presentation techniques in research methodology

Princeton Correspondents on Undergraduate Research

How to Make a Successful Research Presentation

Turning a research paper into a visual presentation is difficult; there are pitfalls, and navigating the path to a brief, informative presentation takes time and practice. As a TA for  GEO/WRI 201: Methods in Data Analysis & Scientific Writing this past fall, I saw how this process works from an instructor’s standpoint. I’ve presented my own research before, but helping others present theirs taught me a bit more about the process. Here are some tips I learned that may help you with your next research presentation:

More is more

In general, your presentation will always benefit from more practice, more feedback, and more revision. By practicing in front of friends, you can get comfortable with presenting your work while receiving feedback. It is hard to know how to revise your presentation if you never practice. If you are presenting to a general audience, getting feedback from someone outside of your discipline is crucial. Terms and ideas that seem intuitive to you may be completely foreign to someone else, and your well-crafted presentation could fall flat.

Less is more

Limit the scope of your presentation, the number of slides, and the text on each slide. In my experience, text works well for organizing slides, orienting the audience to key terms, and annotating important figures–not for explaining complex ideas. Having fewer slides is usually better as well. In general, about one slide per minute of presentation is an appropriate budget. Too many slides is usually a sign that your topic is too broad.

presentation techniques in research methodology

Limit the scope of your presentation

Don’t present your paper. Presentations are usually around 10 min long. You will not have time to explain all of the research you did in a semester (or a year!) in such a short span of time. Instead, focus on the highlight(s). Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

You will not have time to explain all of the research you did. Instead, focus on the highlights. Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

Craft a compelling research narrative

After identifying the focused research question, walk your audience through your research as if it were a story. Presentations with strong narrative arcs are clear, captivating, and compelling.

  • Introduction (exposition — rising action)

Orient the audience and draw them in by demonstrating the relevance and importance of your research story with strong global motive. Provide them with the necessary vocabulary and background knowledge to understand the plot of your story. Introduce the key studies (characters) relevant in your story and build tension and conflict with scholarly and data motive. By the end of your introduction, your audience should clearly understand your research question and be dying to know how you resolve the tension built through motive.

presentation techniques in research methodology

  • Methods (rising action)

The methods section should transition smoothly and logically from the introduction. Beware of presenting your methods in a boring, arc-killing, ‘this is what I did.’ Focus on the details that set your story apart from the stories other people have already told. Keep the audience interested by clearly motivating your decisions based on your original research question or the tension built in your introduction.

  • Results (climax)

Less is usually more here. Only present results which are clearly related to the focused research question you are presenting. Make sure you explain the results clearly so that your audience understands what your research found. This is the peak of tension in your narrative arc, so don’t undercut it by quickly clicking through to your discussion.

  • Discussion (falling action)

By now your audience should be dying for a satisfying resolution. Here is where you contextualize your results and begin resolving the tension between past research. Be thorough. If you have too many conflicts left unresolved, or you don’t have enough time to present all of the resolutions, you probably need to further narrow the scope of your presentation.

  • Conclusion (denouement)

Return back to your initial research question and motive, resolving any final conflicts and tying up loose ends. Leave the audience with a clear resolution of your focus research question, and use unresolved tension to set up potential sequels (i.e. further research).

Use your medium to enhance the narrative

Visual presentations should be dominated by clear, intentional graphics. Subtle animation in key moments (usually during the results or discussion) can add drama to the narrative arc and make conflict resolutions more satisfying. You are narrating a story written in images, videos, cartoons, and graphs. While your paper is mostly text, with graphics to highlight crucial points, your slides should be the opposite. Adapting to the new medium may require you to create or acquire far more graphics than you included in your paper, but it is necessary to create an engaging presentation.

The most important thing you can do for your presentation is to practice and revise. Bother your friends, your roommates, TAs–anybody who will sit down and listen to your work. Beyond that, think about presentations you have found compelling and try to incorporate some of those elements into your own. Remember you want your work to be comprehensible; you aren’t creating experts in 10 minutes. Above all, try to stay passionate about what you did and why. You put the time in, so show your audience that it’s worth it.

For more insight into research presentations, check out these past PCUR posts written by Emma and Ellie .

— Alec Getraer, Natural Sciences Correspondent

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Chapter 20. Presentations

Introduction.

If a tree falls in a forest, and no one is around to hear it, does it make a sound? If a qualitative study is conducted, but it is not presented (in words or text), did it really happen? Perhaps not. Findings from qualitative research are inextricably tied up with the way those findings are presented. These presentations do not always need to be in writing, but they need to happen. Think of ethnographies, for example, and their thick descriptions of a particular culture. Witnessing a culture, taking fieldnotes, talking to people—none of those things in and of themselves convey the culture. Or think about an interview-based phenomenological study. Boxes of interview transcripts might be interesting to read through, but they are not a completed study without the intervention of hours of analysis and careful selection of exemplary quotes to illustrate key themes and final arguments and theories. And unlike much quantitative research in the social sciences, where the final write-up neatly reports the results of analyses, the way the “write-up” happens is an integral part of the analysis in qualitative research. Once again, we come back to the messiness and stubborn unlinearity of qualitative research. From the very beginning, when designing the study, imagining the form of its ultimate presentation is helpful.

Because qualitative researchers are motivated by understanding and conveying meaning, effective communication is not only an essential skill but a fundamental facet of the entire research project. Ethnographers must be able to convey a certain sense of verisimilitude, the appearance of true reality. Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them. And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important. This chapter will address how to organize various kinds of presentations for different audiences so that your results can be appreciated and understood.

In the world of academic science, social or otherwise, the primary audience for a study’s results is usually the academic community, and the primary venue for communicating to this audience is the academic journal. Journal articles are typically fifteen to thirty pages in length (8,000 to 12,000 words). Although qualitative researchers often write and publish journal articles—indeed, there are several journals dedicated entirely to qualitative research [1] —the best writing by qualitative researchers often shows up in books. This is because books, running from 80,000 to 150,000 words in length, allow the researcher to develop the material fully. You have probably read some of these in various courses you have taken, not realizing what they are. I have used examples of such books throughout this text, beginning with the three profiles in the introductory chapter. In some instances, the chapters in these books began as articles in academic journals (another indication that the journal article format somewhat limits what can be said about the study overall).

While the article and the book are “final” products of qualitative research, there are actually a few other presentation formats that are used along the way. At the very beginning of a research study, it is often important to have a written research proposal not just to clarify to yourself what you will be doing and when but also to justify your research to an outside agency, such as an institutional review board (IRB; see chapter 12), or to a potential funder, which might be your home institution, a government funder (such as the National Science Foundation, or NSF), or a private foundation (such as the Gates Foundation). As you get your research underway, opportunities will arise to present preliminary findings to audiences, usually through presentations at academic conferences. These presentations can provide important feedback as you complete your analyses. Finally, if you are completing a degree and looking to find an academic job, you will be asked to provide a “job talk,” usually about your research. These job talks are similar to conference presentations but can run significantly longer.

