why write research statement

Baylor Graduate Writing Center

Helping Grad Students Become Better Writers

Writing a Research Statement: A Brief Overview and Tips for Success

Jasmine Stovall, Consultant

Research statements have become an increasingly common required component of job application materials for positions in academia, specifically those that are research focused. The purpose of this blog post is to provide a brief overview of what a research statement is, why they are important, how they differ from other job application materials, and offer some tips and helpful advice for writing one.

What is a research statement?

To begin, let’s first discuss what a research statement is. Whether you are new to the job application material world or just need a refresher, this is always a great starting point. Having a clear definition of the type of writing you are setting out to do will help you to set more precise writing goals and develop an outline that is in alignment with the required and expected content of the genre as well as any job or field specific conventions.

A research statement is generally defined as a written summary of your research experiences past, present, and future ( Writing a Research Statement-Purdue OWL ). Specifically, it highlights your previous accomplishments (most often your thesis, dissertation, or postdoc research), any current projects you are working on, and proposed projects for the future ( Research Statement-Cornell University ).

Why is it important?

Research statements are important because they allow a hiring committee to evaluate your academic journey and get to know you, not just as a student but also as a professional researcher and active member of the scholarly community. They further allow you as the applicant to inform the committee of what exactly it is that you do, how your previous and future work aligns with the position to which you are applying, how you would be an asset to the department, and ways in which your scope of research can potentially form fruitful collaborations with existing faculty, partnerships with other industries, and engage students. And on a broader scale, the research statement highlights how your research interests and areas of expertise will bring funding to the university and advance the research status of the institution.

How is it different from a CV, cover letter, etc.?

The biggest differences between a research statement and most other job application materials, particularly a CV, are the length and the style of content. While CVs can be several pages, research statements tend to be shorter (three pages maximum) and discuss your research projects detail, rather than as a brief line on your CV. Another difference is that a research statement discusses proposed research, which is generally uncommon for CVs.

Research statements are different from cover letters in that the subject matter is narrower, with your work as the central focus more so than yourself as a person. Cover letters are generally all-encompassing, highlighting hard and soft skills and speaking to your accomplishments personally, professionally, and academically. They make you stand out while also expressing your interest in the position you are applying for and showing why you would be the ideal candidate.

Tips and Helpful Advice for Getting Started

As is the case with most writing projects, the hardest part is getting started. Listed below are some helpful tips to keep in mind and use as a guide when beginning to write your research statement.

Use your CV – While the CV differs from a research statement, it still contains a plethora of valuable information as it relates to your research projects and accomplishments, making it a great starting point when it comes to outlining your research statement, deciding which information to include, how to structure it, etc. So, don’t hesitate to lean on it to get the ball rolling if you find yourself stuck.
Focus on examples – Rather than just stating what you’ve done and would like to do, be sure to use specific examples to describe how your research findings have contributed to the scholarly community and the different ways your proposed future research will continue to build upon that. Don’t be afraid to showcase your work ( Writing a Research Statement-Carnegie Mellon University ).
Make connections – When brainstorming ideas for your research statement, let the main themes of your research and the problems you have tackled or plan to tackle within that main theme serve as a guide in your thought process. When writing, try to prioritize drawing upon these main themes, keeping the big picture and your ‘why’ in mind, then make connections between these main themes/big picture ideas and your specific research goals.
Be clear, concise, and realistic – Remember that there will be people from various subdisciplines reading your research statement. Therefore, it is important to be mindful of your audience when it comes to the use of technical jargon and overall word choice. This is where having peer reviewers outside of your field can be helpful.

I hope you found this blog post to be helpful. Should you find yourself in need of a second set of eyes to look over your research statement draft or to help with the drafting process, feel free to reach out to the GWC to schedule a consultation.

Writing a Research Statement (with example)

Much like writing a teaching philosophy , a research statement takes time, energy, and a lot of self reflection. This statement is a summary of your research accomplishments, what you are currently working on, and the future direction of your research program. This is also the place to really highlight your potential contributions to your field. For researchers who are further along in their career, this statement may include information about funding applications that were reviewed, approved, as well as any applications that are going to be submitted within the next year.

