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

Last updated

30 January 2024

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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

Should you be using a customer insights hub?

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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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1000+ FREE Research Topics & Title Ideas

If you’re at the start of your research journey and are trying to figure out which research topic you want to focus on, you’ve come to the right place. Select your area of interest below to view a comprehensive collection of potential research ideas.

Research Topic FAQs

What (exactly) is a research topic.

A research topic is the subject of a research project or study – for example, a dissertation or thesis. A research topic typically takes the form of a problem to be solved, or a question to be answered.

A good research topic should be specific enough to allow for focused research and analysis. For example, if you are interested in studying the effects of climate change on agriculture, your research topic could focus on how rising temperatures have impacted crop yields in certain regions over time.

To learn more about the basics of developing a research topic, consider our free research topic ideation webinar.

What constitutes a good research topic?

A strong research topic comprises three important qualities : originality, value and feasibility.

• Originality – a good topic explores an original area or takes a novel angle on an existing area of study.
• Value – a strong research topic provides value and makes a contribution, either academically or practically.
• Feasibility – a good research topic needs to be practical and manageable, given the resource constraints you face.

To learn more about what makes for a high-quality research topic, check out this post .

What's the difference between a research topic and research problem?

A research topic and a research problem are two distinct concepts that are often confused. A research topic is a broader label that indicates the focus of the study , while a research problem is an issue or gap in knowledge within the broader field that needs to be addressed.

To illustrate this distinction, consider a student who has chosen “teenage pregnancy in the United Kingdom” as their research topic. This research topic could encompass any number of issues related to teenage pregnancy such as causes, prevention strategies, health outcomes for mothers and babies, etc.

Within this broad category (the research topic) lies potential areas of inquiry that can be explored further – these become the research problems . For example:

• What factors contribute to higher rates of teenage pregnancy in certain communities?
• How do different types of parenting styles affect teen pregnancy rates?
• What interventions have been successful in reducing teenage pregnancies?

Simply put, a key difference between a research topic and a research problem is scope ; the research topic provides an umbrella under which multiple questions can be asked, while the research problem focuses on one specific question or set of questions within that larger context.

How can I find potential research topics for my project?

There are many steps involved in the process of finding and choosing a high-quality research topic for a dissertation or thesis. We cover these steps in detail in this video (also accessible below).

How can I find quality sources for my research topic?

Finding quality sources is an essential step in the topic ideation process. To do this, you should start by researching scholarly journals, books, and other academic publications related to your topic. These sources can provide reliable information on a wide range of topics. Additionally, they may contain data or statistics that can help support your argument or conclusions.

Identifying Relevant Sources

When searching for relevant sources, it’s important to look beyond just published material; try using online databases such as Google Scholar or JSTOR to find articles from reputable journals that have been peer-reviewed by experts in the field.

You can also use search engines like Google or Bing to locate websites with useful information about your topic. However, be sure to evaluate any website before citing it as a source—look for evidence of authorship (such as an “About Us” page) and make sure the content is up-to-date and accurate before relying on it.

Evaluating Sources

Once you’ve identified potential sources for your research project, take some time to evaluate them thoroughly before deciding which ones will best serve your purpose. Consider factors such as author credibility (are they an expert in their field?), publication date (is the source current?), objectivity (does the author present both sides of an issue?) and relevance (how closely does this source relate to my specific topic?).

By researching the current literature on your topic, you can identify potential sources that will help to provide quality information. Once you’ve identified these sources, it’s time to look for a gap in the research and determine what new knowledge could be gained from further study.

How can I find a good research gap?

Finding a strong gap in the literature is an essential step when looking for potential research topics. We explain what research gaps are and how to find them in this post.

How should I evaluate potential research topics/ideas?

When evaluating potential research topics, it is important to consider the factors that make for a strong topic (we discussed these earlier). Specifically:

• Originality
• Feasibility

So, when you have a list of potential topics or ideas, assess each of them in terms of these three criteria. A good topic should take a unique angle, provide value (either to academia or practitioners), and be practical enough for you to pull off, given your limited resources.

Finally, you should also assess whether this project could lead to potential career opportunities such as internships or job offers down the line. Make sure that you are researching something that is relevant enough so that it can benefit your professional development in some way. Additionally, consider how each research topic aligns with your career goals and interests; researching something that you are passionate about can help keep motivation high throughout the process.

How can I assess the feasibility of a research topic?

When evaluating the feasibility and practicality of a research topic, it is important to consider several factors.

First, you should assess whether or not the research topic is within your area of competence. Of course, when you start out, you are not expected to be the world’s leading expert, but do should at least have some foundational knowledge.

Time commitment

When considering a research topic, you should think about how much time will be required for completion. Depending on your field of study, some topics may require more time than others due to their complexity or scope.

Additionally, if you plan on collaborating with other researchers or institutions in order to complete your project, additional considerations must be taken into account such as coordinating schedules and ensuring that all parties involved have adequate resources available.

Resources needed

It’s also critically important to consider what type of resources are necessary in order to conduct the research successfully. This includes physical materials such as lab equipment and chemicals but can also include intangible items like access to certain databases or software programs which may be necessary depending on the nature of your work. Additionally, if there are costs associated with obtaining these materials then this must also be factored into your evaluation process.

Potential risks

It’s important to consider the inherent potential risks for each potential research topic. These can include ethical risks (challenges getting ethical approval), data risks (not being able to access the data you’ll need), technical risks relating to the equipment you’ll use and funding risks (not securing the necessary financial back to undertake the research).

If you’re looking for more information about how to find, evaluate and select research topics for your dissertation or thesis, check out our free webinar here . Alternatively, if you’d like 1:1 help with the topic ideation process, consider our private coaching services .

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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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Sat / act prep online guides and tips, 113 great research paper topics.

General Education

One of the hardest parts of writing a research paper can be just finding a good topic to write about. Fortunately we've done the hard work for you and have compiled a list of 113 interesting research paper topics. They've been organized into ten categories and cover a wide range of subjects so you can easily find the best topic for you.

In addition to the list of good research topics, we've included advice on what makes a good research paper topic and how you can use your topic to start writing a great paper.

What Makes a Good Research Paper Topic?

Not all research paper topics are created equal, and you want to make sure you choose a great topic before you start writing. Below are the three most important factors to consider to make sure you choose the best research paper topics.

#1: It's Something You're Interested In

A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject. Even if a certain research paper topic is getting a lot of buzz right now or other people seem interested in writing about it, don't feel tempted to make it your topic unless you genuinely have some sort of interest in it as well.

#2: There's Enough Information to Write a Paper

Even if you come up with the absolute best research paper topic and you're so excited to write about it, you won't be able to produce a good paper if there isn't enough research about the topic. This can happen for very specific or specialized topics, as well as topics that are too new to have enough research done on them at the moment. Easy research paper topics will always be topics with enough information to write a full-length paper.

Trying to write a research paper on a topic that doesn't have much research on it is incredibly hard, so before you decide on a topic, do a bit of preliminary searching and make sure you'll have all the information you need to write your paper.

#3: It Fits Your Teacher's Guidelines

Don't get so carried away looking at lists of research paper topics that you forget any requirements or restrictions your teacher may have put on research topic ideas. If you're writing a research paper on a health-related topic, deciding to write about the impact of rap on the music scene probably won't be allowed, but there may be some sort of leeway. For example, if you're really interested in current events but your teacher wants you to write a research paper on a history topic, you may be able to choose a topic that fits both categories, like exploring the relationship between the US and North Korea. No matter what, always get your research paper topic approved by your teacher first before you begin writing.

113 Good Research Paper Topics

Below are 113 good research topics to help you get you started on your paper. We've organized them into ten categories to make it easier to find the type of research paper topics you're looking for.

Arts/Culture

• Discuss the main differences in art from the Italian Renaissance and the Northern Renaissance .
• Analyze the impact a famous artist had on the world.
• How is sexism portrayed in different types of media (music, film, video games, etc.)? Has the amount/type of sexism changed over the years?
• How has the music of slaves brought over from Africa shaped modern American music?
• How has rap music evolved in the past decade?
• How has the portrayal of minorities in the media changed?

Current Events

• What have been the impacts of China's one child policy?
• How have the goals of feminists changed over the decades?
• How has the Trump presidency changed international relations?
• Analyze the history of the relationship between the United States and North Korea.
• What factors contributed to the current decline in the rate of unemployment?
• What have been the impacts of states which have increased their minimum wage?
• How do US immigration laws compare to immigration laws of other countries?
• How have the US's immigration laws changed in the past few years/decades?
• How has the Black Lives Matter movement affected discussions and view about racism in the US?
• What impact has the Affordable Care Act had on healthcare in the US?
• What factors contributed to the UK deciding to leave the EU (Brexit)?
• What factors contributed to China becoming an economic power?
• Discuss the history of Bitcoin or other cryptocurrencies  (some of which tokenize the S&P 500 Index on the blockchain) .
• Do students in schools that eliminate grades do better in college and their careers?
• Do students from wealthier backgrounds score higher on standardized tests?
• Do students who receive free meals at school get higher grades compared to when they weren't receiving a free meal?
• Do students who attend charter schools score higher on standardized tests than students in public schools?
• Do students learn better in same-sex classrooms?
• How does giving each student access to an iPad or laptop affect their studies?
• What are the benefits and drawbacks of the Montessori Method ?
• Do children who attend preschool do better in school later on?
• What was the impact of the No Child Left Behind act?
• How does the US education system compare to education systems in other countries?
• What impact does mandatory physical education classes have on students' health?
• Which methods are most effective at reducing bullying in schools?
• Do homeschoolers who attend college do as well as students who attended traditional schools?
• Does offering tenure increase or decrease quality of teaching?
• How does college debt affect future life choices of students?
• Should graduate students be able to form unions?

