients with unnecessary information. 

To keep research-focused, this section should include:

• 3-6 question topics (e.g. How do users spend their time on a website?)
• Design Focus Components, including interface qualities (e.g. Usability, Training, Efficiency, Satisfaction)
• Primary User Scenarios (e.g. Scenarios in which pain points are most problematic; scenarios you have the least information about, etc.)

Example Methodology

For this study, we’re conducting a 30-minute usability test to evaluate our user’s experience of our app/website. A secondary method will be to conduct one-on-one generative research interviews to better understand our customers and empathize with their needs. 

UX Research Plan Participant Profiles

Once you’ve defined objectives methodology and focus areas, it’s time to outline the participants you’ll need to get the required insights. Participant profiles help you determine who you want to recruit, or an approximation of your users, to optimize recruiting efforts. Here are a few examples of how to ensure you’ll get the best participants for your study. 

Define your target user by collaborating with internal stakeholders, marketing, sales, and customer support. With their help, you can create approximations about who your users are. This is a great starting point for finding the right participants for your study. 

Compare yourself to your competitors and create participant profiles based on their audiences. Recruiting people who use a competitor’s product can be an excellent way to glean insights into how to further improve your product. 

Outline a screening process. Participant profiles should include any relevant information concerning your target audience, including behaviors, needs, demographics, geography, etc. Including the right criteria will help you evaluate whether or not to include certain individuals in your user research plan. 

This Nielsen Norman article offers some great information about defining and recruiting the right participants for your study. 

UX Research Plan Timeline

This is optional, but many UX research plans include a timeline that offers clients and stakeholders a general overview of how long the research will take. It helps to set expectations for the final results as well as allowing you to create a schedule for research sessions, debriefing, follow-up, and deliverables. 

Timeline Example: 

Approximately 6-8 weeks for identifying objectives, creating participant profiles, recruitment, in-person meetings, qualitative research, and analysis. 

Try an End-to-End Design Solution

UX research plan templates are essential tools for executing a successful project. Having a master template helps you to remember what the process entails, communicate essential information to the right people, and stay on track throughout the user research plan.

UXPin, besides being a great prototyping tool, makes creating such research templates fast and easy. Especially since each project will be a little different and plans will need tweaking in terms of structure and content. Try UXPin for free .

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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

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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10 Free Research Plan Templates for Teams and Professionals

February 13, 2024

Starting a new research project from scratch can feel overwhelming. Without the right tools and templates, you’re left with a blank page and no direction. With them, starting a new project or organizing an existing one feels like a breeze.

That’s why you need to build a library of the best research plan templates. And we’re here to help you do it.

Stick with us as we run through the benefits of using a research plan template and share some of our favorites—all designed to help make your research projects run like magic.

What is a Research Plan Template?

What makes a good research plan template, 1. clickup user research plan template, 2. clickup market research template, 3. clickup research whiteboard template, 4. clickup equity research report template, 5. clickup seo research & management template, 6. clickup research report template, 7. clickup data analysis findings template, 8. clickup personal swot analysis template, 9. clickup case study template, 10. clickup investigation report template, how to write a research plan.

A research plan template is a document that’s designed to help you build the best research management plan possible. Instead of starting from scratch with a blank screen, a research plan document gives you the building blocks to fill in—so you won’t miss anything important.

There are a lot of solid research plan documents out there—covering everything from UX research (user experience) to case study templates . These templates can be helpful for any team, whether you’re working on product development prototypes or research objectives for a marketing project. They’re especially helpful for product design , UX research, and project management teams.

Some of the most popular research plan templates include:

• UX research plan templates
• Usability testing research templates
• Data analysis findings templates
• Project proposal templates
• Case study templates
• Research process templates
• Market research templates
• Competitive analysis templates
• Request for proposal templates

Each is there to guide you towards collecting, reviewing, and reporting on your research in a more strategic and organized way. Think of the research plan as your helpful research buddy—there to make things easier, provide guidance, and help you ace your project execution .

We’re all looking for something different when it comes to project templates. You might favor simplicity and order, while another team might prefer a more creative approach with lots of color and prompts.

Even though your needs are unique, there are some elements that almost always make a research plan template stand out above all the rest.

The best research plan templates:

• Keep you and your product team organized
• Help you standardize the research process and research method you use 
• Keep you focused on the key project goals and deliverables
• Give you suggestions for metrics to record and analyze
• Help you keep your research questions in one place
• Help you stay on target with your project timeline
• Give you a defined place to store your thoughts and research findings

There’s no one perfect template for any individual or team. Consider what your purpose or goal is, what your project management workstreams look like, and which areas you need the most support or guidance in. This will help you choose which templates to feature and how you can use wiki software to build a collection of your go-to templates.

10 Research Plan Templates to Use in 2024

There are hundreds of research plan templates out there, but they’re not all alike. Some of them bring out the best of your project management skills , while others hinder them.