All the presentations mentioned so far are (mostly) for academic audiences. But qualitative research is also unique in that many of its practitioners don’t want to confine their presentation only to other academics. Qualitative researchers who study particular contexts or cultures might want to report back to the people and places they observed. Those working in the critical tradition might want to raise awareness of a particular issue to as large an audience as possible. Many others simply want everyday, nonacademic people to read their work, because they think it is interesting and important. To reach a wide audience, the final product can look like almost anything—it can be a poem, a blog, a podcast, even a science fiction short story. And if you are very lucky, it can even be a national or international bestseller.

In this chapter, we are going to stick with the more basic quotidian presentations—the academic paper / research proposal, the conference slideshow presentation / job talk, and the conference poster. We’ll also spend a bit of time on incorporating universal design into your presentations and how to create some especially attractive and impactful visual displays.

Researcher Note

What is the best piece of advice you’ve ever been given about conducting qualitative research?

The best advice I’ve received came from my adviser, Alford Young Jr. He told me to find the “Jessi Streib” answer to my research question, not the “Pierre Bourdieu” answer to my research question. In other words, don’t just say how a famous theorist would answer your question; say something original, something coming from you.

—Jessi Streib, author of The Power of the Past and Privilege Lost 

Writing about Your Research

The journal article and the research proposal.

Although the research proposal is written before you have actually done your research and the article is written after all data collection and analysis is complete, there are actually many similarities between the two in terms of organization and purpose. The final article will (probably—depends on how much the research question and focus have shifted during the research itself) incorporate a great deal of what was included in a preliminary research proposal. The average lengths of both a proposal and an article are quite similar, with the “front sections” of the article abbreviated to make space for the findings, discussion of findings, and conclusion.

Figure 20.1 shows one model for what to include in an article or research proposal, comparing the elements of each with a default word count for each section. Please note that you will want to follow whatever specific guidelines you have been provided by the venue you are submitting the article/proposal to: the IRB, the NSF, the Journal of Qualitative Research . In fact, I encourage you to adapt the default model as needed by swapping out expected word counts for each section and adding or varying the sections to match expectations for your particular publication venue. [2]

You will notice a few things about the default model guidelines. First, while half of the proposal is spent discussing the research design, this section is shortened (but still included) for the article. There are a few elements that only show up in the proposal (e.g., the limitations section is in the introductory section here—it will be more fully developed in the conclusory section in the article). Obviously, you don’t have findings in the proposal, so this is an entirely new section for the article. Note that the article does not include a data management plan or a timeline—two aspects that most proposals require.

It might be helpful to find and maintain examples of successfully written sections that you can use as models for your own writing. I have included a few of these throughout the textbook and have included a few more at the end of this chapter.

Make an Argument

Some qualitative researchers, particularly those engaged in deep ethnographic research, focus their attention primarily if not exclusively on describing the data. They might even eschew the notion that they should make an “argument” about the data, preferring instead to use thick descriptions to convey interpretations. Bracketing the contrast between interpretation and argument for the moment, most readers will expect you to provide an argument about your data, and this argument will be in answer to whatever research question you eventually articulate (remember, research questions are allowed to shift as you get further into data collection and analysis). It can be frustrating to read a well-developed study with clear and elegant descriptions and no argument. The argument is the point of the research, and if you do not have one, 99 percent of the time, you are not finished with your analysis. Calarco ( 2020 ) suggests you imagine a pyramid, with all of your data forming the basis and all of your findings forming the middle section; the top/point of the pyramid is your argument, “what the patterns in your data tell us about how the world works or ought to work” ( 181 ).

The academic community to which you belong will be looking for an argument that relates to or develops theory. This is the theoretical generalizability promise of qualitative research. An academic audience will want to know how your findings relate to previous findings, theories, and concepts (the literature review; see chapter 9). It is thus vitally important that you go back to your literature review (or develop a new one) and draw those connections in your discussion and/or conclusion. When writing to other audiences, you will still want an argument, although it may not be written as a theoretical one. What do I mean by that? Even if you are not referring to previous literature or developing new theories or adapting older ones, a simple description of your findings is like dumping a lot of leaves in the lap of your audience. They still deserve to know about the shape of the forest. Maybe provide them a road map through it. Do this by telling a clear and cogent story about the data. What is the primary theme, and why is it important? What is the point of your research? [3]

A beautifully written piece of research based on participant observation [and/or] interviews brings people to life, and helps the reader understand the challenges people face. You are trying to use vivid, detailed and compelling words to help the reader really understand the lives of the people you studied. And you are trying to connect the lived experiences of these people to a broader conceptual point—so that the reader can understand why it matters. ( Lareau 2021:259 )

Do not hide your argument. Make it the focal point of your introductory section, and repeat it as often as needed to ensure the reader remembers it. I am always impressed when I see researchers do this well (see, e.g., Zelizer 1996 ).

Here are a few other suggestions for writing your article: Be brief. Do not overwhelm the reader with too many words; make every word count. Academics are particularly prone to “overwriting” as a way of demonstrating proficiency. Don’t. When writing your methods section, think about it as a “recipe for your work” that allows other researchers to replicate if they so wish ( Calarco 2020:186 ). Convey all the necessary information clearly, succinctly, and accurately. No more, no less. [4] Do not try to write from “beginning to end” in that order. Certain sections, like the introductory section, may be the last ones you write. I find the methods section the easiest, so I often begin there. Calarco ( 2020 ) begins with an outline of the analysis and results section and then works backward from there to outline the contribution she is making, then the full introduction that serves as a road map for the writing of all sections. She leaves the abstract for the very end. Find what order best works for you.

Presenting at Conferences and Job Talks

Students and faculty are primarily called upon to publicly present their research in two distinct contexts—the academic conference and the “job talk.” By convention, conference presentations usually run about fifteen minutes and, at least in sociology and other social sciences, rely primarily on the use of a slideshow (PowerPoint Presentation or PPT) presentation. You are usually one of three or four presenters scheduled on the same “panel,” so it is an important point of etiquette to ensure that your presentation falls within the allotted time and does not crowd into that of the other presenters. Job talks, on the other hand, conventionally require a forty- to forty-five-minute presentation with a fifteen- to twenty-minute question and answer (Q&A) session following it. You are the only person presenting, so if you run over your allotted time, it means less time for the Q&A, which can disturb some audience members who have been waiting for a chance to ask you something. It is sometimes possible to incorporate questions during your presentation, which allows you to take the entire hour, but you might end up shorting your presentation this way if the questions are numerous. It’s best for beginners to stick to the “ask me at the end” format (unless there is a simple clarifying question that can easily be addressed and makes the presentation run more smoothly, as in the case where you simply forgot to include information on the number of interviews you conducted).