• What are different ways to lower gun-related deaths in the US?
• How and why have divorce rates changed over time?
• Is affirmative action still necessary in education and/or the workplace?
• Should physician-assisted suicide be legal?
• How has stem cell research impacted the medical field?
• How can human trafficking be reduced in the United States/world?
• Should people be able to donate organs in exchange for money?
• Which types of juvenile punishment have proven most effective at preventing future crimes?
• Has the increase in US airport security made passengers safer?
• Analyze the immigration policies of certain countries and how they are similar and different from one another.
• Several states have legalized recreational marijuana. What positive and negative impacts have they experienced as a result?
• Do tariffs increase the number of domestic jobs?
• Which prison reforms have proven most effective?
• Should governments be able to censor certain information on the internet?
• Which methods/programs have been most effective at reducing teen pregnancy?
• What are the benefits and drawbacks of the Keto diet?
• How effective are different exercise regimes for losing weight and maintaining weight loss?
• How do the healthcare plans of various countries differ from each other?
• What are the most effective ways to treat depression ?
• What are the pros and cons of genetically modified foods?
• Which methods are most effective for improving memory?
• What can be done to lower healthcare costs in the US?
• What factors contributed to the current opioid crisis?
• Analyze the history and impact of the HIV/AIDS epidemic .
• Are low-carbohydrate or low-fat diets more effective for weight loss?
• How much exercise should the average adult be getting each week?
• Which methods are most effective to get parents to vaccinate their children?
• What are the pros and cons of clean needle programs?
• How does stress affect the body?
• Discuss the history of the conflict between Israel and the Palestinians.
• What were the causes and effects of the Salem Witch Trials?
• Who was responsible for the Iran-Contra situation?
• How has New Orleans and the government's response to natural disasters changed since Hurricane Katrina?
• What events led to the fall of the Roman Empire?
• What were the impacts of British rule in India ?
• Was the atomic bombing of Hiroshima and Nagasaki necessary?
• What were the successes and failures of the women's suffrage movement in the United States?
• What were the causes of the Civil War?
• How did Abraham Lincoln's assassination impact the country and reconstruction after the Civil War?
• Which factors contributed to the colonies winning the American Revolution?
• What caused Hitler's rise to power?
• Discuss how a specific invention impacted history.
• What led to Cleopatra's fall as ruler of Egypt?
• How has Japan changed and evolved over the centuries?
• What were the causes of the Rwandan genocide ?

• Why did Martin Luther decide to split with the Catholic Church?
• Analyze the history and impact of a well-known cult (Jonestown, Manson family, etc.)
• How did the sexual abuse scandal impact how people view the Catholic Church?
• How has the Catholic church's power changed over the past decades/centuries?
• What are the causes behind the rise in atheism/ agnosticism in the United States?
• What were the influences in Siddhartha's life resulted in him becoming the Buddha?
• How has media portrayal of Islam/Muslims changed since September 11th?

Science/Environment

• How has the earth's climate changed in the past few decades?
• How has the use and elimination of DDT affected bird populations in the US?
• Analyze how the number and severity of natural disasters have increased in the past few decades.
• Analyze deforestation rates in a certain area or globally over a period of time.
• How have past oil spills changed regulations and cleanup methods?
• How has the Flint water crisis changed water regulation safety?
• What are the pros and cons of fracking?
• What impact has the Paris Climate Agreement had so far?
• What have NASA's biggest successes and failures been?
• How can we improve access to clean water around the world?
• Does ecotourism actually have a positive impact on the environment?
• Should the US rely on nuclear energy more?
• What can be done to save amphibian species currently at risk of extinction?
• What impact has climate change had on coral reefs?
• How are black holes created?
• Are teens who spend more time on social media more likely to suffer anxiety and/or depression?
• How will the loss of net neutrality affect internet users?
• Analyze the history and progress of self-driving vehicles.
• How has the use of drones changed surveillance and warfare methods?
• Has social media made people more or less connected?
• What progress has currently been made with artificial intelligence ?
• Do smartphones increase or decrease workplace productivity?
• What are the most effective ways to use technology in the classroom?
• How is Google search affecting our intelligence?
• When is the best age for a child to begin owning a smartphone?
• Has frequent texting reduced teen literacy rates?

How to Write a Great Research Paper

Even great research paper topics won't give you a great research paper if you don't hone your topic before and during the writing process. Follow these three tips to turn good research paper topics into great papers.

#1: Figure Out Your Thesis Early

Before you start writing a single word of your paper, you first need to know what your thesis will be. Your thesis is a statement that explains what you intend to prove/show in your paper. Every sentence in your research paper will relate back to your thesis, so you don't want to start writing without it!

As some examples, if you're writing a research paper on if students learn better in same-sex classrooms, your thesis might be "Research has shown that elementary-age students in same-sex classrooms score higher on standardized tests and report feeling more comfortable in the classroom."

If you're writing a paper on the causes of the Civil War, your thesis might be "While the dispute between the North and South over slavery is the most well-known cause of the Civil War, other key causes include differences in the economies of the North and South, states' rights, and territorial expansion."

#2: Back Every Statement Up With Research

Remember, this is a research paper you're writing, so you'll need to use lots of research to make your points. Every statement you give must be backed up with research, properly cited the way your teacher requested. You're allowed to include opinions of your own, but they must also be supported by the research you give.

#3: Do Your Research Before You Begin Writing

You don't want to start writing your research paper and then learn that there isn't enough research to back up the points you're making, or, even worse, that the research contradicts the points you're trying to make!

Get most of your research on your good research topics done before you begin writing. Then use the research you've collected to create a rough outline of what your paper will cover and the key points you're going to make. This will help keep your paper clear and organized, and it'll ensure you have enough research to produce a strong paper.

What's Next?

Are you also learning about dynamic equilibrium in your science class? We break this sometimes tricky concept down so it's easy to understand in our complete guide to dynamic equilibrium .

Thinking about becoming a nurse practitioner? Nurse practitioners have one of the fastest growing careers in the country, and we have all the information you need to know about what to expect from nurse practitioner school .

Want to know the fastest and easiest ways to convert between Fahrenheit and Celsius? We've got you covered! Check out our guide to the best ways to convert Celsius to Fahrenheit (or vice versa).

These recommendations are based solely on our knowledge and experience. If you purchase an item through one of our links, PrepScholar may receive a commission.

Christine graduated from Michigan State University with degrees in Environmental Biology and Geography and received her Master's from Duke University. In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist. She has taught English and biology in several countries.

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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Education During Coronavirus

A Smithsonian magazine special report

Science | June 15, 2020

Seventy-Five Scientific Research Projects You Can Contribute to Online

From astrophysicists to entomologists, many researchers need the help of citizen scientists to sift through immense data collections

Rachael Lallensack

Former Assistant Editor, Science and Innovation

If you find yourself tired of streaming services, reading the news or video-chatting with friends, maybe you should consider becoming a citizen scientist. Though it’s true that many field research projects are paused , hundreds of scientists need your help sifting through wildlife camera footage and images of galaxies far, far away, or reading through diaries and field notes from the past.

Plenty of these tools are free and easy enough for children to use. You can look around for projects yourself on Smithsonian Institution’s citizen science volunteer page , National Geographic ’s list of projects and CitizenScience.gov ’s catalog of options. Zooniverse is a platform for online-exclusive projects , and Scistarter allows you to restrict your search with parameters, including projects you can do “on a walk,” “at night” or “on a lunch break.”

To save you some time, Smithsonian magazine has compiled a collection of dozens of projects you can take part in from home.

American Wildlife

If being home has given you more time to look at wildlife in your own backyard, whether you live in the city or the country, consider expanding your view, by helping scientists identify creatures photographed by camera traps. Improved battery life, motion sensors, high-resolution and small lenses have made camera traps indispensable tools for conservation.These cameras capture thousands of images that provide researchers with more data about ecosystems than ever before.

Smithsonian Conservation Biology Institute’s eMammal platform , for example, asks users to identify animals for conservation projects around the country. Currently, eMammal is being used by the Woodland Park Zoo ’s Seattle Urban Carnivore Project, which studies how coyotes, foxes, raccoons, bobcats and other animals coexist with people, and the Washington Wolverine Project, an effort to monitor wolverines in the face of climate change. Identify urban wildlife for the Chicago Wildlife Watch , or contribute to wilderness projects documenting North American biodiversity with The Wilds' Wildlife Watch in Ohio , Cedar Creek: Eyes on the Wild in Minnesota , Michigan ZoomIN , Western Montana Wildlife and Snapshot Wisconsin .

"Spend your time at home virtually exploring the Minnesota backwoods,” writes the lead researcher of the Cedar Creek: Eyes on the Wild project. “Help us understand deer dynamics, possum populations, bear behavior, and keep your eyes peeled for elusive wolves!"