We’ve brought together the best of the best, to share with you the ultimate list of research plan templates to add to your workflow this year. Want to know what’s even better? You don’t need to get buy-in for an expensive pricing plan—these templates are all free!

One of the first things that comes to mind when you say “research plan template” is user research. For development and project teams, this is one step of the process where strategy and staying organized is essential.

The User Research Plan Template by ClickUp makes it easy for you to achieve that and more. There’s space to share your project overview and research goals, research objectives, hypotheses, and more—plus a bonus Interview Research Debrief doc.

This template acts as a central resource for all the stakeholders. Use it to bring your team together, reaffirm your goals and objectives, and stay on track as you execute your qualitative research project.

Bonus: UX design tools !

Planning your market research is a must-have if you want to get the best possible data. Give your team everything they need in one place and it helps your process run smoothly.

To help keep your team informed and ready to go, we developed the Market Research Template by ClickUp . It’s a Task template that brings you key information, all in one place.

Our Market Research Template features five custom fields—a research presentation link, market research type, report document link, data collection technique, and research stage. Add your clickable links, and use the dropdowns to assign the correct stage or type as you progress.

You can collect user research in so many ways. Questionnaires, user interviews, focus groups, user research sessions, or social media. Another super engaging way to do this is with a whiteboard.

Collaboration and user research feels interactive and fun with the Research Whiteboard Template by ClickUp . Encourage your team to share the insights they’ve collected in this highly visual template, with digital sticky notes instead of empty white boxes.

Use this ClickUp whiteboard template as a more engaging way to view your user research. You can also use this as a tool for internal research projects—invite your stakeholders by link and ask them to comment directly.

If you’re in the business of advising investors on what to do with their money, an equity report is a must-have. Instead of manually writing a new report every time, a research plan template can help you shortcut the process and get straight to the details.

Enter the Equity Research Report Template by ClickUp . It’s designed to help you share what you know in a more strategic way. Share an insight into the company overview, management team, performance, market valuation, and recommendations.

This research plan template has everything you need to present your findings to investors in an organized and effective way. Look like a pro to your investor clients and partners, and store all your data in a meaningful way to reflect on later.

Staying on top of your company’s SEO performance is no easy task. There are so many moving parts, tools, projects, goals, and team members that you need a way to stay organized and productive.

Luckily for you, the SEO Research & Management Template by ClickUp is here to help simplify the process—and make you look good to your boss. This Folder template gives you a dedicated place to work on your SEO goals, with SEO-related custom fields and plenty of custom task types to help your team communicate progress and see roadblocks in your research plan.

Use this template to see at a glance where your SEO projects are, so you can be more proactive about how your team is working. You can also dive in to details and understand time estimates, publish dates, and where your rankings are at.

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There’s no need to start from scratch every time you’re asked to put a research report together—instead use a template to make all your research questions and study reports as impressive as the last one.

Shortcut your way to success with the Research Report Template by ClickUp . There are sections for your executive summary, introduction, research method and techniques, results & discussion, references, and appendices. Add a report author and contributors, so you can recognize everyone that contributed to the report.

Share your research methods, approach, and findings with stakeholders and clients with this impressive template. It’s a useful foundation to help your team get organized and find a better way to update stakeholders on progress.

The Data Analysis Findings Template by ClickUp helps you present your data to everyone in a more meaningful way. Instead of presenting numbers and graphs, this template can help you go deeper into the problem statement, scope, analysis and research method, findings, and conclusion.

Use this template to help you organize your thoughts and communicate the results of your study in a transparent and easy-to-read way. Explain the context and background information alongside your approach, so your stakeholders can fully understand what the data shows.

A personal SWOT analysis can help you understand your (or your team’s) strengths, weaknesses, opportunities, and threats. This information can not only help you work better, but it means you can be more intentional about your impact on the wider company.

The Personal SWOT Analysis Template by ClickUp can help you remember to work on your SWOT analysis. Find your strengths, weaknesses or pain points, opportunities, and threats. This Task template features several custom fields designed to help you monitor your progress—including your objective, timeline, and completion rate.

This template can be a helpful reminder to focus on your personal SWOT analysis, so you can be more intentional and aware of how you contribute to your team and company’s goals and objectives. Use your personal SWOT to help you set professional goals for work and make a bigger impact.

Case studies give you a powerful insight into what your brands, clients, or competitors are doing. They’re an in-depth look into a specific area of the business, based on your personal research and findings.

Simplify the process of building your case studies with the Case Study Template by ClickUp . This template gives you a strong foundation for presenting clear, insightful case studies with your team, stakeholders, or clients. Introduce the company, your case study objective, solutions and statistics, and your insights.

Use this template to help you create case studies at scale. Present your data in a clear and concise way, with all the context your team or stakeholders need to extract the most value from the case study as possible.

Often our research helps us understand the market, our competitors, or what our own company is doing. Sometimes, it’s to help us understand incidents and challenges instead.