For slideshows, you should allot two or even three minutes for each slide, never less than one minute. And those slides should be clear, concise, and limited. Most of what you say should not be on those slides at all. The slides are simply the main points or a clear image of what you are speaking about. Include bulleted points (words, short phrases), not full sentences. The exception is illustrative quotations from transcripts or fieldnotes. In those cases, keep to one illustrative quote per slide, and if it is long, bold or otherwise, highlight the words or passages that are most important for the audience to notice. [5]

Figure 20.2 provides a possible model for sections to include in either a conference presentation or a job talk, with approximate times and approximate numbers of slides. Note the importance (in amount of time spent) of both the research design and the findings/results sections, both of which have been helpfully starred for you. Although you don’t want to short any of the sections, these two sections are the heart of your presentation.

Fig 20.2. Suggested Slideshow Times and Number of Slides

Should you write out your script to read along with your presentation? I have seen this work well, as it prevents presenters from straying off topic and keeps them to the time allotted. On the other hand, these presentations can seem stiff and wooden. Personally, although I have a general script in advance, I like to speak a little more informally and engagingly with each slide, sometimes making connections with previous panelists if I am at a conference. This means I have to pay attention to the time, and I sometimes end up breezing through one section more quickly than I would like. Whatever approach you take, practice in advance. Many times. With an audience. Ask for feedback, and pay attention to any presentation issues that arise (e.g., Do you speak too fast? Are you hard to hear? Do you stumble over a particular word or name?).

Even though there are rules and guidelines for what to include, you will still want to make your presentation as engaging as possible in the little amount of time you have. Calarco ( 2020:274 ) recommends trying one of three story structures to frame your presentation: (1) the uncertain explanation , where you introduce a phenomenon that has not yet been fully explained and then describe how your research is tackling this; (2) the uncertain outcome , where you introduce a phenomenon where the consequences have been unclear and then you reveal those consequences with your research; and (3) the evocative example , where you start with some interesting example from your research (a quote from the interview transcripts, for example) or the real world and then explain how that example illustrates the larger patterns you found in your research. Notice that each of these is a framing story. Framing stories are essential regardless of format!

A Word on Universal Design

Please consider accessibility issues during your presentation, and incorporate elements of universal design into your slideshow. The basic idea behind universal design in presentations is that to the greatest extent possible, all people should be able to view, hear, or otherwise take in your presentation without needing special individual adaptations. If you can make your presentation accessible to people with visual impairment or hearing loss, why not do so? For example, one in twelve men is color-blind, unable to differentiate between certain colors, red/green being the most common problem. So if you design a graphic that relies on red and green bars, some of your audience members may not be able to properly identify which bar means what. Simple contrasts of black and white are much more likely to be visible to all members of your audience. There are many other elements of good universal design, but the basic foundation of all of them is that you consider how to make your presentation as accessible as possible at the outset. For example, include captions whenever possible, both as descriptions on slides and as images on slides and for any audio or video clips you are including; keep font sizes large enough to read from the back of the room; and face the audience when you are.

Poster Design

Undergraduate students who present at conferences are often encouraged to present at “poster sessions.” This usually means setting up a poster version of your research in a large hall or convention space at a set period of time—ninety minutes is common. Your poster will be one of dozens, and conference-goers will wander through the space, stopping intermittently at posters that attract them. Those who stop by might ask you questions about your research, and you are expected to be able to talk intelligently for two or three minutes. It’s a fairly easy way to practice presenting at conferences, which is why so many organizations hold these special poster sessions.

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A good poster design will be immediately attractive to passersby and clearly and succinctly describe your research methods, findings, and conclusions. Some students have simply shrunk down their research papers to manageable sizes and then pasted them on a poster, all twelve to fifteen pages of them. Don’t do that! Here are some better suggestions: State the main conclusion of your research in large bold print at the top of your poster, on brightly colored (contrasting) paper, and paste in a QR code that links to your full paper online ( Calarco 2020:280 ). Use the rest of the poster board to provide a couple of highlights and details of the study. For an interview-based study, for example, you will want to put in some details about your sample (including number of interviews) and setting and then perhaps one or two key quotes, also distinguished by contrasting color background.

Incorporating Visual Design in Your Presentations

In addition to ensuring that your presentation is accessible to as large an audience as possible, you also want to think about how to display your data in general, particularly how to use charts and graphs and figures. [6] The first piece of advice is, use them! As the saying goes, a picture is worth a thousand words. If you can cut to the chase with a visually stunning display, do so. But there are visual displays that are stunning, and then there are the tired, hard-to-see visual displays that predominate at conferences. You can do better than most presenters by simply paying attention here and committing yourself to a good design. As with model section passages, keep a file of visual displays that work as models for your own presentations. Find a good guidebook to presenting data effectively (Evergreen 2018 , 2019 ; Schwabisch 2021) , and refer to it often.

Let me make a few suggestions here to get you started. First, test every visual display on a friend or colleague to find out how quickly they can understand the point you are trying to convey. As with reading passages aloud to ensure that your writing works, showing someone your display is the quickest way to find out if it works. Second, put the point in the title of the display! When writing for an academic journal, there will be specific conventions of what to include in the title (full description including methods of analysis, sample, dates), but in a public presentation, there are no limiting rules. So you are free to write as your title “Working-Class College Students Are Three Times as Likely as Their Peers to Drop Out of College,” if that is the point of the graphic display. It certainly helps the communicative aspect. Third, use the themes available to you in Excel for creating graphic displays, but alter them to better fit your needs . Consider adding dark borders to bars and columns, for example, so that they appear crisper for your audience. Include data callouts and labels, and enlarge them so they are clearly visible. When duplicative or otherwise unnecessary, drop distracting gridlines and labels on the y-axis (the vertical one). Don’t go crazy adding different fonts, however—keep things simple and clear. Sans serif fonts (those without the little hooks on the ends of letters) read better from a distance. Try to use the same color scheme throughout, even if this means manually changing the colors of bars and columns. For example, when reporting on working-class college students, I use blue bars, while I reserve green bars for wealthy students and yellow bars for students in the middle. I repeat these colors throughout my presentations and incorporate different colors when talking about other items or factors. You can also try using simple grayscale throughout, with pops of color to indicate a bar or column or line that is of the most interest. These are just some suggestions. The point is to take presentation seriously and to pay attention to visual displays you are using to ensure they effectively communicate what you want them to communicate. I’ve included a data visualization checklist from Evergreen ( 2018 ) here.