If being cooped up at home has you daydreaming about traveling, Snapshot Safari has six active animal identification projects. Try eyeing lions, leopards, cheetahs, wild dogs, elephants, giraffes, baobab trees and over 400 bird species from camera trap photos taken in South African nature reserves, including De Hoop Nature Reserve and Madikwe Game Reserve .

With South Sudan DiversityCam , researchers are using camera traps to study biodiversity in the dense tropical forests of southwestern South Sudan. Part of the Serenegeti Lion Project, Snapshot Serengeti needs the help of citizen scientists to classify millions of camera trap images of species traveling with the wildebeest migration.

Classify all kinds of monkeys with Chimp&See . Count, identify and track giraffes in northern Kenya . Watering holes host all kinds of wildlife, but that makes the locales hotspots for parasite transmission; Parasite Safari needs volunteers to help figure out which animals come in contact with each other and during what time of year.

Mount Taranaki in New Zealand is a volcanic peak rich in native vegetation, but native wildlife, like the North Island brown kiwi, whio/blue duck and seabirds, are now rare—driven out by introduced predators like wild goats, weasels, stoats, possums and rats. Estimate predator species compared to native wildlife with Taranaki Mounga by spotting species on camera trap images.

The Zoological Society of London’s (ZSL) Instant Wild app has a dozen projects showcasing live images and videos of wildlife around the world. Look for bears, wolves and lynx in Croatia ; wildcats in Costa Rica’s Osa Peninsula ; otters in Hampshire, England ; and both black and white rhinos in the Lewa-Borana landscape in Kenya.

Under the Sea

Researchers use a variety of technologies to learn about marine life and inform conservation efforts. Take, for example, Beluga Bits , a research project focused on determining the sex, age and pod size of beluga whales visiting the Churchill River in northern Manitoba, Canada. With a bit of training, volunteers can learn how to differentiate between a calf, a subadult (grey) or an adult (white)—and even identify individuals using scars or unique pigmentation—in underwater videos and images. Beluga Bits uses a “ beluga boat ,” which travels around the Churchill River estuary with a camera underneath it, to capture the footage and collect GPS data about the whales’ locations.

Many of these online projects are visual, but Manatee Chat needs citizen scientists who can train their ear to decipher manatee vocalizations. Researchers are hoping to learn what calls the marine mammals make and when—with enough practice you might even be able to recognize the distinct calls of individual animals.

Several groups are using drone footage to monitor seal populations. Seals spend most of their time in the water, but come ashore to breed. One group, Seal Watch , is analyzing time-lapse photography and drone images of seals in the British territory of South Georgia in the South Atlantic. A team in Antarctica captured images of Weddell seals every ten minutes while the seals were on land in spring to have their pups. The Weddell Seal Count project aims to find out what threats—like fishing and climate change—the seals face by monitoring changes in their population size. Likewise, the Año Nuevo Island - Animal Count asks volunteers to count elephant seals, sea lions, cormorants and more species on a remote research island off the coast of California.

With Floating Forests , you’ll sift through 40 years of satellite images of the ocean surface identifying kelp forests, which are foundational for marine ecosystems, providing shelter for shrimp, fish and sea urchins. A project based in southwest England, Seagrass Explorer , is investigating the decline of seagrass beds. Researchers are using baited cameras to spot commercial fish in these habitats as well as looking out for algae to study the health of these threatened ecosystems. Search for large sponges, starfish and cold-water corals on the deep seafloor in Sweden’s first marine park with the Koster seafloor observatory project.

The Smithsonian Environmental Research Center needs your help spotting invasive species with Invader ID . Train your eye to spot groups of organisms, known as fouling communities, that live under docks and ship hulls, in an effort to clean up marine ecosystems.

If art history is more your speed, two Dutch art museums need volunteers to start “ fishing in the past ” by analyzing a collection of paintings dating from 1500 to 1700. Each painting features at least one fish, and an interdisciplinary research team of biologists and art historians wants you to identify the species of fish to make a clearer picture of the “role of ichthyology in the past.”

Interesting Insects

Notes from Nature is a digitization effort to make the vast resources in museums’ archives of plants and insects more accessible. Similarly, page through the University of California Berkeley’s butterfly collection on CalBug to help researchers classify these beautiful critters. The University of Michigan Museum of Zoology has already digitized about 300,000 records, but their collection exceeds 4 million bugs. You can hop in now and transcribe their grasshopper archives from the last century . Parasitic arthropods, like mosquitos and ticks, are known disease vectors; to better locate these critters, the Terrestrial Parasite Tracker project is working with 22 collections and institutions to digitize over 1.2 million specimens—and they’re 95 percent done . If you can tolerate mosquito buzzing for a prolonged period of time, the HumBug project needs volunteers to train its algorithm and develop real-time mosquito detection using acoustic monitoring devices. It’s for the greater good!

For the Birders

Birdwatching is one of the most common forms of citizen science . Seeing birds in the wilderness is certainly awe-inspiring, but you can birdwatch from your backyard or while walking down the sidewalk in big cities, too. With Cornell University’s eBird app , you can contribute to bird science at any time, anywhere. (Just be sure to remain a safe distance from wildlife—and other humans, while we social distance ). If you have safe access to outdoor space—a backyard, perhaps—Cornell also has a NestWatch program for people to report observations of bird nests. Smithsonian’s Migratory Bird Center has a similar Neighborhood Nest Watch program as well.

Birdwatching is easy enough to do from any window, if you’re sheltering at home, but in case you lack a clear view, consider these online-only projects. Nest Quest currently has a robin database that needs volunteer transcribers to digitize their nest record cards.

You can also pitch in on a variety of efforts to categorize wildlife camera images of burrowing owls , pelicans , penguins (new data coming soon!), and sea birds . Watch nest cam footage of the northern bald ibis or greylag geese on NestCams to help researchers learn about breeding behavior.

Or record the coloration of gorgeous feathers across bird species for researchers at London’s Natural History Museum with Project Plumage .

Pretty Plants

If you’re out on a walk wondering what kind of plants are around you, consider downloading Leafsnap , an electronic field guide app developed by Columbia University, the University of Maryland and the Smithsonian Institution. The app has several functions. First, it can be used to identify plants with its visual recognition software. Secondly, scientists can learn about the “ the ebb and flow of flora ” from geotagged images taken by app users.

What is older than the dinosaurs, survived three mass extinctions and still has a living relative today? Ginko trees! Researchers at Smithsonian’s National Museum of Natural History are studying ginko trees and fossils to understand millions of years of plant evolution and climate change with the Fossil Atmospheres project . Using Zooniverse, volunteers will be trained to identify and count stomata, which are holes on a leaf’s surface where carbon dioxide passes through. By counting these holes, or quantifying the stomatal index, scientists can learn how the plants adapted to changing levels of carbon dioxide. These results will inform a field experiment conducted on living trees in which a scientist is adjusting the level of carbon dioxide for different groups.

Help digitize and categorize millions of botanical specimens from natural history museums, research institutions and herbaria across the country with the Notes from Nature Project . Did you know North America is home to a variety of beautiful orchid species? Lend botanists a handby typing handwritten labels on pressed specimens or recording their geographic and historic origins for the New York Botanical Garden’s archives. Likewise, the Southeastern U.S. Biodiversity project needs assistance labeling pressed poppies, sedums, valerians, violets and more. Groups in California , Arkansas , Florida , Texas and Oklahoma all invite citizen scientists to partake in similar tasks.

Historic Women in Astronomy

Become a transcriber for Project PHaEDRA and help researchers at the Harvard-Smithsonian Center for Astrophysics preserve the work of Harvard’s women “computers” who revolutionized astronomy in the 20th century. These women contributed more than 130 years of work documenting the night sky, cataloging stars, interpreting stellar spectra, counting galaxies, and measuring distances in space, according to the project description .

More than 2,500 notebooks need transcription on Project PhaEDRA - Star Notes . You could start with Annie Jump Cannon , for example. In 1901, Cannon designed a stellar classification system that astronomers still use today. Cecilia Payne discovered that stars are made primarily of hydrogen and helium and can be categorized by temperature. Two notebooks from Henrietta Swan Leavitt are currently in need of transcription. Leavitt, who was deaf, discovered the link between period and luminosity in Cepheid variables, or pulsating stars, which “led directly to the discovery that the Universe is expanding,” according to her bio on Star Notes .

Volunteers are also needed to transcribe some of these women computers’ notebooks that contain references to photographic glass plates . These plates were used to study space from the 1880s to the 1990s. For example, in 1890, Williamina Flemming discovered the Horsehead Nebula on one of these plates . With Star Notes, you can help bridge the gap between “modern scientific literature and 100 years of astronomical observations,” according to the project description . Star Notes also features the work of Cannon, Leavitt and Dorrit Hoffleit , who authored the fifth edition of the Bright Star Catalog, which features 9,110 of the brightest stars in the sky.

Microscopic Musings

Electron microscopes have super-high resolution and magnification powers—and now, many can process images automatically, allowing teams to collect an immense amount of data. Francis Crick Institute’s Etch A Cell - Powerhouse Hunt project trains volunteers to spot and trace each cell’s mitochondria, a process called manual segmentation. Manual segmentation is a major bottleneck to completing biological research because using computer systems to complete the work is still fraught with errors and, without enough volunteers, doing this work takes a really long time.