That’s where the Investigation Report Template by ClickUp comes in. This template is designed to help you report on accidents, complaints, incidents, and violations. Explain the case details including a summary and evidence, then move into cross-examination with space for interview questions and answers, and your conclusion.

This template is a must-have for teams and companies that want to demonstrate how they overcome challenges or handle incidents. It’s great for transparency and trust-building, and serves as a useful way to document a trail of evidence for when you need it.

Now that you have a template for your research plan, let’s dive into the details of how to write one. Follow these steps to create an effective research plan that will guide your research and help you achieve your goals.

Step 1: Identify Your Research Question

The first step in writing a research plan is to clearly define your research question or topic. This will serve as the foundation for all of your research and help guide your methods and analysis. Make sure your question is specific, relevant, and achievable within the scope of your project.

Step 2: Outline Your Objectives

Next, you should outline the specific objectives or goals of your research. These objectives should be aligned with your research question and provide a clear roadmap for your project. Be sure to make them measurable and achievable.

Step 3: Choose Your Research Methods

Based on your research question and objectives, you can now determine the appropriate methods for gathering data and conducting analysis. This may include surveys, experiments, interviews, or literature reviews. It’s important to choose methods that are suitable for your research topic and will provide reliable and accurate results.

Step 4: Create a Timeline

A research plan should include a detailed timeline for each stage of the project. This will help you stay on track and ensure that you have enough time to complete each task. Be realistic with your timeline and build in some buffer time for unexpected delays or challenges.

Step 5: Consider Ethical Implications

When conducting research, it’s important to consider any potential ethical implications. This may include obtaining consent from participants, ensuring privacy and confidentiality, or following ethical guidelines set by your institution or governing body.

Step 6: Anticipate Potential Outcomes

As with any research project, there are always potential outcomes that can arise. These could be both positive and negative, and it’s important to anticipate and plan for them. This will help you be prepared for any potential challenges or changes that may occur during your research.

Step 7: Revise and Refine Your Plan

Once you have completed the previous steps, it’s essential to review and revise your research plan as needed. It’s common for plans to change as the project progresses, so be open to making adjustments and tweaking your methods or timeline as needed.

Stay Organized with the Best Research Plan Templates

Nobody likes a disorganized project—especially a research project. Let your team breathe a sigh of relief and make your stakeholders smile when they realize you’ve got it all under control.

Use these free research plan templates to help you get organized, streamline your workflows, and keep everyone informed. Build a collection of templates that work for your projects, and make them a central part of the way you work as a team. Standardize, simplify, and get productive.

All of these research plan templates are available right now, for free, inside our template library . Get access to these user-friendly templates, 100MB of storage, 1,000+ integrations, and more with ClickUp—free now, and forever!

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UX Research Plan Template

Create a strong business case for UX research and streamline your process with the UX research plan template.

Trusted by 65M+ users and leading companies

About the UX Research Plan Template

A UX research plan, also known as a user research plan, is a brief reference document that outlines your research project’s goals, key contributors, important dates, and timelines.

Think of your research plan as a UX-focused  kick-off document  for your project. The plan offers an overview of the research initiative, encourages well-defined and agreed-upon goals, and acts as a written guarantee that the research will meet these goals.

What is a UX research plan?

When conducting usability testing or user research with a goal in mind, researchers need to plan. UX researchers often present their findings to stakeholders, like product managers, developers, marketers, and executives, to act on those results.

You should present your UX research plan in plain language with a single document. Keep your findings clear, collaborative, easily accessed, and digestible to get buy-in for your research and your team’s next steps.

A user research plan typically has up to seven segments:

Project background: Reasons for the study and internal stakeholders involved.

Research goals and objectives: What your teams want to learn, or their ideal research outcome.

Research participants: Who they are and how they’ll be recruited.

Method: How you conducted research, and any other information about how the research will be conducted.

Guides: An interview guide or cheat sheet of instructions and questions to follow during the session.

Duration: A rough timeline of how long the research will take and when the team can review the report.

Other helpful information: Additional resources for your team, such as previous studies, scripts, or results, can inform this new round of research.

Research plans keep your team focused on outcomes rather than getting lost in the details or changing the research goal midway through the project. By the end of the project, UX researchers should feel confident that their questions were answered and presented in both the plan and actual research.

When to use UX research plans

UX research plans are useful for teams who need to decide on  questions such as:

What do our customers need? Who is our target persona?

Does the proposed or current design work well for our customers? How can we make it better?

Planning UX research also gives researchers an opportunity to:

Decide what works for your stakeholders, especially the questions they’re trying to answer.

Engage stakeholders and keep them invested in your research results.

Clarify your ideas, problems to be solved, and research approaches.

Treat your research plan as a blueprint for aligning expectations, asking for feedback, or generating enthusiasm and support for increasing the value of user research in your organization.

Create your own UX research plan template

Making your own UX research plans is easy, and Miro is the perfect tool to create and share them. Get started by selecting the UX research plan template, then take the following steps to make one of your own.