Ethics of Presentation and Reliability

Until now, all the data you have collected have been yours alone. Once you present the data, however, you are sharing sometimes very intimate information about people with a broader public. You will find yourself balancing between protecting the privacy of those you’ve interviewed and observed and needing to demonstrate the reliability of the study. The more information you provide to your audience, the more they can understand and appreciate what you have found, but this also may pose risks to your participants. There is no one correct way to go about finding the right balance. As always, you have a duty to consider what you are doing and must make some hard decisions.

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The most obvious place we see this paradox emerge is when you mask your data to protect the privacy of your participants. It is standard practice to provide pseudonyms, for example. It is such standard practice that you should always assume you are being given a pseudonym when reading a book or article based on qualitative research. When I was a graduate student, I tried to find information on how best to construct pseudonyms but found little guidance. There are some ethical issues here, I think. [7] Do you create a name that has the same kind of resonance as the original name? If the person goes by a nickname, should you use a nickname as a pseudonym? What about names that are ethnically marked (as in, almost all of them)? Is there something unethical about reracializing a person? (Yes!) In her study of adolescent subcultures, Wilkins ( 2008 ) noted, “Because many of the goths used creative, alternative names rather than their given names, I did my best to reproduce the spirit of their chosen names” ( 24 ).

Your reader or audience will want to know all the details about your participants so that they can gauge both your credibility and the reliability of your findings. But how many details are too many? What if you change the name but otherwise retain all the personal pieces of information about where they grew up, and how old they were when they got married, and how many children they have, and whether they made a splash in the news cycle that time they were stalked by their ex-boyfriend? At some point, those details are going to tip over into the zone of potential unmasking. When you are doing research at one particular field site that may be easily ascertained (as when you interview college students, probably at the institution at which you are a student yourself), it is even more important to be wary of providing too many details. You also need to think that your participants might read what you have written, know things about the site or the population from which you drew your interviews, and figure out whom you are talking about. This can all get very messy if you don’t do more than simply pseudonymize the people you interviewed or observed.

There are some ways to do this. One, you can design a study with all of these risks in mind. That might mean choosing to conduct interviews or observations at multiple sites so that no one person can be easily identified. Another is to alter some basic details about your participants to protect their identity or to refuse to provide all the information when selecting quotes . Let’s say you have an interviewee named “Anna” (a pseudonym), and she is a twenty-four-year-old Latina studying to be an engineer. You want to use a quote from Anna about racial discrimination in her graduate program. Instead of attributing the quote to Anna (whom your reader knows, because you’ve already told them, is a twenty-four-year-old Latina studying engineering), you might simply attribute the quote to “Latina student in STEM.” Taking this a step further, you might leave the quote unattributed, providing a list of quotes about racial discrimination by “various students.”

The problem with masking all the identifiers, of course, is that you lose some of the analytical heft of those attributes. If it mattered that Anna was twenty-four (not thirty-four) and that she was a Latina and that she was studying engineering, taking out any of those aspects of her identity might weaken your analysis. This is one of those “hard choices” you will be called on to make! A rather radical and controversial solution to this dilemma is to create composite characters , characters based on the reality of the interviews but fully masked because they are not identifiable with any one person. My students are often very queasy about this when I explain it to them. The more positivistic your approach and the more you see individuals rather than social relationships/structure as the “object” of your study, the more employing composites will seem like a really bad idea. But composites “allow researchers to present complex, situated accounts from individuals” without disclosing personal identities ( Willis 2019 ), and they can be effective ways of presenting theory narratively ( Hurst 2019 ). Ironically, composites permit you more latitude when including “dirty laundry” or stories that could harm individuals if their identities became known. Rather than squeezing out details that could identify a participant, the identities are permanently removed from the details. Great difficulty remains, however, in clearly explaining the theoretical use of composites to your audience and providing sufficient information on the reliability of the underlying data.

There are a host of other ethical issues that emerge as you write and present your data. This is where being reflective throughout the process will help. How and what you share of what you have learned will depend on the social relationships you have built, the audiences you are writing or speaking to, and the underlying animating goals of your study. Be conscious about all of your decisions, and then be able to explain them fully, both to yourself and to those who ask.

Our research is often close to us. As a Black woman who is a first-generation college student and a professional with a poverty/working-class origin, each of these pieces of my identity creates nuances in how I engage in my research, including how I share it out. Because of this, it’s important for us to have people in our lives who we trust who can help us, particularly, when we are trying to share our findings. As researchers, we have been steeped in our work, so we know all the details and nuances. Sometimes we take this for granted, and we might not have shared those nuances in conversation or writing or taken some of this information for granted. As I share my research with trusted friends and colleagues, I pay attention to the questions they ask me or the feedback they give when we talk or when they read drafts.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

Final Comments: Preparing for Being Challenged

Once you put your work out there, you must be ready to be challenged. Science is a collective enterprise and depends on a healthy give and take among researchers. This can be both novel and difficult as you get started, but the more you understand the importance of these challenges, the easier it will be to develop the kind of thick skin necessary for success in academia. Scientists’ authority rests on both the inherent strength of their findings and their ability to convince other scientists of the reliability and validity and value of those findings. So be prepared to be challenged, and recognize this as simply another important aspect of conducting research!

Considering what challenges might be made as you design and conduct your study will help you when you get to the writing and presentation stage. Address probable challenges in your final article, and have a planned response to probable questions in a conference presentation or job talk. The following is a list of common challenges of qualitative research and how you might best address them:

  • Questions about generalizability . Although qualitative research is not statistically generalizable (and be prepared to explain why), qualitative research is theoretically generalizable. Discuss why your findings here might tell us something about related phenomena or contexts.
  • Questions about reliability . You probably took steps to ensure the reliability of your findings. Discuss them! This includes explaining the use and value of multiple data sources and defending your sampling and case selections. It also means being transparent about your own position as researcher and explaining steps you took to ensure that what you were seeing was really there.
  • Questions about replicability. Although qualitative research cannot strictly be replicated because the circumstances and contexts will necessarily be different (if only because the point in time is different), you should be able to provide as much detail as possible about how the study was conducted so that another researcher could attempt to confirm or disconfirm your findings. Also, be very clear about the limitations of your study, as this allows other researchers insight into what future research might be warranted.

None of this is easy, of course. Writing beautifully and presenting clearly and cogently require skill and practice. If you take anything from this chapter, it is to remember that presentation is an important and essential part of the research process and to allocate time for this as you plan your research.