For the Monkey Health Explorer project, researchers studying the social behavior of rhesus monkeys on the tiny island Cayo Santiago off the southeastern coast of Puerto Rico need volunteers to analyze the monkeys’ blood samples. Doing so will help the team understand which monkeys are sick and which are healthy, and how the animals’ health influences behavioral changes.

Using the Zooniverse’s app on a phone or tablet, you can become a “ Science Scribbler ” and assist researchers studying how Huntington disease may change a cell’s organelles. The team at the United Kingdom's national synchrotron , which is essentially a giant microscope that harnesses the power of electrons, has taken highly detailed X-ray images of the cells of Huntington’s patients and needs help identifying organelles, in an effort to see how the disease changes their structure.

Oxford University’s Comprehensive Resistance Prediction for Tuberculosis: an International Consortium—or CRyPTIC Project , for short, is seeking the aid of citizen scientists to study over 20,000 TB infection samples from around the world. CRyPTIC’s citizen science platform is called Bash the Bug . On the platform, volunteers will be trained to evaluate the effectiveness of antibiotics on a given sample. Each evaluation will be checked by a scientist for accuracy and then used to train a computer program, which may one day make this process much faster and less labor intensive.

Out of This World

If you’re interested in contributing to astronomy research from the comfort and safety of your sidewalk or backyard, check out Globe at Night . The project monitors light pollution by asking users to try spotting constellations in the night sky at designated times of the year . (For example, Northern Hemisphere dwellers should look for the Bootes and Hercules constellations from June 13 through June 22 and record the visibility in Globe at Night’s app or desktop report page .)

For the amateur astrophysicists out there, the opportunities to contribute to science are vast. NASA's Wide-field Infrared Survey Explorer (WISE) mission is asking for volunteers to search for new objects at the edges of our solar system with the Backyard Worlds: Planet 9 project .

Galaxy Zoo on Zooniverse and its mobile app has operated online citizen science projects for the past decade. According to the project description, there are roughly one hundred billion galaxies in the observable universe. Surprisingly, identifying different types of galaxies by their shape is rather easy. “If you're quick, you may even be the first person to see the galaxies you're asked to classify,” the team writes.

With Radio Galaxy Zoo: LOFAR , volunteers can help identify supermassive blackholes and star-forming galaxies. Galaxy Zoo: Clump Scout asks users to look for young, “clumpy” looking galaxies, which help astronomers understand galaxy evolution.

If current events on Earth have you looking to Mars, perhaps you’d be interested in checking out Planet Four and Planet Four: Terrains —both of which task users with searching and categorizing landscape formations on Mars’ southern hemisphere. You’ll scroll through images of the Martian surface looking for terrain types informally called “spiders,” “baby spiders,” “channel networks” and “swiss cheese.”

Gravitational waves are telltale ripples in spacetime, but they are notoriously difficult to measure. With Gravity Spy , citizen scientists sift through data from Laser Interferometer Gravitational­-Wave Observatory, or LIGO , detectors. When lasers beamed down 2.5-mile-long “arms” at these facilities in Livingston, Louisiana and Hanford, Washington are interrupted, a gravitational wave is detected. But the detectors are sensitive to “glitches” that, in models, look similar to the astrophysical signals scientists are looking for. Gravity Spy teaches citizen scientists how to identify fakes so researchers can get a better view of the real deal. This work will, in turn, train computer algorithms to do the same.

Similarly, the project Supernova Hunters needs volunteers to clear out the “bogus detections of supernovae,” allowing researchers to track the progression of actual supernovae. In Hubble Space Telescope images, you can search for asteroid tails with Hubble Asteroid Hunter . And with Planet Hunters TESS , which teaches users to identify planetary formations, you just “might be the first person to discover a planet around a nearby star in the Milky Way,” according to the project description.

Help astronomers refine prediction models for solar storms, which kick up dust that impacts spacecraft orbiting the sun, with Solar Stormwatch II. Thanks to the first iteration of the project, astronomers were able to publish seven papers with their findings.

With Mapping Historic Skies , identify constellations on gorgeous celestial maps of the sky covering a span of 600 years from the Adler Planetarium collection in Chicago. Similarly, help fill in the gaps of historic astronomy with Astronomy Rewind , a project that aims to “make a holistic map of images of the sky.”

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Rachael Lallensack | READ MORE

Rachael Lallensack is the former assistant web editor for science and innovation at Smithsonian .

Stanford AI Projects Greenlighted in National AI Research Resource Pilot

Robotics and hospital computer vision projects receive NSF grants as part of an innovative pilot program to democratize AI research.

On May 6, the U.S. National Science Foundation and the Department of Energy awarded grants to 35 research teams for access to advanced computing resources through the National Artificial Intelligence Research Resource (NAIRR) pilot. This initial wave of  awarded projects includes scholars from across the U.S. who are working in clinical medicine, agriculture, biochemistry, computer science, informatics, and other interdisciplinary fields. Two Stanford AI projects — from the School of Engineering and School of Medicine — were selected to participate in the pilot.

Part of the 2023  Executive Order on the Safe, Secure, and Trustworthy Development and Use of AI, the NAIRR pilot launched in January 2024 with four stated goals: spur innovation, increase diversity of talent, improve capacity, and advance trustworthy AI. Stakeholders in academia, industry, and government see this program as a critical step toward strengthening U.S. leadership in AI and democratizing AI resources for public sector innovation.

“The NAIRR pilot is a landmark initiative that supports applied AI research and will benefit the entire nation,” said Stanford Institute for Human-Centered AI Deputy Director Russell Wald . “No AI scholar should be constrained by the high cost of compute resources and access to data to train their models.”

Most of the awarded projects are given computational time on NSF-funded supercomputer systems at the University of Illinois Urbana-Champaign, University of Texas at Austin, and Pittsburgh Supercomputing Center; additionally, the DOE will allocate resources at its Summit supercomputer at Oak Ridge National Laboratory and AI Testbed at Argonne National Laboratory to a few of the research teams.

Taking Reinforcement Learning into Visual Environments

A team from the Stanford Intelligent and Interactive Autonomous Systems Group ( ILIAD ), led by HAI Faculty Affiliate  Dorsa Sadigh , an assistant professor of computer science and of electrical engineering, submitted a proposal to continue groundbreaking work in the domain of human-robot and human-AI interactions. The project will focus on learning effective reward functions for robotics using large datasets and human feedback.

Reward functions are key to a machine learning technique called reinforcement learning, which works by training a large language model to maximize rewards. When humans provide feedback as part of the training process, the model learns how to make decisions that are aligned with human priorities. Stanford computer science PhD student Joey Hejna says that applying this technique to real-world robotics presents new challenges because it requires understanding the visual world, which is captured by modern visual-language models. Another challenge is that it’s not enough for the model to get the right result; how it arrives at that answer also matters. Researchers will want to make sure the robot operates safely and reliably around people, and they may need to personalize how certain robots interact with humans – in a home-care setting, for example. 

“Training robot models that can work in the real world will require a massive amount of compute power," Hejna explains. “High-performing VLMs usually have at least 7 billion parameters. This project would not be possible without access to the GPU hours from the National Science Foundation.”

Autonomous Patient Monitoring in the ICU

The second Stanford project to receive NSF support comes out of the School of Medicine’s  Clinical Excellence Research Center (CERC), dedicated to reducing the cost of patient care. Part of a multiyear initiative to enhance healthcare environments by integrating smart sensors and AI algorithms, the awarded project seeks to develop computer vision models that can collect and analyze comprehensive video data from ICU patient rooms to help doctors and nurses better track patients’ health.

A key aspect of the research is to address potential biases in the AI models used for predicting patient status and monitoring clinical activities. By analyzing demographic data from electronic health records, the team aims to identify and correct algorithmic biases that might affect predictions across different ethnicities and sexes. “The ultimate goal is to develop bias-free algorithms and propose interventions to ensure fair and accurate patient monitoring and care in ICUs,” said the team’s lead scholar,  Dr. Kevin Schulman .

Leadership from Stanford HAI

HAI’s leadership team has been a driving force behind the creation of a National AI Research Resource since the founding of the institute in 2019. Co-Directors Fei-Fei Li and John Etchemendy started to organize universities and tech companies in 2020, and they initiated the call for a government-led task force to establish the program.

“From our earliest conversations with universities, industry executives, and policymakers, we felt that American innovation was at stake,” said Li. “We knew that support from Congress and the president could have a meaningful impact on the future of AI technology.”

According to Etchemendy, “The start of this pilot program marks a historic moment for U.S. researchers and educators. It will rebalance the AI ecosystem by supporting mission-driven researchers who want AI to serve the public good.”

Reflecting on the years of strategic planning and dedication that have led to this milestone, Wald added, “John and Fei-Fei’s vision, combined with the extraordinary support of the Stanford community and our country’s policymakers, is leading to greater access to AI research not just at Stanford but at all of America’s universities.”

Immediately following the May 6 announcement of initial awards, the NAIRR pilot opened the application window for a second wave of projects. With contributions from industry partners, a wider range of technical resources are going to be available for applicants this round, including access to advanced computing systems, cloud computing platforms, foundation models, software and privacy-enhancing tools, collaborations to train models, and education platforms. 

Researchers and educators can apply for access to these resources and view descriptions of the first cohort projects on  the NAIRR pilot website .