Give your team or stakeholders a quick project introduction.  You can hop on a video chat with up to 25 team members and remind everyone what you’re trying to achieve. Remember that research proves its value when it satisfies a single objective rather than many. If you seem to have lots of different goals or objectives, avoid overreaching and start fresh: what’s the one customer problem and business problem you’re trying to solve?

Define the user and business problems your research needs to solve.  The default sticky notes are simply for inspiration — feel free to edit each of these to fix your own context. If you want your team to focus on this area instead of skipping ahead, you can select the “problem” frame and  click the “hide frame” (closed eye) icon  that appears in the frame’s menu.

Define your research goals.  Ask your team to brainstorm their top three research goals or priorities. Remember that the best research sessions are chasing a single objective, so out of the two to three you note down, ask your team to vote for their preferences. Try  Miro’s Voting Plugin  to help your team reach a decision.

Draft your research questions.  Pick three to five questions with your team or stakeholders that are most important to your research. Aim for no more than 10. The more focused your questions, the more focused your research will be.

Link to useful supporting information as needed.  Keep this plan to the point in order to get buy-in. For stakeholders who need more detail, there may be other useful data to link to. If you have previous UX research results or relevant studies, link to them on your Miro Board. You can also import survey data, embed  tables and charts , or link sticky notes  to external sources .

Dive even deeper into how to conduct UX research – and see examples – in our expert guide to  user research .

Why should you use the UX Research Template?

Centralized planning: Centralize your UX research plans in one shared space. This ensures that all relevant information, including research objectives, methodologies, and timelines, is easily accessible in one place, reducing the risk of scattered or lost documentation.

Collaborative research: Multiple stakeholders, including designers, researchers, and product managers, can collaborate on your UX research plan template simultaneously, fostering a more inclusive and collaborative approach to research planning.

Visual representation of research steps: Create diagrams, flowcharts, and visual representations of the research process. This visual mapping helps teams better understand the sequence of research activities, identify dependencies, and effectively communicate the overall research strategy.

Iterative refinement: Provide feedback, comments, and suggestions directly on the UX research plan template. Promote continuous improvement, allowing the team to refine the research plan based on insights and changing project requirements.

Integration with user flows and personas: Integrate with other templates, such as user flows and persona maps. By connecting these elements, teams can create a holistic view of the user experience journey. This integration helps align research activities with the overall UX strategy and ensures a more cohesive and user-centric product design.

How can I ensure that a UX Research Plan remains effective?

Regularly review and update the research plan as project requirements evolve. It's crucial to stay flexible and adapt the plan based on the findings and changing project needs.

Get started with this template right now.

UML Activity Diagram Template

Works best for:.

Use our Activity Diagram template to break down activities into smaller decisions and subprocesses. Improve and optimize systems and processes in I.T., business management, and more.

3x3 Prioritization Method Template

Operations, Prioritization, Strategic Planning

It’s all about assessing a task or idea, and quickly deciding the effort it will take and the potential impact it will have—ranked low, medium, or high. That’s what the 3x3 prioritization method does: Help teams prioritize and identify quick wins, big projects, filler tasks, or time-wasters. With nine bucket areas, it offers slightly greater detail than the 2x2 Prioritization Matrix (or Lean Prioritization Method). It’s easy to make your own 3x3 prioritization matrix—then use it to determine what activities or ideas to focus on with your valuable resources.

Weekly Planner Template

Business Management, Project Planning

A weekly planner is a schedule that outlines your plans and activities for the week ahead. It helps you manage your time, keep track of your tasks, and organize your team on a day-to-day basis. Unlike traditional planners, which are often non-customizable, this weekly planner can be modified to suit your specific needs.

Buyer Persona Template

Marketing, Desk Research, User Experience

You have an ideal customer: The group (or few groups) of people who will buy and love your product or service. But to reach that ideal customer, your entire team or company has to align on who that is. Buyer personas give you a simple but creative way to get that done. These semi-fictional representations of your current and potential customers can help you shape your product offering, weed out the “bad apples,” and tailor your marketing strategies for serious success.

Creative Brief Template

Design, Marketing, Desk Research

Even creative thinkers (or maybe especially creative thinkers) need clear guidelines to push their ideas in productive, usable directions. And a good creative lays down those guidelines, with information that includes target audience, goals, timeline, and budget, as well as the scope and specifications of the project itself. The foundation of any marketing or advertising campaign, a creative brief is the first step in building websites, videos, ads, banners, and much more. The brief is generally prepared before kicking off a project, and this template will make it easy.

UML Component Diagram Template

Mapping, Diagrams, Software Development

Use our Component Diagram template to show how a system’s physical components are organized and wired together. Visualize implementation details, make sure planned development matches system needs, and more — all in a collaborative environment.

Research Plan

Define how to conduct a research activity by writing the protocol before starting., applied for.