Data Visualization Checklist for Slideshow (PPT) Presentations

Adapted from Evergreen ( 2018 )

Text checklist

  • Short catchy, descriptive titles (e.g., “Working-class students are three times as likely to drop out of college”) summarize the point of the visual display
  • Subtitled and annotations provide additional information (e.g., “note: male students also more likely to drop out”)
  • Text size is hierarchical and readable (titles are largest; axes labels smallest, which should be at least 20points)
  • Text is horizontal. Audience members cannot read vertical text!
  • All data labeled directly and clearly: get rid of those “legends” and embed the data in your graphic display
  • Labels are used sparingly; avoid redundancy (e.g., do not include both a number axis and a number label)

Arrangement checklist

  • Proportions are accurate; bar charts should always start at zero; don’t mislead the audience!
  • Data are intentionally ordered (e.g., by frequency counts). Do not leave ragged alphabetized bar graphs!
  • Axis intervals are equidistant: spaces between axis intervals should be the same unit
  • Graph is two-dimensional. Three-dimensional and “bevelled” displays are confusing
  • There is no unwanted decoration (especially the kind that comes automatically through the PPT “theme”). This wastes your space and confuses.

Color checklist

  • There is an intentional color scheme (do not use default theme)
  • Color is used to identify key patterns (e.g., highlight one bar in red against six others in greyscale if this is the bar you want the audience to notice)
  • Color is still legible when printed in black and white
  • Color is legible for people with color blindness (do not use red/green or yellow/blue combinations)
  • There is sufficient contrast between text and background (black text on white background works best; be careful of white on dark!)

Lines checklist

  • Be wary of using gridlines; if you do, mute them (grey, not black)
  • Allow graph to bleed into surroundings (don’t use border lines)
  • Remove axis lines unless absolutely necessary (better to label directly)

Overall design checklist

  • The display highlights a significant finding or conclusion that your audience can ‘”see” relatively quickly
  • The type of graph (e.g., bar chart, pie chart, line graph) is appropriate for the data. Avoid pie charts with more than three slices!
  • Graph has appropriate level of precision; if you don’t need decimal places
  • All the chart elements work together to reinforce the main message

Universal Design Checklist for Slideshow (PPT) Presentations

  • Include both verbal and written descriptions (e.g., captions on slides); consider providing a hand-out to accompany the presentation
  • Microphone available (ask audience in back if they can clearly hear)
  • Face audience; allow people to read your lips
  • Turn on captions when presenting audio or video clips
  • Adjust light settings for visibility
  • Speak slowly and clearly; practice articulation; don’t mutter or speak under your breath (even if you have something humorous to say – say it loud!)
  • Use Black/White contrasts for easy visibility; or use color contrasts that are real contrasts (do not rely on people being able to differentiate red from green, for example)
  • Use easy to read font styles and avoid too small font sizes: think about what an audience member in the back row will be able to see and read.
  • Keep your slides simple: do not overclutter them; if you are including quotes from your interviews, take short evocative snippets only, and bold key words and passages. You should also read aloud each passage, preferably with feeling!

Supplement: Models of Written Sections for Future Reference

Data collection section example.

Interviews were semi structured, lasted between one and three hours, and took place at a location chosen by the interviewee. Discussions centered on four general topics: (1) knowledge of their parent’s immigration experiences; (2) relationship with their parents; (3) understanding of family labor, including language-brokering experiences; and (4) experiences with school and peers, including any future life plans. While conducting interviews, I paid close attention to respondents’ nonverbal cues, as well as their use of metaphors and jokes. I conducted interviews until I reached a point of saturation, as indicated by encountering repeated themes in new interviews (Glaser and Strauss 1967). Interviews were audio recorded, transcribed with each interviewee’s permission, and conducted in accordance with IRB protocols. Minors received permission from their parents before participation in the interview. ( Kwon 2022:1832 )

Justification of Case Selection / Sample Description Section Example

Looking at one profession within one organization and in one geographic area does impose limitations on the generalizability of our findings. However, it also has advantages. We eliminate the problem of interorganizational heterogeneity. If multiple organizations are studied simultaneously, it can make it difficult to discern the mechanisms that contribute to racial inequalities. Even with a single occupation there is considerable heterogeneity, which may make understanding how organizational structure impacts worker outcomes difficult. By using the case of one group of professionals in one religious denomination in one geographic region of the United States, we clarify how individuals’ perceptions and experiences of occupational inequality unfold in relation to a variety of observed and unobserved occupational and contextual factors that might be obscured in a larger-scale study. Focusing on a specific group of professionals allows us to explore and identify ways that formal organizational rules combine with informal processes to contribute to the persistence of racial inequality. ( Eagle and Mueller 2022:1510–1511 )

Ethics Section Example

I asked everyone who was willing to sit for a formal interview to speak only for themselves and offered each of them a prepaid Visa Card worth $25–40. I also offered everyone the opportunity to keep the card and erase the tape completely at any time they were dissatisfied with the interview in any way. No one asked for the tape to be erased; rather, people remarked on the interview being a really good experience because they felt heard. Each interview was professionally transcribed and for the most part the excerpts are literal transcriptions. In a few places, the excerpts have been edited to reduce colloquial features of speech (e.g., you know, like, um) and some recursive elements common to spoken language. A few excerpts were placed into standard English for clarity. I made this choice for the benefit of readers who might otherwise find the insights and ideas harder to parse in the original. However, I have to acknowledge this as an act of class-based violence. I tried to keep the original phrasing whenever possible. ( Pascale 2021:235 )

Further Readings

Calarco, Jessica McCrory. 2020. A Field Guide to Grad School: Uncovering the Hidden Curriculum . Princeton, NJ: Princeton University Press. Don’t let the unassuming title mislead you—there is a wealth of helpful information on writing and presenting data included here in a highly accessible manner. Every graduate student should have a copy of this book.

Edwards, Mark. 2012. Writing in Sociology . Thousand Oaks, CA: SAGE. An excellent guide to writing and presenting sociological research by an Oregon State University professor. Geared toward undergraduates and useful for writing about either quantitative or qualitative research or both.

Evergreen, Stephanie D. H. 2018. Presenting Data Effectively: Communicating Your Findings for Maximum Impact . Thousand Oaks, CA: SAGE. This is one of my very favorite books, and I recommend it highly for everyone who wants their presentations and publications to communicate more effectively than the boring black-and-white, ragged-edge tables and figures academics are used to seeing.

Evergreen, Stephanie D. H. 2019. Effective Data Visualization 2 . Thousand Oaks, CA: SAGE. This is an advanced primer for presenting clean and clear data using graphs, tables, color, font, and so on. Start with Evergreen (2018), and if you graduate from that text, move on to this one.

Schwabisch, Jonathan. 2021. Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks . New York: Columbia University Press. Where Evergreen’s (2018, 2019) focus is on how to make the best visual displays possible for effective communication, this book is specifically geared toward visual displays of academic data, both quantitative and qualitative. If you want to know when it is appropriate to use a pie chart instead of a stacked bar chart, this is the reference to use.