Stanford HAI’s mission is to advance AI research, education, policy and practice to improve the human condition.  Learn more . 

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ACS Project SEED Program – Bringing Research and High School Students Together

This summer, 17 high school students in the American Chemical Society Snake River Section will have the opportunity to conduct research through the ACS Project SEED program.

Project SEED, originally “Summer Experiences for the Economically Disadvantaged,” was born in 1968. Now 56 years old, the program has provided hands-on summer research experiences and webinars to over 13,000 students across the U.S. and its territories. The Project SEED Mission is “to provide sustained STEM research, learning, and growth opportunities for high school students with diverse identities and socioeconomic backgrounds so they can be empowered to advance and enrich the chemical science enterprise.”

Each year, high school students spend 10 weeks in an industry lab or at host institutions like Boise State University working alongside PIs and qualified mentors on cutting-edge research projects. In addition to the technical skills learned in the lab, students will participate in professional development activities to enhance skills in time management, teamwork, and research presentation. The Project SEED webinars cover topics such as personal and chemical safety, career exploration, college readiness, resume building, and mental health and wellness. The summer experience is culminated in a poster presentation where the student present their research, with this year’s presentations being held at the Idaho Conference on Undergraduate Research.

The ACS Snake River Section Project SEED coordinator is Boise State’s Dr. Don Warner, a professor in the Department of Chemistry and Biochemistry. This year he placed 17 students, 8 of whom are returning participants. He received 70 applications and conducted 24 initial interviews to fill the 9 open spots. Two students are going to Northwest Nazarene University to work with Jerry Harris on synthesizing and characterizing zinc oxide nanoparticles with enhanced antimicrobial properties. Two more will go to Danny Xu’s lab at Idaho State University – Meridian to research the effects of Lunar and Martian regolith on zebrafish.

The remaining 13 students will be working in several laboratories across campus at Boise State University this summer. The PIs hosting students, and their projects, are:

• Oliviero Andreussi: Computational Study of Materials for Electro-Catalysis
• Leonora Bittleston: 4: Exploring the effects of leaf chemistry on microbial colonization
• Eric Brown: Development of molecules that inhibit a bacteria’s ability to cause disease
• Ken Cornell: Analysis of Antimicrobial Activity of Nanoparticles and Organometallic Complexes
• Jenée Cyran & Brian McClain: Developing innovative Physical Chemistry Lab Modules
• Owen McDougal: Chemistry of Food Systems
• Konrad Meister: Cool Molecules: Understanding the Mode of Action of Ice-Binding Macromolecules
• Don Warner: Synthesis of small molecules for inhibition of tumor metastasis
• Claire Xiong: Sodium Ion Batteries

Participants in the Project SEED program are awarded a stipend for their efforts, providing low-income students the opportunity to participate while earning money to help support their families. This crucial funding in 2024 is largely from the American Chemical Society, but also contributed to by Northwest Nazarene University, the ACS Snake River Local Section, and from Boise State University’s College of Arts & Sciences, Research and Economic Development, Materials Science and Engineering, Chemistry & Biochemistry, several individual PIs, and the university itself. Some of the program’s graduates will also receive scholarships from Project SEED to help fund their undergraduate education.

For more information on this amazing program, visit ACS News to read Project SEED’s Impact Continues to Grow .

Interested in getting involved? Visit Project SEED on the American Chemical Society’s webpage.

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Simplified Review Framework for Research Project Grants (RPGs) Webinar Resources Available 

Did you miss the webinar on the implementation of the simplified review framework for RPGs? Not to worry, the presentation resources are now available! Reference the slides and transcript , or dive right in to the video , which includes sections on:  

• Background   
• Overview of the simplified review framework   
• Preparing for and tracking changes to funding opportunities   
• Tips for applicants   
• Communication and training   

For more resources, see the event page and the Simplifying Review of Research Project Grant Applications page .  

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More From Forbes

5 highest paying skills for project managers in 2024, from research.

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To remain competitive and gain an edge as a project management professional, it helps to learn one ... [+] or more of these five critical skills this year

Within a competitive job market in which 25 million project managers are projected to be in demand over the next few years, it's critical for aspiring and existing project management professionals to stay ahead of the curve so they can secure the highest-paying roles. While the project management profession in itself is a well-remunerated industry, with U.S. median salaries jumping to as high as $120,000, that doesn't necessarily mean that you can sit back, relax, and assume you're worthy of a six-figure salary.

There are things that lie within your power, which you can do to dramatically skyrocket your earnings.

When exploring how to increase and even multiply your salary as a project manager, it's best to look into what are the highest-paying, in-demand skills within the project management industry, so that you can position yourself as best suited for a promotion, or as a star candidate when job-searching.

Highest-Paying In-Demand Skills For Project Managers

The compensation and salary data company, PayScale, compiled a list of high-paying skills which include a combination of hard, technical skills, and soft or power skills for those within the project industry.

It's worth noting that there are some industries in which the impact of these skills on your pay increase will be more visible than others. For example, considering programme/project management within the technology industry, you can expect to earn more for your skill set, as the tech industry is renowned for offering the highest salaries to project and program management professionals. As such, some of the skills listed below are more specific to the technology industry.

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However, many of these skills are equally in demand in other industries as well, so they can still be applicable and relevant to you.

These competencies include:

1. Agile Software Development

Using the agile software development approach for building and delivering software products entails prioritising flexibility responsiveness and adaptability to change as well as collaboration. Following this framework, you and your team would be working in sprints, (short iterations) which allows you to make incremental progress and quickly respond to stakeholder requirements and feedback to meet their needs.

This is the highest-paying skill for project managers, with Payscale data revealing that it can boost your earnings by 47%. Coursera and Skillsoft are two of the amazing resources that are available for you to learn this skill.

The tech industry offers the highest salaries for PMs

2. Business Analysis

Analytical thinking is listed in the World Economic Forum's Future of Jobs Report 2023 as the number one skill needed by professionals over the next few years.

Business analysis, in simple terms, is when you identify business needs and research solutions for them. This skill comes handy in your PM role, as you will naturally be working with stakeholders on a regular basis to gather and analyze data on their needs and define requirements, and then propose the best solution with your program or project. This skill improves salary prospects by up to 43%.

3. Engineering Design

Next on the list is engineering design, which is of course more specifically focused on the technology industry. This involves taking the results of your business analysis, and creating detailed plans and specifications, including prototyping and testing, to ensure you deliver a high-quality product that satisfies your stakeholders' needs. This skill is more relatable to product managers, and provides a 14% uptake in salary.

4. Risk Management/Risk Control

With all the changes that are occurring to disrupt industries in 2024, it's no wonder that risk management and risk control are highly in-demand skills for project and program managers to possess. This skill also has the potential for a 14% salary boost, according to Payscale analysis.

You can learn more about how to comprehensively manage and plan for risk by undertaking courses and certifications such as those offered by the Institute of Risk Management, which are globally recognized.

5. Strategy

Strategic thinking is a trademark of leadership, and of exceptional program and project management. You need to be able to steer your project team in the right direction to achieve successful project outcomes, and this means you'll need to have a solid strategy that is clearly articulated so that everyone is on the same page. Setting clear goals and objectives, and assigning the right team members to fulfil each task according to their strengths requires some practice to get it right, but it can be achieved if you're persistent and intentional. Possessing and showcasing this skill results in a 12% salary increase.

Risk management skills helps ensure your project is prepared for worst-case scenarios and minimizes ... [+] negative outcomes, including those that could affect your job directly

By investing in yourself this year by upskilling in one or more of these five essential competencies, you can position yourself to successfully meet the evolving demands of your stakeholders and the project management industry, and unlock numerous career-building and salary-boosting opportunities.

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Facility for Rare Isotope Beams

At michigan state university, international research team uses wavefunction matching to solve quantum many-body problems, new approach makes calculations with realistic interactions possible.

FRIB researchers are part of an international research team solving challenging computational problems in quantum physics using a new method called wavefunction matching. The new approach has applications to fields such as nuclear physics, where it is enabling theoretical calculations of atomic nuclei that were previously not possible. The details are published in Nature (“Wavefunction matching for solving quantum many-body problems”) .

Ab initio methods and their computational challenges

An ab initio method describes a complex system by starting from a description of its elementary components and their interactions. For the case of nuclear physics, the elementary components are protons and neutrons. Some key questions that ab initio calculations can help address are the binding energies and properties of atomic nuclei not yet observed and linking nuclear structure to the underlying interactions among protons and neutrons.

Yet, some ab initio methods struggle to produce reliable calculations for systems with complex interactions. One such method is quantum Monte Carlo simulations. In quantum Monte Carlo simulations, quantities are computed using random or stochastic processes. While quantum Monte Carlo simulations can be efficient and powerful, they have a significant weakness: the sign problem. The sign problem develops when positive and negative weight contributions cancel each other out. This cancellation results in inaccurate final predictions. It is often the case that quantum Monte Carlo simulations can be performed for an approximate or simplified interaction, but the corresponding simulations for realistic interactions produce severe sign problems and are therefore not possible.