Stakeholders

also called

Research Protocol

related content

Hypothesis Generation

Interview Guide

Diary Study

The research plan is a document that clarifies how to approach the research, touching upon research goals, selected methodologies, types of participants and tools used, timeline and locations. This planning activity needs to be done upfront, before starting the actual research, and help maximizing the effort and modeling the activities in the best way possible, according to the specific research purpose. The plan becomes even more important when the research requires to travel in the field, or coordinate different teams in various locations.

Design the research and explain the approach to other team members or stakeholders.

remember to

Include debriefing sessions in the schedule in order to make the work effective and avoid team burnout.

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Research indicates that carbon dioxide removal plans will not be enough to meet Paris treaty goals

There’s a fairly large gap between what nations have committed to and what is required to limit warming to 1.5c..

New research conducted by the University of East Anglia (UEA) suggests that current carbon removal plans will not be enough to comply with Paris treaty goals to limit global warming to 1.5C, as reported in a study published by Nature . Scientists came to this conclusion by measuring the “emissions gap” between various national climate protection plans and what is actually needed to reach that goal.

This first-of-its-kind study found a gap of up to 3.2 billion tons of carbon dioxide (CO2) between current global plans to remove carbon from the atmosphere and what’s needed by 2050 to avoid the worst impacts of global warming . These impacts include heatwaves, floods, droughts, melting ice and sea level rise .

Since 2010, the United Nations environmental organization UNEP has taken similar measurements of this emissions gap. UEA’s research, which focuses primarily on CO2 removal, indicates that climate policy requires a more ambitious scope if we are to, well, survive as a species.

This means a more nuanced and robust approach that still keeps current carbon removal practices in place, but with a renewed focus on cutting emissions, renewable energy and minimizing deforestation. There are also novel carbon removal options that many nations have been slow to discuss, let alone implement.

These include advanced air filters systems and enhanced rock weathering . The latter is a technique in which carbon is removed from the atmosphere and stored in rocks. These techniques account for the removal of just 0.002 billion tons of C02 per year, compared to 3 billion tons through conventional options. The research indicates that these novel options must become more prevalent in the coming years to help meet that 1.5C threshold.

“The calculation should certainly be refined,” said the study’s lead author, Dr. William Lamb, of the MCC Applied Sustainability Science working group. “This much is clear: without a rapid reduction in emissions towards zero, across all sectors, the 1.5C limit will not be met under any circumstances.”

Co-author Dr. Naomi Vaughan, of the Tyndall Centre for Climate Change Research at UEA, added that “countries need more awareness, ambition and action on scaling up carbon dioxide removal methods together with deep emissions reductions to achieve the aspirations of the Paris Agreement."

To that end, even if every country sticks to promises regarding carbon removal targets, the amount of carbon removed would likely increase by a maximum of 0.5 billion tons by 2030 and 1.9 billion tons by 2050. The latest Intergovernmental Panel on Climate Change (IPCC) reported that it would take a removal increase of 5.1 billion tons to avoid the worst effects of climate change. So, yeah, there’s that gap of 3.2 billion tons.

We aren’t doomed, at least not yet anyways. The IPCC suggests an alternative scenario in which the world’s governments work together to reduce global energy demand, hastened by “politically initiated behavior.” In this scenario, carbon removal would increase by 2.5 billion tons by 2050 and alternative methods would help tighten the emissions gap to just 400 million tons. So we basically have to shift our entire society from one of self interest to one of global cooperation. It never hurts to dream and, hey, maybe AI will swoop in and save us .

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• Environment
• River maintenance, flooding and coastal erosion

Shoreline management plans

Check how coastal flood and erosion risks will be managed in your area.

Applies to England

Shoreline Management Plans ( SMPs ) help to deliver the ambitions of the National Flood and Coastal Erosion Risk Management Strategy . They set out a planned approach to managing flood and coastal erosion risk around the coast of England to 2105.

There are 20 SMPs covering the English coast. You can see these on the Shoreline Management Plan Explorer .

What SMPs are

SMPs were developed by coastal groups between 2006 and 2012.

Coastal groups include:

• the Environment Agency
• local authorities
• others with an interest in coastal management

The Environment Agency has a strategic overview role for the management of all sources of flooding and coastal change in England, including coastal erosion. This includes approving SMPs and any changes made to them.

SMPs are living plans updated by coastal groups. They guide coastal management investment decisions on the coast such as:

• building and maintaining sea defences
• implementing adaptation plans
• creating coastal habitats

They are adopted by local authorities and used as part of the town and country planning system to designate Coastal Change Management Areas ( CCMAs ). They also inform local plans and development decisions.

The Environment Agency has worked closely with coastal groups to refresh and improve SMPs . These works include:

• updating the action plans
• improving the description of management approaches
• making the SMPs easier to access through the Shoreline Management Plan explorer

The Environment Agency also commissioned an independent peer review to assess the state of SMPs and identify where further improvements can be made. The peer review panel was made up of six coastal experts including representatives from local government and academia. The peer review report provides an objective view of how much the updated shoreline management plans are contributing to the ambitions of the National Flood and Coastal Erosion Risk Management Strategy .