  • Some examples: Qualitative Inquiry , Qualitative Research , American Journal of Qualitative Research , Ethnography , Journal of Ethnographic and Qualitative Research , Qualitative Report , Qualitative Sociology , and Qualitative Studies . ↵
  • This is something I do with every article I write: using Excel, I write each element of the expected article in a separate row, with one column for “expected word count” and another column for “actual word count.” I fill in the actual word count as I write. I add a third column for “comments to myself”—how things are progressing, what I still need to do, and so on. I then use the “sum” function below each of the first two columns to keep a running count of my progress relative to the final word count. ↵
  • And this is true, I would argue, even when your primary goal is to leave space for the voices of those who don’t usually get a chance to be part of the conversation. You will still want to put those voices in some kind of choir, with a clear direction (song) to be sung. The worst thing you can do is overwhelm your audience with random quotes or long passages with no key to understanding them. Yes, a lot of metaphors—qualitative researchers love metaphors! ↵
  • To take Calarco’s recipe analogy further, do not write like those food bloggers who spend more time discussing the color of their kitchen or the experiences they had at the market than they do the actual cooking; similarly, do not write recipes that omit crucial details like the amount of flour or the size of the baking pan used or the temperature of the oven. ↵
  • The exception is the “compare and contrast” of two or more quotes, but use caution here. None of the quotes should be very long at all (a sentence or two each). ↵
  • Although this section is geared toward presentations, many of the suggestions could also be useful when writing about your data. Don’t be afraid to use charts and graphs and figures when writing your proposal, article, thesis, or dissertation. At the very least, you should incorporate a tabular display of the participants, sites, or documents used. ↵
  • I was so puzzled by these kinds of questions that I wrote one of my very first articles on it ( Hurst 2008 ). ↵

The visual presentation of data or information through graphics such as charts, graphs, plots, infographics, maps, and animation.  Recall the best documentary you ever viewed, and there were probably excellent examples of good data visualization there (for me, this was An Inconvenient Truth , Al Gore’s film about climate change).  Good data visualization allows more effective communication of findings of research, particularly in public presentations (e.g., slideshows).

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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Ten simple rules for effective presentation slides

* E-mail: [email protected]

Affiliation Biomedical Engineering and the Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America

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  • Kristen M. Naegle

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Published: December 2, 2021

  • https://doi.org/10.1371/journal.pcbi.1009554
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Citation: Naegle KM (2021) Ten simple rules for effective presentation slides. PLoS Comput Biol 17(12): e1009554. https://doi.org/10.1371/journal.pcbi.1009554

Copyright: © 2021 Kristen M. Naegle. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The author received no specific funding for this work.

Competing interests: The author has declared no competing interests exist.

Introduction

The “presentation slide” is the building block of all academic presentations, whether they are journal clubs, thesis committee meetings, short conference talks, or hour-long seminars. A slide is a single page projected on a screen, usually built on the premise of a title, body, and figures or tables and includes both what is shown and what is spoken about that slide. Multiple slides are strung together to tell the larger story of the presentation. While there have been excellent 10 simple rules on giving entire presentations [ 1 , 2 ], there was an absence in the fine details of how to design a slide for optimal effect—such as the design elements that allow slides to convey meaningful information, to keep the audience engaged and informed, and to deliver the information intended and in the time frame allowed. As all research presentations seek to teach, effective slide design borrows from the same principles as effective teaching, including the consideration of cognitive processing your audience is relying on to organize, process, and retain information. This is written for anyone who needs to prepare slides from any length scale and for most purposes of conveying research to broad audiences. The rules are broken into 3 primary areas. Rules 1 to 5 are about optimizing the scope of each slide. Rules 6 to 8 are about principles around designing elements of the slide. Rules 9 to 10 are about preparing for your presentation, with the slides as the central focus of that preparation.

Rule 1: Include only one idea per slide

Each slide should have one central objective to deliver—the main idea or question [ 3 – 5 ]. Often, this means breaking complex ideas down into manageable pieces (see Fig 1 , where “background” information has been split into 2 key concepts). In another example, if you are presenting a complex computational approach in a large flow diagram, introduce it in smaller units, building it up until you finish with the entire diagram. The progressive buildup of complex information means that audiences are prepared to understand the whole picture, once you have dedicated time to each of the parts. You can accomplish the buildup of components in several ways—for example, using presentation software to cover/uncover information. Personally, I choose to create separate slides for each piece of information content I introduce—where the final slide has the entire diagram, and I use cropping or a cover on duplicated slides that come before to hide what I’m not yet ready to include. I use this method in order to ensure that each slide in my deck truly presents one specific idea (the new content) and the amount of the new information on that slide can be described in 1 minute (Rule 2), but it comes with the trade-off—a change to the format of one of the slides in the series often means changes to all slides.

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  • PPT PowerPoint slide
  • PNG larger image
  • TIFF original image

Top left: A background slide that describes the background material on a project from my lab. The slide was created using a PowerPoint Design Template, which had to be modified to increase default text sizes for this figure (i.e., the default text sizes are even worse than shown here). Bottom row: The 2 new slides that break up the content into 2 explicit ideas about the background, using a central graphic. In the first slide, the graphic is an explicit example of the SH2 domain of PI3-kinase interacting with a phosphorylation site (Y754) on the PDGFR to describe the important details of what an SH2 domain and phosphotyrosine ligand are and how they interact. I use that same graphic in the second slide to generalize all binding events and include redundant text to drive home the central message (a lot of possible interactions might occur in the human proteome, more than we can currently measure). Top right highlights which rules were used to move from the original slide to the new slide. Specific changes as highlighted by Rule 7 include increasing contrast by changing the background color, increasing font size, changing to sans serif fonts, and removing all capital text and underlining (using bold to draw attention). PDGFR, platelet-derived growth factor receptor.

https://doi.org/10.1371/journal.pcbi.1009554.g001

Rule 2: Spend only 1 minute per slide

When you present your slide in the talk, it should take 1 minute or less to discuss. This rule is really helpful for planning purposes—a 20-minute presentation should have somewhere around 20 slides. Also, frequently giving your audience new information to feast on helps keep them engaged. During practice, if you find yourself spending more than a minute on a slide, there’s too much for that one slide—it’s time to break up the content into multiple slides or even remove information that is not wholly central to the story you are trying to tell. Reduce, reduce, reduce, until you get to a single message, clearly described, which takes less than 1 minute to present.

Rule 3: Make use of your heading

When each slide conveys only one message, use the heading of that slide to write exactly the message you are trying to deliver. Instead of titling the slide “Results,” try “CTNND1 is central to metastasis” or “False-positive rates are highly sample specific.” Use this landmark signpost to ensure that all the content on that slide is related exactly to the heading and only the heading. Think of the slide heading as the introductory or concluding sentence of a paragraph and the slide content the rest of the paragraph that supports the main point of the paragraph. An audience member should be able to follow along with you in the “paragraph” and come to the same conclusion sentence as your header at the end of the slide.