Using ‘plastic surgery’ to make calculations possible

The new wavefunction-matching approach is designed to solve such computational problems. The research team—from Gaziantep Islam Science and Technology University in Turkey; University of Bonn, Ruhr University Bochum, and Forschungszentrum Jülich in Germany; Institute for Basic Science in South Korea; South China Normal University, Sun Yat-Sen University, and Graduate School of China Academy of Engineering Physics in China; Tbilisi State University in Georgia; CEA Paris-Saclay and Université Paris-Saclay in France; and Mississippi State University and the Facility for Rare Isotope Beams (FRIB) at Michigan State University (MSU)—includes  Dean Lee , professor of physics at FRIB and in MSU’s Department of Physics and Astronomy and head of the Theoretical Nuclear Science department at FRIB, and  Yuan-Zhuo Ma , postdoctoral research associate at FRIB.

“We are often faced with the situation that we can perform calculations using a simple approximate interaction, but realistic high-fidelity interactions cause severe computational problems,” said Lee. “Wavefunction matching solves this problem by doing plastic surgery. It removes the short-distance part of the high-fidelity interaction, and replaces it with the short-distance part of an easily computable interaction.”

This transformation is done in a way that preserves all of the important properties of the original realistic interaction. Since the new wavefunctions look similar to that of the easily computable interaction, researchers can now perform calculations using the easily computable interaction and apply a standard procedure for handling small corrections called perturbation theory.  A team effort

The research team applied this new method to lattice quantum Monte Carlo simulations for light nuclei, medium-mass nuclei, neutron matter, and nuclear matter. Using precise ab initio calculations, the results closely matched real-world data on nuclear properties such as size, structure, and binding energies. Calculations that were once impossible due to the sign problem can now be performed using wavefunction matching.

“It is a fantastic project and an excellent opportunity to work with the brightest nuclear scientist s in FRIB and around the globe,” said Ma. “As a theorist , I'm also very excited about programming and conducting research on the world's most powerful exascale supercomputers, such as Frontier , which allows us to implement wavefunction matching to explore the mysteries of nuclear physics.”

While the research team focused solely on quantum Monte Carlo simulations, wavefunction matching should be useful for many different ab initio approaches, including both classical and  quantum computing calculations. The researchers at FRIB worked with collaborators at institutions in China, France, Germany, South Korea, Turkey, and United States.

“The work is the culmination of effort over many years to handle the computational problems associated with realistic high-fidelity nuclear interactions,” said Lee. “It is very satisfying to see that the computational problems are cleanly resolved with this new approach. We are grateful to all of the collaboration members who contributed to this project, in particular, the lead author, Serdar Elhatisari.”

This material is based upon work supported by the U.S. Department of Energy, the U.S. National Science Foundation, the German Research Foundation, the National Natural Science Foundation of China, the Chinese Academy of Sciences President’s International Fellowship Initiative, Volkswagen Stiftung, the European Research Council, the Scientific and Technological Research Council of Turkey, the National Natural Science Foundation of China, the National Security Academic Fund, the Rare Isotope Science Project of the Institute for Basic Science, the National Research Foundation of Korea, the Institute for Basic Science, and the Espace de Structure et de réactions Nucléaires Théorique.

Michigan State University operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), supporting the mission of the DOE-SC Office of Nuclear Physics. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science.

USC OORI Awards Four Faculty-led Projects under GenAI Program

The University of Southern California (USC) Office of Research and Innovation (OORI) has announced four new awardees named under the Generative Artificial Intelligence (GenAI) Research Program.

USC has made recent advances across the university to enhance research efforts in the field of artificial intelligence (AI) and Generative AI (GenAI). For example, USC recently launched the Center for Generative Artificial Intelligence and Society to examine how GenAI is reshaping the way humans live, work, learn, and play, and how it can be leveraged for the common good. Additionally, OORI has worked to implement support services and available funds for faculty interested in pursuing critical and timely cutting-edge research on GenAI.

Through the internally funded GenAI Research Program, OORI provides funding to explore the transformative impact of GenAI on the world, including its potential capacity to unleash human potential. Funding is available for researchers from across schools and disciplines. The GenAI Research Program consists of three subprograms: (1) Building GenAI Research Networks; (2) GenAI Research Award; and (3) Collaborative GenAI Research Award.

The 2024 GenAI Research Program awardees are as follows:

• Proposal Title: Simulation of realistic motion artifacts and correction of motion-affected MRI Images via a conditional diffusion probabilistic model
• Proposal Title: Quantum Empowered Generative Artificial Intelligence
• Proposal Title: Generative AI-Based Tractometry to Reveal Brain Fiber Tract Abnormalities in Alzheimer’s and Parkinson’s Disease
• Proposal Title: Large Language Models-Based AI Solutions for Clinical Trial Enrollment and Design

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AI Is Everybody’s Business

This briefing presents three principles to guide business leaders when making AI investments: invest in practices that build capabilities required for AI, involve all your people in your AI journey, and focus on realizing value from your AI projects. The principles are supported by the MIT CISR data monetization research, and the briefing illustrates them using examples from the Australia Taxation Office and CarMax. The three principles apply to any kind of AI, defined as technology that performs human-like cognitive tasks; subsequent briefings will present management advice distinct to machine learning and generative tools, respectively.

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Author Barb Wixom reads this research briefing as part of our audio edition of the series. Follow the series on SoundCloud.

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Today, everybody across the organization is hungry to know more about AI. What is it good for? Should I trust it? Will it take my job? Business leaders are investing in massive training programs, partnering with promising vendors and consultants, and collaborating with peers to identify ways to benefit from AI and avoid the risk of AI missteps. They are trying to understand how to manage AI responsibly and at scale.

Our book Data Is Everybody’s Business: The Fundamentals of Data Monetization describes how organizations make money using their data.[foot]Barbara H. Wixom, Cynthia M. Beath, and Leslie Owens, Data Is Everybody's Business: The Fundamentals of Data Monetization , (Cambridge: The MIT Press, 2023), https://mitpress.mit.edu/9780262048217/data-is-everybodys-business/ .[/foot] We wrote the book to clarify what data monetization is (the conversion of data into financial returns) and how to do it (by using data to improve work, wrap products and experiences, and sell informational solutions). AI technology’s role in this is to help data monetization project teams use data in ways that humans cannot, usually because of big complexity or scope or required speed. In our data monetization research, we have regularly seen leaders use AI effectively to realize extraordinary business goals. In this briefing, we explain how such leaders achieve big AI wins and maximize financial returns.

Using AI in Data Monetization

AI refers to the ability of machines to perform human-like cognitive tasks.[foot]See Hind Benbya, Thomas H. Davenport, and Stella Pachidi, “Special Issue Editorial: Artificial Intelligence in Organizations: Current State and Future Opportunities , ” MIS Quarterly Executive 19, no. 4 (December 2020), https://aisel.aisnet.org/misqe/vol19/iss4/4 .[/foot] Since 2019, MIT CISR researchers have been studying deployed data monetization initiatives that rely on machine learning and predictive algorithms, commonly referred to as predictive AI.[foot]This research draws on a Q1 to Q2 2019 asynchronous discussion about AI-related challenges with fifty-three data executives from the MIT CISR Data Research Advisory Board; more than one hundred structured interviews with AI professionals regarding fifty-two AI projects from Q3 2019 to Q2 2020; and ten AI project narratives published by MIT CISR between 2020 and 2023.[/foot] Such initiatives use large data repositories to recognize patterns across time, draw inferences, and predict outcomes and future trends. For example, the Australian Taxation Office (ATO) used machine learning, neural nets, and decision trees to understand citizen tax-filing behaviors and produce respectful nudges that helped citizens abide by Australia’s work-related expense policies. In 2018, the nudging resulted in AUD$113 million in changed claim amounts.[foot]I. A. Someh, B. H. Wixom, and R. W. Gregory, “The Australian Taxation Office: Creating Value with Advanced Analytics,” MIT CISR Working Paper No. 447, November 2020, https://cisr.mit.edu/publication/MIT_CISRwp447_ATOAdvancedAnalytics_SomehWixomGregory .[/foot]

In 2023, we began exploring data monetization initiatives that rely on generative AI.[foot]This research draws on two asynchronous generative AI discussions (Q3 2023, N=35; Q1 2024, N=34) regarding investments and capabilities and roles and skills, respectively, with data executives from the MIT CISR Data Research Advisory Board. It also draws on in-progress case studies with large organizations in the publishing, building materials, and equipment manufacturing industries.[/foot] This type of AI analyzes vast amounts of text or image data to discern patterns in them. Using these patterns, generative AI can create new text, software code, images, or videos, usually in response to user prompts. Organizations are now beginning to openly discuss data monetization initiative deployments that include generative AI technologies. For example, used vehicle retailer CarMax reported using OpenAI’s ChatGPT chatbot to help aggregate customer reviews and other car information from multiple data sets to create helpful, easy-to-read summaries about individual used cars for its online shoppers. At any point in time, CarMax has on average 50,000 cars on its website, so to produce such content without AI the company would require hundreds of content writers and years of time; using ChatGPT, the company’s content team can generate summaries in hours.[foot]Paula Rooney, “CarMax drives business value with GPT-3.5,” CIO , May 5, 2023, https://www.cio.com/article/475487/carmax-drives-business-value-with-gpt-3-5.html ; Hayete Gallot and Shamim Mohammad, “Taking the car-buying experience to the max with AI,” January 2, 2024, in Pivotal with Hayete Gallot, produced by Larj Media, podcast, MP3 audio, https://podcasts.apple.com/us/podcast/taking-the-car-buying-experience-to-the-max-with-ai/id1667013760?i=1000640365455 .[/foot]

Big advancements in machine learning, generative tools, and other AI technologies inspire big investments when leaders believe the technologies can help satisfy pent-up demand for solutions that previously seemed out of reach. However, there is a lot to learn about novel technologies before we can properly manage them. In this year’s MIT CISR research, we are studying predictive and generative AI from several angles. This briefing is the first in a series; in future briefings we will present management advice specific to machine learning and generative tools. For now, we present three principles supported by our data monetization research to guide business leaders when making AI investments of any kind: invest in practices that build capabilities required for AI, involve all your people in your AI journey, and focus on realizing value from your AI projects.