These ambitions include:

• climate resilient places - working with partners to bolster resilience to flooding and coastal change across the nation, both now and in the face of climate change
• today’s growth and infrastructure resilient in tomorrow’s climate - making the right investment and planning decisions to secure sustainable growth and environmental improvements, as well as resilient infrastructure
• a nation ready to respond and adapt to flooding and coastal change - making sure local people understand their risk to flooding and coastal change, and know their responsibilities and how to take action

The Environment Agency is continuing to work with coastal groups on further improvements to SMPs . These include updating management approaches where needed and providing new assessments of coastal flood and erosion risks.

Department for Environment, Food and Rural Affairs (Defra) has committed to review national policy for shoreline management plans by 2026. This will be informed by the Environment Agency’s SMP refresh.

It will make sure:  

• local plans are transparent  
• they continuously review outcomes and enable  
• local authorities can  make robust decisions for their areas  

This commitment is set out in the government’s flood and coastal erosion risk management policy statement.

What is the Shoreline Management Plan Explorer

The Shoreline Management Plan Explorer  is an online tool that makes shoreline management plans easier to access and use.

It is available for:

• coastal managers
• local authority planners
• the public, including communities living on the coast

You can use the Shoreline Management Plan Explorer  to view:

• SMP management approaches and actions for each section of coast
• where changes to management approaches have been made and why
• areas protected for their environmental, historic or landscape importance which must be considered when deciding the approach to managing flood and erosion risk
• guidance on how shoreline management plans are developed and updated

Who uses Shoreline Management Plans

The Environment Agency and local authorities use SMPs to guide investment in managing flood and erosion risk to people and property in a sustainable way.

Local planning authorities can use SMPs to guide where they plan and permit development, including the designation of CCMAs .

The National Planning Policy Framework Planning Practice Guidance explains how planners can use SMPs to define coastal change management areas and their associated policies.

SMPs are useful to anybody living and working at the coast or to those interested in how the coast is changing and how it is being managed.

Shoreline Management Plan management approaches

All SMPs apply a management approach for each section or ‘unit’ of the coast through this century. They have been developed by coastal groups in consultation with local communities. They are based on the best available evidence on how the coast is changing and what may be at risk from flooding or erosion now and in the future.

The management approaches are:

• hold the line - maintain or upgrade protection from flooding or erosion by holding the shoreline in broadly the same position
• no active intervention - maintain or encourage a more natural coastline, which may involve discussing adaptation to the risk from flooding or erosion
• managed realignment - change the position of the shoreline in a controlled way, such as by slowing erosion or creating areas of habitat to help manage flooding
• advance the line - actively move shoreline defences significantly seawards

The Shoreline Management Plan Explorer explains how these approaches can be achieved along different sections of the coast. All are dependent upon funding being available.

Management approaches can change if new evidence shows a different approach would be more sustainable. The Environment Agency reviews all changes proposed to management approaches.

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All you have to do is ask. Chat with your doc.

Meet AI Assistant for Acrobat. Interact with your document for quick answers and one-click summaries to create impactful content and level up your productivity. It’s available on desktop, web, and mobile.  Watch video .

AI Assistant for Acrobat starts at     . Early-access pricing ends June 4, 2024.

AI Assistant for Acrobat starts at     . Early-access pricing ends June 4, 2024.

Existing Acrobat user? Click here

*Available to individual users in English only. Generative summary not available on mobile.

A whole new way to get to what matters.

AI ASSISTANT

Ask AI Assistant.

Now you can engage with your document. Ask it questions and get quick answers linked to sources primarily from your doc. Then use the responses to craft your emails, presentations, and more — helping you sound like an expert in seconds. And with voice prompts in the mobile app, working on the go is easier than ever.

GENERATIVE SUMMARY

Sum it up, quick.

Save time and accomplish more. One-click generative summary automatically pulls out key points to help you navigate your docs and get important info fast. Available on desktop and web.

Explore all you can do with AI Assistant.

Simplify sales research and prospecting.

Learn what you need to know about your prospects so you can be effective at sales meetings.

Share findings faster.

Summarize industry reports, get deeper insights, and draft recaps for your team in no time.

Easily create study guides.

Ask AI Assistant to generate a study guide that you can quickly refine to make your own.

See how AI Assistant is helping small businesses think big.

Productivity is now in fashion. Watch to learn how AI Assistant for Acrobat boosts productivity at Bryan Bonilla’s fashion brand so he can focus on being creative.

PLANS AND PRICING

Get AI Assistant with these Acrobat plans.

Acrobat reader.

View, print, share, and comment on PDFs.

AI Assistant add-on available starting at     . Early access pricing ends June 4, 2024.