When I’ve looked at research statements over the years, helping people prepare for the academic interview cycle, one thing I’ve noticed more than anything is that people tend focus solely on the tangible aspects of their research, essentially rehashing their CV or resume. Although their accomplishments are often great, it can result in a rather boring set of pages full of nitty-gritty details rather than an immersive story about research experiences and potential. If there is one thing you take away from this article, your research path is magical and you want your readers to be invested in your magical story .

Now, I realize in my particular area of research (statistics and numerical reasoning), magical is not the word that most people would use as a descriptor. But therein lies the catch. When you are applying for academic positions, you aren’t selling just your research focus. Rather, you are selling the idea of you, your work, and your potential. Yes, your focus is a part of this, but only one part. You are the truly magical component, and your research is just one aspect of that.

When I did my cycle through academic application season, I wanted the review board to see who I was as a researcher, but I also wanted them to see how I approached my research content. The value my research adds to the field is the icing on the cake. I know my research is valuable. Generally speaking, scientists agree that most research in always valuable. But I needed the review board to see more than just my research value because I was competing against literally hundreds of applications. In such a competitive arena, every component of my application portfolio needed to stand out and grab attention.

As with other aspects of your portfolio, your research statement has some core components:

a brief summary of your research program
an overarching research question that ties all the individual studies together
what you are currently working on
where your research program is expected to go

Talking through these core aspects in a serial, linear way can be rather … Boring. You definitely do not want to be placed in the discard pile simply because your portfolio wasn’t engaging enough. Which brings me to storytelling. When I say storytelling, I’m not saying academics need to be master weavers of fantasy, complete with plots and characters that draw people out of reality into an imaginary world. Instead, I mean that people need to be walked through a narrative that logically carries the reader from one sentence to the next. This research statements connects the readers to you and invests them in your future research potential. Every sentence should be designed to make them want to keep reading.

Don’t feel bad if this statement takes some time to draft. Not all of us are naturally gifted with the talent for wordsmithing. It, like many other aspects of your portfolio, takes time, effort, energy, and self-reflection. Each aspect should be built with thoughtfulness and insight, and those things cannot be drawn overnight. Take your time and really develop your ideas. Over time, you’ll find that your research statement will evolve into a mature, guiding light of where you’ve been and where you’re going. And your readers will enjoy placing your files in the accept pile.

Alaina Talboy, PhD Research Statement Example

“Science and everyday life cannot and should not be separated.” – Rosalind Franklin

Research Interests

Over the last eight years, my research interests have focused on how people understand and utilize information to make judgments and decisions. Of particular interest are the mechanisms which underlie general abilities to reason through complex information when uncertainty is involved. In these types of situations, the data needed to make a decision are often presented as complicated statistics which are notoriously difficult to understand. In my research, I employ a combination of quantitative and qualitative research methods and analyses to evaluate how people process statistical data, which has strong theoretical contributions for discerning how people may perceive and utilize statistics in reasoning and decision making. This research also has valuable practical implications as statistical reasoning is one of the foundational pillars required for scientific thinking. I plan to continue this research via several avenues in both theoretical and applied contexts.

Statistics and the Reference Class Problem

It is easy to feel overwhelmed when presented with statistics, especially when the meaning of the statistical data is not clear. For example, what does it mean when the newscaster says there is a 20% chance of showers? Does that mean it will only rain 20% of the day? Or that only 20% of the area will get rain? Or that 20% of the possible rain will actually fall? Without a knowing the appropriate reference class, or group from which the data are drawn, reasoners are often forced to make a decision based on an improper assessment of the numbers provided. (The correct answer is that out of 100 days with these weather conditions, rain occurs on 20 of them.) Although this is a rather benign version of the reference class problem, difficulties with this issue extends well into the very core of understanding statistics.

Statistical testing involves an inherently nested structure in which values are dependent on the expression of other values. Understanding these relationships are foundational for appropriate use and application of statistics in practice. However, difficulties understanding statistics has been widely documented throughout numerous fields, contributing to the current research crisis as well as patient diagnostic errors (e.g., Gelman & Loken, 2014; Ioannidis, 2005; Ioannidis, Munafò, Fusar-Poli, Nosek, & David, 2014; Pashler & Wagenmakers, 2012). Therefore, research that can improve general statistical literacy is highly sought after.