Principle 1: Invest in Practices That Build Capabilities Required for AI

Succeeding with AI depends on having deep data science skills that help teams successfully build and validate effective models. In fact, organizations need deep data science skills even when the models they are using are embedded in tools and partner solutions, including to evaluate their risks; only then can their teams make informed decisions about how to incorporate AI effectively into work practices. We worry that some leaders view buying AI products from providers as an opportunity to use AI without deep data science skills; we do not advise this.

But deep data science skills are not enough. Leaders often hire new talent and offer AI literacy training without making adequate investments in building complementary skills that are just as important. Our research shows that an organization’s progress in AI is dependent on having not only an advanced data science capability, but on having equally advanced capabilities in data management, data platform, acceptable data use, and customer understanding.[foot]In the June 2022 MIT CISR research briefing, we described why and how organizations build the five advanced data monetization capabilities for AI. See B. H. Wixom, I. A. Someh, and C. M. Beath, “Building Advanced Data Monetization Capabilities for the AI-Powered Organization,” MIT CISR Research Briefing, Vol. XXII, No. 6, June 2022, https://cisr.mit.edu/publication/2022_0601_AdvancedAICapabilities_WixomSomehBeath .[/foot] Think about it. Without the ability to curate data (an advanced data management capability), teams cannot effectively incorporate a diverse set of features into their models. Without the ability to oversee the legality and ethics of partners’ data use (an advanced acceptable data use capability), teams cannot responsibly deploy AI solutions into production.

It’s no surprise that ATO’s AI journey evolved in conjunction with the organization’s Smarter Data Program, which ATO established to build world-class data analytics capabilities, and that CarMax emphasizes that its governance, talent, and other data investments have been core to its generative AI progress.

Capabilities come mainly from learning by doing, so they are shaped by new practices in the form of training programs, policies, processes, or tools. As organizations undertake more and more sophisticated practices, their capabilities get more robust. Do invest in AI training—but also invest in practices that will boost the organization’s ability to manage data (such as adopting a data cataloging tool), make data accessible cost effectively (such as adopting cloud policies), improve data governance (such as establishing an ethical oversight committee), and solidify your customer understanding (such as mapping customer journeys). In particular, adopt policies and processes that will improve your data governance, so that data is only used in AI initiatives in ways that are consonant with your organization's values and its regulatory environment.

Principle 2: Involve All Your People in Your AI Journey

Data monetization initiatives require a variety of stakeholders—people doing the work, developing products, and offering solutions—to inform project requirements and to ensure the adoption and confident use of new data tools and behaviors.[foot]Ida Someh, Barbara Wixom, Michael Davern, and Graeme Shanks, “Configuring Relationships between Analytics and Business Domain Groups for Knowledge Integration, ” Journal of the Association for Information Systems 24, no. 2 (2023): 592-618, https://cisr.mit.edu/publication/configuring-relationships-between-analytics-and-business-domain-groups-knowledge .[/foot] With AI, involving a variety of stakeholders in initiatives helps non-data scientists become knowledgeable about what AI can and cannot do, how long it takes to deliver certain kinds of functionality, and what AI solutions cost. This, in turn, helps organizations in building trustworthy models, an important AI capability we call AI explanation (AIX).[foot]Ida Someh, Barbara H. Wixom, Cynthia M. Beath, and Angela Zutavern, “Building an Artificial Intelligence Explanation Capability,” MIS Quarterly Executive 21, no. 2 (2022), https://cisr.mit.edu/publication/building-artificial-intelligence-explanation-capability .[/foot]

For example, at ATO, data scientists educated business colleagues on the mechanics and results of models they created. Business colleagues provided feedback on the logic used in the models and helped to fine-tune them, and this interaction helped everyone understand how the AI made decisions. The data scientists provided their model results to ATO auditors, who also served as a feedback loop to the data scientists for improving the model. The data scientists regularly reported on initiative progress to senior management, regulators, and other stakeholders, which ensured that the AI team was proactively creating positive benefits without neglecting negative external factors that might surface.

Given the consumerization of generative AI tools, we believe that pervasive worker involvement in ideating, building, refining, using, and testing AI models and tools will become even more crucial to deploying fruitful AI projects—and building trust that AI will do the right thing in the right way at the right time.

Principle 3: Focus on Realizing Value From Your AI Projects

AI is costly—just add up your organization’s expenses in tools, talent, and training. AI needs to pay off, yet some organizations become distracted with endless experimentation. Others get caught up in finding the sweet spot of the technology, ignoring the sweet spot of their business model. For example, it is easy to become enamored of using generative AI to improve worker productivity, rolling out tools for employees to write better emails and capture what happened in meetings. But unless those activities materially impact how your organization makes money, there likely are better ways to spend your time and money.

Leaders with data monetization experience will make sure their AI projects realize value in the form of increased revenues or reduced expenses by backing initiatives that are clearly aligned with real challenges and opportunities. That is step one. In our research, the leaders that realize value from their data monetization initiatives measure and track their outcomes, especially their financial outcomes, and they hold someone accountable for achieving the desired financial returns. At CarMax, a cross-functional team owned the mission to provide better website information for used car shoppers, a mission important to the company’s sales goals. Starting with sales goals in mind, the team experimented with and then chose a generative AI solution that would enhance the shopper experience and increase sales.

Figure 1: Three Principles for Getting Value from AI Investments

The three principles are based on the following concepts from MIT CISR data research: 1. Data liquidity: the ease of data asset recombination and reuse 2. Data democracy: an organization that empowers employees in the access and use of data 3. Data monetization: the generation of financial returns from data assets

Managing AI Using a Data Monetization Mindset

AI has and always will play a big role in data monetization. It’s not a matter of whether to incorporate AI, but a matter of how to best use it. To figure this out, quantify the outcomes of some of your organization’s recent AI projects. How much money has the organization realized from them? If the answer disappoints, then make sure the AI technology value proposition is a fit for your organization’s most important goals. Then assign accountability for ensuring that AI technology is applied in use cases that impact your income statements. If the AI technology is not a fit for your organization, then don’t be distracted by media reports of the AI du jour.

Understanding your AI technology investments can be hard if your organization is using AI tools that are bundled in software you purchase or are built for you by a consultant. To set yourself up for success, ask your partners to be transparent with you about the quality of data they used to train their AI models and the data practices they relied on. Do their answers persuade you that their tools are trustworthy? Is it obvious that your partner is using data compliantly and is safeguarding the model from producing bad or undesired outcomes? If so, make sure this good news is shared with the people in your organization and those your organization serves. If not, rethink whether to break with your partner and find another way to incorporate the AI technology into your organization, such as by hiring people to build it in-house.

To paraphrase our book’s conclusion: When people actively engage in data monetization initiatives using AI , they learn, and they help their organization learn. Their engagement creates momentum that initiates a virtuous cycle in which people’s engagement leads to better data and more bottom-line value, which in turn leads to new ideas and more engagement, which further improves data and delivers more value, and so on. Imagine this happening across your organization as all people everywhere make it their business to find ways to use AI to monetize data.

This is why AI, like data, is everybody’s business.

© 2024 MIT Center for Information Systems Research, Wixom and Beath. MIT CISR Research Briefings are published monthly to update the center’s member organizations on current research projects.

Related Publications

Talking Points

Ai, like data, is everybody's business.

Working Paper: Vignette

The australian taxation office: creating value with advanced analytics.

Research Briefing

Building advanced data monetization capabilities for the ai-powered organization.

Building AI Explanation Capability for the AI-Powered Organization

What is Data Monetization?

About the researchers.

Barbara H. Wixom, Principal Research Scientist, MIT Center for Information Systems Research (CISR)

Cynthia M. Beath, Professor Emerita, University of Texas and Academic Research Fellow, MIT CISR

Mit center for information systems research (cisr).

Founded in 1974 and grounded in MIT's tradition of combining academic knowledge and practical purpose, MIT CISR helps executives meet the challenge of leading increasingly digital and data-driven organizations. We work directly with digital leaders, executives, and boards to develop our insights. Our consortium forms a global community that comprises more than seventy-five organizations.

MIT CISR Associate Members

MIT CISR wishes to thank all of our associate members for their support and contributions.

MIT CISR's Mission Expand

MIT CISR helps executives meet the challenge of leading increasingly digital and data-driven organizations. We provide insights on how organizations effectively realize value from approaches such as digital business transformation, data monetization, business ecosystems, and the digital workplace. Founded in 1974 and grounded in MIT’s tradition of combining academic knowledge and practical purpose, we work directly with digital leaders, executives, and boards to develop our insights. Our consortium forms a global community that comprises more than seventy-five organizations.