Available on desktop and mobile

View, print, share, and comment

Acrobat Standard

The simple PDF tool for editing and converting documents.

Starting at

Available on desktop, web, and mobile

Edit text and images, export, secure, and organize documents

Collect legally binding e-signatures and track responses

Acrobat Pro

The essential PDF and e-signature solution with secure, advanced tools.

Create web forms, redact, compare, and access 70+ features

Get early-access pricing starting at      when you add AI Assistant to Reader, Standard, or Pro.

Learn more  about AI Assistant for business.

Already an existing Acrobat customer?

If you already have an Acrobat Reader, Standard, or Pro plan, simply sign in on your Acrobat or Acrobat Reader app and try AI Assistant today.

The Adobe difference.

We protect your documents and content using responsible practices and developed Acrobat generative AI following Adobe’s AI Ethics principles of accountability, responsibility, and transparency.

Frequently asked questions.

AI Assistant Customers can ask questions in documents and receive easy-to-understand answers with attribution. AI Assistant can help generate a document summary and suggested questions based on the document to help customers explore, comprehend content, and gain insights more effectively.​

Using responses from AI Assistant, customers can consume info and create impactful content based on their document faster than ever — draft and share content for emails, presentations, meeting notes, research summaries, and more.​

Generative summary With generative summary, customers automatically get an outline with headings and section-specific key points to help them focus on what matters in a streamlined way — easily finding, discerning, and navigating to essential information they need on demand.

Voice Prompt (mobile) Enhance productivity on the go with AI Assistant on Acrobat Reader mobile. Get key insights with voice prompt, making comprehension easier and faster —creating content for emails, study guides, blog posts, and more.

AI Assistant can help customers accelerate document comprehension and transform their productivity:

• Summarize crucial concepts and themes from the document       
• Get one-click summaries with generative summary (desktop and web)  
• Explore content using suggested questions 
• Ask questions and receive credible answers with cited references

Communicate with impact. Customers can save time when AI Assistant helps them create content based on their document.

• Create content from their documents for emails, presentations, meeting notes, and more
• Come up with ideas for blog posts, articles, research topics, and more

Get inspired —  see how others have incorporated AI Assistant into their everyday work.

Acrobat Individual customers can access these features in Reader desktop and the Adobe Acrobat desktop application on both Windows and macOS, on the Acrobat web application, on Acrobat mobile applications (iOS and Android), and in their Google Chrome or Microsoft Edge extensions.

Acrobat Individual free and paid customers will receive a complimentary, limited number of AI Assistant “requests.” Customers will have the opportunity to purchase an add-on for their existing Acrobat plan for full use of AI Assistant.

Generative AI features in Acrobat are available through a public beta for Teams customers. A private beta is available for paid Enterprise VIP customers. To determine entitlement status for a teams or enterprise account, contact the account admin . Paid Enterprise ETLA customers can access generative AI features through a free trial, please contact an Adobe sales representative. To learn more about AI Assistant for Teams and Enterprises, see here .

AI Assistant will be available in countries where Acrobat is currently available. Adobe products and services, including ones with AI Assistant for Acrobat, are not available in Belarus, China, Crimea, Cuba, Iran, North Korea, Russia, Syria, the Crimea Region of Ukraine, and the so-called breakaway Luhansk People’s Republic and Donetsk People’s Republic located in Ukraine. 

Currently, AI Assistant in Acrobat supports PDFs in English with plans to add additional languages in future releases. AI Assistant may inadvertently provide non-English responses, but these go beyond the intended purpose of the AI Assistant capability and should not be relied upon at this time. 

At this time, this feature works for PDFs that meet certain criteria. It doesn’t yet support the following types of files:

• Files exceeding 25MB in size
• Files that contain more than 120 pages
• Files with permissions that are configured in a way that prevents processing, such as being password-protected or having the “do not copy” permission enabled 
• Files that are scanned PDF documents
• Files in a non-English language

Yes, a separate add-on plan for full access is available to new and existing Acrobat Individual customers. Acrobat Individual customers do not need to have an existing Acrobat Pro or Acrobat Standard plan to purchase. See the plans page for additional details.  

For Teams customers, generative AI features in Acrobat are available as a public beta. A private beta is available for paid Enterprise VIP customers. To determine entitlement status for a teams or enterprise accounts, contact the account admin . Paid Enterprise ETLA customers can access generative AI features through a free trial, please contact an Adobe sales representative to learn more.

We encourage customers to provide feedback directly in the product. They can select the thumbs-up icon or thumbs-down icon to express their approval or disapproval with the generated responses. To provide more detailed feedback, customers should select “Thanks! Tell us more,” or they can choose from the provided options to add a note, and then select "Submit." Customers also can choose to share their document and its associated data associated with Adobe while providing more detailed feedback. 

In the case of inappropriate content being generated, customers should press the flag icon to report it. Their document and the associated data will be escalated to the Adobe Trust & Safety team and other internal channels to investigate and address.