As a stepping stone toward the more difficulty reference classes in statistics, a slightly less complicated version of the reference class problem can be found in Bayesian reasoning tasks (e.g., Gigerenzer, Gaissmaier, Kurz-Milcke, Schwartz, & Woloshin, 2007; Gigerenzer & Hoffrage, 1995; Hoffrage, Krauss, Martignon, & Gigerenzer, 2015; Johnson & Tubau, 2015; Reyna & Brainerd, 2008; Sirota, Kostovičová, & Vallée-Tourangeau, 2015; Talboy & Schneider, 2017, 2018, in press). In these types of reasoning tasks, there are difficulties with representing the inherently nested structure of the problem in a way that clearly elucidates the correct reference class needed to determine the solution. Additionally, computational demands compound these representation difficulties, contributing to generally low levels of accuracy.

In my own research, we have tackled the representational difficulties of reasoning by fundamentally altering how information is presented and which reference classes are elucidated in the problem structure (Talboy & Schneider, 2017, 2018, in press). In a related line, we break down the computational difficulties into the component processes of identification, computation, and application of values from the problem to the solution (Talboy & Schneider, in progress). In doing so, we discovered a general bias in which reasoners tend to select values that are presented in the problem text as the answer even when computations are required (Talboy & Schneider, in press, in progress, 2018). Moving forward, I plan to apply the advances made in understanding how people work through the complicated nested structure of Bayesian reasoning tasks to the more difficult nested structure of statistical testing.

Reference Dependence in Reasoning

While completing earlier work on a brief tutorial designed to increased understanding of these Bayesian reasoning problems through both representation and computation training (Talboy & Schneider, 2017), I realized that the reasoning task could be structurally reformed to focus on the information needed to solve the problem rather than using the traditional format which focuses on conflicting information that only serves to confuse the reasoner. In doing so, we inadvertently found a mechanism for reference dependence in Bayesian reasoning that was not previously documented (Talboy & Schneider, 2018, in press).

Reference dependence is the tendency to start cognitive deliberations from a given or indicated point of reference, and is considered to be one of the most ubiquitous findings through judgment and decision making literature (e.g., Dinner, Johnson, Goldstein, & Liu, 2011; Hájek, 2007; Lopes & Oden, 1999; Tversky & Kahneman, 1991). Although the majority of research documenting reference dependence comes from the choice literature, the importance of context in shaping behavior has also been noted in several other domains, including logical reasoning (Johnson-Laird, 2010), problem solving (Kotovsky & Simon, 1990), extensional reasoning (Fox & Levav, 2004)—and now in Bayesian reasoning as well (Talboy & Schneider, 2018, in press).

I parlayed my previous research on representational and computational difficulties into the foundation for my dissertation, with an eye toward how reference dependence affects uninitiated reasoners’ abilities to overcome these obstacles (Talboy, dissertation). I also evaluated the general value selection bias to determine the circumstances in which uninitiated reasoners revert to selecting values from the problem rather than completing computations (Talboy & Schneider, in progress, in press). I plan to extend this line of research to further evaluate the extent to which a value selection bias is utilized in other types of reasoning tasks involving reference classes, such as relative versus absolute risk.

Advancing Health Literacy

Although the majority of my research focuses on the theoretical underpinnings of cognitive processes involved in reasoning about inherently nested problem structures, I also have an applied line of research that focuses on applying what we learn from research to everyday life. We recently published a paper geared toward the medical community that takes what we learned about Bayesian reasoning and applies it to understanding the outcomes of medical diagnostic testing, and how patients would use that information to make future medical decisions (Talboy & Schneider, 2018). I also led an interdisciplinary team on a collaborative project to evaluate how younger and older adults evaluate pharmaceutical pamphlet information to determine which treatment to use (Talboy, Aylward, Lende, & Guttmann, 2016; Talboy & Guttmann, in progress). I plan to continue researching how information presented in medical contexts can be more clearly elucidated to improve individual health literacy, as well as general health decision making and reasoning.