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BTPI will research relationship between Bitcoin and financial freedom

By giles morris cornell jeb e. brooks school of public policy.

The Brooks School Tech Policy Institute (BTPI) has announced a $1M project to study financial freedom in countries with authoritarian governments. Led by BTPI Director Sarah Kreps , John L. Wetherill Professor in the Department of Government in the College of Arts & Sciences and the Cornell Jeb E. Brooks School of Public Policy, the research will employ quantitative and qualitative approaches to understanding the use of Bitcoin and stablecoins by individuals around the world.  

“If you live in a place where the government silences its critics by threatening their assets or where you cannot trust the local banking system, you understand the importance of financial freedom to democracy,” said Kreps. “We want to study how people in these countries are using Bitcoin and stablecoins in the pursuit of their financial security.”

BTPI Director Dr. Sarah Kreps

The innovative approach to purpose-driven research is designed to build a framework for the creation of a Bitcoin and stablecoins adoption index that would map and analyze uptake globally. Supported by funding from Human Rights Foundation– a nonpartisan, nonprofit organization that promotes and protects human rights globally, with a focus on closed societies– and the Reynolds Foundation– a family foundation dedicated to supporting medical and spinal cord research and treatment, education, and democracy and freedom– the project is scheduled to kick off in July 2024 and conclude in 2026. 

Reynolds Foundation president and CEO Dr. Álvaro Salas Castro MPA '14 explained the multimodal and collaborative nature of the inquiry would lead to wider access to knowledge at a critical moment in global policy.

"The Tech Policy Institute at Cornell University's Brooks School of Public Policy stands as a crucial center for investigating the intricate relationship between emerging technology and global politics. Through a dedicated focus on critical issues such as artificial intelligence, cybersecurity, and digital privacy regulations, the Institute's interdisciplinary research aims to shed light on the complexities of our rapidly evolving technological landscape," said Dr. Salas Castro. "As Bitcoin adoption continues to exert influence over the global economic system, the Institute's steadfast commitment to fostering collaboration among scholars, policymakers, and industry leaders aligns seamlessly with the Reynolds Foundation's vision to support a network of knowledge-sharing that harnesses this technology for societal benefit."

According to Professor Kreps, the project will focus on about 12 countries, including India, Nigeria, El Salvador, Indonesia, and Turkey, and investigate Bitcoin and stablecoin uptake.  Kreps and her research team will partner with a major global research firm to develop and deliver surveys to 1,000 participants in each country that query not just adoption behaviors on the basis of demographic within each country but also perceptions and attitudes toward these digital currencies. A research team that includes undergraduate students will then conduct interviews to dig deeper into the basis for use.

According to HRF chief strategy officer Alex Gladstein, the combination of survey data and qualitative research in countries where relatively little is known about the use of Bitcoin and stablecoins represents a new approach to creating a baseline of understanding about their potential to enhance financial freedom around the world. 

"Bitcoin continues to grow into a bigger part of the global economic system. Today we have nation-state adoption, widespread mining operations on all continents, spot Exchange Traded Funds (ETFs) trading in the United States, and recent all-time-highs in price. The Human Rights Foundation has also observed that human rights groups and nonprofits are adopting Bitcoin in order to challenge financial repression from authoritarian regimes," said Gladstein. "This research under Professor Kreps will illuminate exactly who out there in the world is using Bitcoin and dollar-substitute stable coins, and why."

The goals of the financial freedom research project include:

• Increasing shared understanding of the factors driving cryptocurrency adoption, usage patterns, and the broader implications for financial inclusion and technological innovation.
• Assessing the ability of policymakers, industry stakeholders, and community organizations to make informed decisions regarding regulatory frameworks, product development, and educational initiatives related to cryptocurrencies.
• Expanding access to financial services and economic opportunities for individuals who are underserved or excluded by traditional banking systems.
• Raising public awareness and understanding of cryptocurrency technology, its potential benefits, risks, and implications for individuals and society.

“Researchers have posited a number of different reasons why citizens in these countries might use crypto and our research will probe these mechanisms of uptake to understand motivations and goals and whether these vary depending on region or type of government,” said Kreps. 

Giles Morris is assistant dean for communications in the Cornell Jeb E. Brooks School of Public Policy.

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ONE (1) research grant for candidates with MSc degree with reference number BI|2024/536 is now available under the scope of project Center for Responsible AI – Refª C628696807-00454142

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Center for Responsible AI -             C628696807-00454142

BI|2024/536

INESC-ID - Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa is a R&D institute dedicated to advanced research and development in the fields of Information Technologies, Electronics, Communications, and Energy. INESC-ID has participated in more than 50 research projects funded by the European Union and more than 190 funded by national entities. Until today, our researchers have published more than 700 papers in international journal papers, more than 3000 papers in international conferences, and have registered 15 patents and/or brands.

1 | RESEARCH GRANT TYPE

ONE (1) research grant for candidates with MSc degree with reference number BI|2024/536   is now available under the scope of project Center for Responsible AI – Refª C628696807-00454142 funded by Recovery and Resilience Plan (RRP)   https://recuperarportugal.gov.pt/ and by european funds Next Generation EU, under the following conditions:

2 | DURATION

FOUR (4) months , starting in September 2024   

-     Renewable, if the candidate is enrolled in a PhD program -  art. 6º, n.4 c)

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf

subject to suitable performance within the period of the project, not exceeding the maximum period set by FCT for such grants – 4 years (included contract renewals)

-     Renewable, if the candidate is enrolled in a non-degree programme – art. 6º, n. 4 a)

https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf  

subject to suitable performance within the period of the project, not exceeding the maximum period set by FCT for such grants – 1 year (included contract renewals)

3 | LEGISLATION

A fellowship contract will be celebrated according to:

• Law 40/2004 of 18 th of August (Scientific Research Fellow Status) and its successive amendments, including the amendments introduced by the Decree Law n. 123/2019 of 28 th of August  https://dre.pt/web/guest/legislacao-consolidada/-/lc/124281176/201912061112/73740605/diploma/indice?lcq=estatuto+do+bolseiro ,  
• Regulations for Research Grants of the Foundation for Science and Technology in force  https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf
• INESC-ID Lisboa Grant Regulations

https://www.inesc-id.pt/scholarship-regulations/

• Recovery and Resilience Plan (RRP)

https://recuperarportugal.gov.pt/

The fellowship contract is awarded on an exclusive dedication basis – art. 5 of Scientific Research Fellow Status and art. 16 of Regulations for Research Grants of the Foundation for Science and Technology.

4 | MONTHLY AMOUNT

The monthly amount of the grant 1259,64€ is in accordance with the values stipulated in the “Regulations for Research Grants of the Foundation for Science and Technology” in force https://www.fct.pt/wp-content/uploads/2024/02/Tabela-de-Valores-SMM_atualizacao-2024.pdf  and shall be rendered through a monthly bank transfer to an account held by the grantee.

5 | OBJECTIVES/WORKPLAN

Design, develop and evaluate methods for estimating the expected impact of retraining or fine-tuning machine learning models.  The objective is to automate the decision process underlying the choice of undergoing computational expensive update processes of Machine Learning (ML) models, in order to contribute to the establishment of sustainable AI systems. The grant assignee will look at machine learning models that target a spectrum of application domains, ranging from financial fraud detection to NLP.

6 | SCIENTIFIC SUPERVISION

The activity will be supervised by Paolo Romano, researcher at INESC-ID and Associate Professor at Instituto Superior Técnico.

INESC ID will integrate the grantee in the research team of the scientific advisor.

7 | ADMISSION REQUIREMENTS

The candidates should have a Master degree in computer science, computer engineering, electrical engineering.

By the grant start date, the candidate must be enrolled in

• a PhD programme – art. 6º, n.1
• a non-degree programme – art. 6º, n. 2

8 | EVALUATION CRITERIA AND COMMITTEE

The selection will be according to the following criteria:

• Prior work in the area of predicting costs and benefits of model retrain or fine-tuning, demonstrable via prior publications. (50%)
• Ability to write high quality scientific publications, demonstrable via the publication track-record. (25%)
• Knowledge of recent ML modelling techniques in domains such as NLP, computer vision and anomaly detection. (20%)
• English knowledge (5%)

The jury may also decide not to assign the scholarship, if none of candidates meets the required conditions

9 | COMPLAIN AND APPEAL DEADLINES AND PROCEDURES

The jury has the faculty not to select a candidate who does not prove the requirements mentioned in required education Level and research experience

The admitted and excluded candidates will be notified by email of the final ranking list, including the copy of the Preliminary Report of the jury.

Prior Hearing and Deadline for Final Decision: After being notified, candidates have 10 working days to submit, if applicable, a formal rebuttal.

After that period, the jury notifies the candidates of the Final Report.

Excluded applicants may complain about the jury's final report for 15 working days after notification or appeal the jury's decision to the INESC ID Board of Directors for 30 working days after notification.

According to the Portuguese Law, a disabled candidate has a preference when in equal classification, which prevails over any other legal preference. Candidates must declare their respective degree of disability, the type of disability and the means of communication / expression to be used in the selection process, under the law.

10 | FORMALISATION OF APPLICATIONS

11 | Application Dates

Requirements

Additional information, work location(s), where to apply.