The new AI Assistant features were developed and deployed after undergoing review by the Adobe AI Ethics Review Board and have been designed to reflect Adobe’s AI Ethics principles of accountability, responsibility, and transparency.

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Defense think tank MITRE to build AI supercomputer with Nvidia

The $20 million AI “sandbox” will allow federal agencies from the Pentagon to the IRS to test cutting-edge technologies.

A key supplier to the Pentagon and U.S. intelligence agencies is building a $20 million supercomputer with buzzy chipmaker Nvidia to speed deployment of artificial intelligence capabilities across the U.S. federal government, the MITRE think tank said Tuesday.

MITRE, a federally funded, not-for-profit research organization that has supplied U.S. soldiers and spies with exotic technical products since the 1950s, says the project could improve everything from Medicare to taxes.

“There’s huge opportunities for AI to make government more efficient,” said Charles Clancy, senior vice president of MITRE. “Government is inefficient, it’s bureaucratic, it takes forever to get stuff done. … That’s the grand vision, is how do we do everything from making Medicare sustainable to filing your taxes easier?”

This AI project is an example of the flurry of activity prompted by the Biden administration’s all-of-government push to ensure the United States remains the world’s leading AI power. Biden signed an executive order in October that ordered accelerated research and deployment of AI across federal agencies, as China makes efforts to catch up.

The MITRE supercomputer will be based in Ashburn, Va., and should be up and running late this year.

MITRE was spun out of a Massachusetts Institute of Technology lab in 1958 and is part of a network of Pentagon-funded research and development centers set up in the early years of the Cold War that also includes Rand and the Fermi National Accelerator Laboratory in Batavia, Ill.

For decades, MITRE has been a supplier of surveillance, communications and cybersecurity technologies to the Pentagon and U.S. intelligence agencies. “We go way beyond what people would typically call IT,” is how a former MITRE chief executive described the organization’s research to Forbes magazine, which reported its projects included a prototype tool that could hack smartwatches and software for the FBI that can capture fingerprints from photos of suspects’ hands on social media websites.

Other recent MITRE projects include technology to counter GPS interference, a study on pathogens in Arctic permafrost and a small drone for the U.S. Navy designed to operate autonomously at sea.

Among MITRE’s funding agencies are the departments of Defense, Homeland Security, Commerce and Treasury, as well as the Internal Revenue Service, the Federal Aviation Administration, and the Social Security Administration. The think tank has 9,000 employees — more than Nintendo or Airbnb — and booked $2.2 billion in revenue in 2022. Clancy said half of MITRE’s R&D funds are currently devoted to AI.

Clancy said the planned supercomputer will run 256 Nvidia graphics processing units, or GPUs, at a cost of $20 million. This counts as a small supercomputer: The world’s fastest supercomputer, Frontier in Tennessee, boasts 37,888 GPUs, and Meta is seeking to build one with 350,000 GPUs. But MITRE’s computer will still eclipse Stanford’s Natural Language Processing Group’s 68 GPUs, and will be large enough to train large language models to perform AI tasks tailored for government agencies.

Clancy said all federal agencies funding MITRE will be able to use this AI “sandbox.”

“AI is the tool that is solving a wide range of problems,” Clancy said. “The U.S. military needs to figure out how to do command and control. We need to understand how cryptocurrency markets impact the traditional banking sector. … Those are the sorts of problems we want to solve.”

The contract is the latest success for Nvidia, which is riding high on the AI boom. The Santa Clara, Calif.-based chipmaker is the world’s leader in designing the GPUs used to train advanced AI models, and there has been a global mad scramble for its chips. Nvidia’s stock price is up more than 200 percent from a year earlier.

Anthony Robbins, vice president of federal for Nvidia, said that the AI sandbox could assist the U.S. government with tasks such as securing infrastructure against cyberthreats, cracking down on fraud, and rolling out chatbots and digital assistants.

“This is a platform by which MITRE can train these large language models,” he said. “You can’t do this important AI work if you don’t have this infrastructure.”

The MITRE-Nvidia AI project is one of a spate of initiatives since Biden’s AI executive order. Silicon Valley giants, defense contractors and universities are all scrambling for a flood of AI contracts.

Graham Gilmer, senior vice president for defense contractor Booz Allen, which is also supplying AI products to the Defense Department and other federal agencies, said that there has been a lot of activity since the executive order and that the deployment of these AI technologies across the government will probably continue through the decade.

“It’s certainly a major shift that we know all of government is going to have to undertake,” he said.

Other federal AI projects are also underway. The National Science Foundation launched an AI research program in January with companies such as Amazon, Google and OpenAI as partners, along with agencies such as the Defense Advanced Research Projects Agency.

The Pentagon has begun studying military applications of generative AI in a program called “Task Force Lima.”

The National Institute of Standards and Technology has also launched a U.S. AI Safety Institute that is researching AI risks with the input of industry.