Rule 4: Include only essential points

While you are speaking, audience members’ eyes and minds will be wandering over your slide. If you have a comment, detail, or figure on a slide, have a plan to explicitly identify and talk about it. If you don’t think it’s important enough to spend time on, then don’t have it on your slide. This is especially important when faculty are present. I often tell students that thesis committee members are like cats: If you put a shiny bauble in front of them, they’ll go after it. Be sure to only put the shiny baubles on slides that you want them to focus on. Putting together a thesis meeting for only faculty is really an exercise in herding cats (if you have cats, you know this is no easy feat). Clear and concise slide design will go a long way in helping you corral those easily distracted faculty members.

Rule 5: Give credit, where credit is due

An exception to Rule 4 is to include proper citations or references to work on your slide. When adding citations, names of other researchers, or other types of credit, use a consistent style and method for adding this information to your slides. Your audience will then be able to easily partition this information from the other content. A common mistake people make is to think “I’ll add that reference later,” but I highly recommend you put the proper reference on the slide at the time you make it, before you forget where it came from. Finally, in certain kinds of presentations, credits can make it clear who did the work. For the faculty members heading labs, it is an effective way to connect your audience with the personnel in the lab who did the work, which is a great career booster for that person. For graduate students, it is an effective way to delineate your contribution to the work, especially in meetings where the goal is to establish your credentials for meeting the rigors of a PhD checkpoint.

Rule 6: Use graphics effectively

As a rule, you should almost never have slides that only contain text. Build your slides around good visualizations. It is a visual presentation after all, and as they say, a picture is worth a thousand words. However, on the flip side, don’t muddy the point of the slide by putting too many complex graphics on a single slide. A multipanel figure that you might include in a manuscript should often be broken into 1 panel per slide (see Rule 1 ). One way to ensure that you use the graphics effectively is to make a point to introduce the figure and its elements to the audience verbally, especially for data figures. For example, you might say the following: “This graph here shows the measured false-positive rate for an experiment and each point is a replicate of the experiment, the graph demonstrates …” If you have put too much on one slide to present in 1 minute (see Rule 2 ), then the complexity or number of the visualizations is too much for just one slide.

Rule 7: Design to avoid cognitive overload

The type of slide elements, the number of them, and how you present them all impact the ability for the audience to intake, organize, and remember the content. For example, a frequent mistake in slide design is to include full sentences, but reading and verbal processing use the same cognitive channels—therefore, an audience member can either read the slide, listen to you, or do some part of both (each poorly), as a result of cognitive overload [ 4 ]. The visual channel is separate, allowing images/videos to be processed with auditory information without cognitive overload [ 6 ] (Rule 6). As presentations are an exercise in listening, and not reading, do what you can to optimize the ability of the audience to listen. Use words sparingly as “guide posts” to you and the audience about major points of the slide. In fact, you can add short text fragments, redundant with the verbal component of the presentation, which has been shown to improve retention [ 7 ] (see Fig 1 for an example of redundant text that avoids cognitive overload). Be careful in the selection of a slide template to minimize accidentally adding elements that the audience must process, but are unimportant. David JP Phillips argues (and effectively demonstrates in his TEDx talk [ 5 ]) that the human brain can easily interpret 6 elements and more than that requires a 500% increase in human cognition load—so keep the total number of elements on the slide to 6 or less. Finally, in addition to the use of short text, white space, and the effective use of graphics/images, you can improve ease of cognitive processing further by considering color choices and font type and size. Here are a few suggestions for improving the experience for your audience, highlighting the importance of these elements for some specific groups:

  • Use high contrast colors and simple backgrounds with low to no color—for persons with dyslexia or visual impairment.
  • Use sans serif fonts and large font sizes (including figure legends), avoid italics, underlining (use bold font instead for emphasis), and all capital letters—for persons with dyslexia or visual impairment [ 8 ].
  • Use color combinations and palettes that can be understood by those with different forms of color blindness [ 9 ]. There are excellent tools available to identify colors to use and ways to simulate your presentation or figures as they might be seen by a person with color blindness (easily found by a web search).
  • In this increasing world of virtual presentation tools, consider practicing your talk with a closed captioning system capture your words. Use this to identify how to improve your speaking pace, volume, and annunciation to improve understanding by all members of your audience, but especially those with a hearing impairment.

Rule 8: Design the slide so that a distracted person gets the main takeaway

It is very difficult to stay focused on a presentation, especially if it is long or if it is part of a longer series of talks at a conference. Audience members may get distracted by an important email, or they may start dreaming of lunch. So, it’s important to look at your slide and ask “If they heard nothing I said, will they understand the key concept of this slide?” The other rules are set up to help with this, including clarity of the single point of the slide (Rule 1), titling it with a major conclusion (Rule 3), and the use of figures (Rule 6) and short text redundant to your verbal description (Rule 7). However, with each slide, step back and ask whether its main conclusion is conveyed, even if someone didn’t hear your accompanying dialog. Importantly, ask if the information on the slide is at the right level of abstraction. For example, do you have too many details about the experiment, which hides the conclusion of the experiment (i.e., breaking Rule 1)? If you are worried about not having enough details, keep a slide at the end of your slide deck (after your conclusions and acknowledgments) with the more detailed information that you can refer to during a question and answer period.

Rule 9: Iteratively improve slide design through practice

Well-designed slides that follow the first 8 rules are intended to help you deliver the message you intend and in the amount of time you intend to deliver it in. The best way to ensure that you nailed slide design for your presentation is to practice, typically a lot. The most important aspects of practicing a new presentation, with an eye toward slide design, are the following 2 key points: (1) practice to ensure that you hit, each time through, the most important points (for example, the text guide posts you left yourself and the title of the slide); and (2) practice to ensure that as you conclude the end of one slide, it leads directly to the next slide. Slide transitions, what you say as you end one slide and begin the next, are important to keeping the flow of the “story.” Practice is when I discover that the order of my presentation is poor or that I left myself too few guideposts to remember what was coming next. Additionally, during practice, the most frequent things I have to improve relate to Rule 2 (the slide takes too long to present, usually because I broke Rule 1, and I’m delivering too much information for one slide), Rule 4 (I have a nonessential detail on the slide), and Rule 5 (I forgot to give a key reference). The very best type of practice is in front of an audience (for example, your lab or peers), where, with fresh perspectives, they can help you identify places for improving slide content, design, and connections across the entirety of your talk.

Rule 10: Design to mitigate the impact of technical disasters

The real presentation almost never goes as we planned in our heads or during our practice. Maybe the speaker before you went over time and now you need to adjust. Maybe the computer the organizer is having you use won’t show your video. Maybe your internet is poor on the day you are giving a virtual presentation at a conference. Technical problems are routinely part of the practice of sharing your work through presentations. Hence, you can design your slides to limit the impact certain kinds of technical disasters create and also prepare alternate approaches. Here are just a few examples of the preparation you can do that will take you a long way toward avoiding a complete fiasco:

  • Save your presentation as a PDF—if the version of Keynote or PowerPoint on a host computer cause issues, you still have a functional copy that has a higher guarantee of compatibility.
  • In using videos, create a backup slide with screen shots of key results. For example, if I have a video of cell migration, I’ll be sure to have a copy of the start and end of the video, in case the video doesn’t play. Even if the video worked, you can pause on this backup slide and take the time to highlight the key results in words if someone could not see or understand the video.
  • Avoid animations, such as figures or text that flash/fly-in/etc. Surveys suggest that no one likes movement in presentations [ 3 , 4 ]. There is likely a cognitive underpinning to the almost universal distaste of pointless animations that relates to the idea proposed by Kosslyn and colleagues that animations are salient perceptual units that captures direct attention [ 4 ]. Although perceptual salience can be used to draw attention to and improve retention of specific points, if you use this approach for unnecessary/unimportant things (like animation of your bullet point text, fly-ins of figures, etc.), then you will distract your audience from the important content. Finally, animations cause additional processing burdens for people with visual impairments [ 10 ] and create opportunities for technical disasters if the software on the host system is not compatible with your planned animation.

Conclusions

These rules are just a start in creating more engaging presentations that increase audience retention of your material. However, there are wonderful resources on continuing on the journey of becoming an amazing public speaker, which includes understanding the psychology and neuroscience behind human perception and learning. For example, as highlighted in Rule 7, David JP Phillips has a wonderful TEDx talk on the subject [ 5 ], and “PowerPoint presentation flaws and failures: A psychological analysis,” by Kosslyn and colleagues is deeply detailed about a number of aspects of human cognition and presentation style [ 4 ]. There are many books on the topic, including the popular “Presentation Zen” by Garr Reynolds [ 11 ]. Finally, although briefly touched on here, the visualization of data is an entire topic of its own that is worth perfecting for both written and oral presentations of work, with fantastic resources like Edward Tufte’s “The Visual Display of Quantitative Information” [ 12 ] or the article “Visualization of Biomedical Data” by O’Donoghue and colleagues [ 13 ].

Acknowledgments

I would like to thank the countless presenters, colleagues, students, and mentors from which I have learned a great deal from on effective presentations. Also, a thank you to the wonderful resources published by organizations on how to increase inclusivity. A special thanks to Dr. Jason Papin and Dr. Michael Guertin on early feedback of this editorial.

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Presentation Skills: How to Present Research Results

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presentation techniques in research methodology

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This book is about designing, implementing and interpreting clinical research. This chapter is aimed at a discussion of how to present the research that has been performed. Although almost no one currently disagrees that a formal curriculum in research methodology is critical for a new investigator, the manner in which the results of a study are presented is presumed to be obvious, and training in the art of presentations is much less common. The belief is that good speakers are born, not made, and this is no more true than good researchers are born and not made. And so, the methodology of presentations should be an important part of a young investigators training. This chapter provides an introduction to delivering an effective presentation.

Speech is power; Speech is to persuade, to convert, to compel Ralph Wald Emerson I know from experience that “sometimes it is better to be quiet and be thought a fool than to open your mouth and remove all doubt”… Abraham Lincoln

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The majority of this chapter was taken from personal experience and extensive notes that I had taken from a large number or Presentation Skills Workshops that I have attended. Although I cannot give specific credit for individual pieces of information, I can credit the Instructors of those workshops as follows:

Sue Castorino, President, The Speaking Specialist, Chicago, IL, 1993.

Gerald Kelliher PhD, Associate Dean, Medical College of Pennsylvania.

Eleanor Lopez, Let’s Communicate Better, www.eleanorlopez.com

Power Speaking, and More, Joyce Newman Communications Inc.

Jerry Michaels-Senior Consultant CommCore Communication Strategies.

Science and Medicine Canada, Presentation and Platform Skills Workshop, 1992.

Wyeth Ayerst Laboratories, Ciba-Geigy, Schering, Pfizer, and KOS Pharmaceuticals for sponsoring many of the Presentation Skills Workshops that I attended.

Foley RP, Smilansky J. Teaching techniques, a handbook for health professionals. New York: McGraw-Hill Book; 1980. p. 1–14.

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Garson A, Gutgesell H, Pinsky WW, McNamara DG. The 10-minute talk, slides, writing, and delivery. Am Heart J. 1985;111:193–203.

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Griswold A. 9 ways to sound like you know what you are talking about Business Insider. www.businessinsider.com/common-speaking-mistakes-2013

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Glasser, S.P. (2014). Presentation Skills: How to Present Research Results. In: Glasser, S. (eds) Essentials of Clinical Research. Springer, Cham. https://doi.org/10.1007/978-3-319-05470-4_22

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How to make a scientific presentation

How to make a scientific presentation

Scientific presentation outlines

Questions to ask yourself before you write your talk, 1. how much time do you have, 2. who will you speak to, 3. what do you want the audience to learn from your talk, step 1: outline your presentation, step 2: plan your presentation slides, step 3: make the presentation slides, slide design, text elements, animations and transitions, step 4: practice your presentation, final thoughts, frequently asked questions about preparing scientific presentations, related articles.

A good scientific presentation achieves three things: you communicate the science clearly, your research leaves a lasting impression on your audience, and you enhance your reputation as a scientist.

But, what is the best way to prepare for a scientific presentation? How do you start writing a talk? What details do you include, and what do you leave out?

It’s tempting to launch into making lots of slides. But, starting with the slides can mean you neglect the narrative of your presentation, resulting in an overly detailed, boring talk.

The key to making an engaging scientific presentation is to prepare the narrative of your talk before beginning to construct your presentation slides. Planning your talk will ensure that you tell a clear, compelling scientific story that will engage the audience.

In this guide, you’ll find everything you need to know to make a good oral scientific presentation, including:

  • The different types of oral scientific presentations and how they are delivered;
  • How to outline a scientific presentation;
  • How to make slides for a scientific presentation.

Our advice results from delving into the literature on writing scientific talks and from our own experiences as scientists in giving and listening to presentations. We provide tips and best practices for giving scientific talks in a separate post.

There are two main types of scientific talks:

  • Your talk focuses on a single study . Typically, you tell the story of a single scientific paper. This format is common for short talks at contributed sessions in conferences.
  • Your talk describes multiple studies. You tell the story of multiple scientific papers. It is crucial to have a theme that unites the studies, for example, an overarching question or problem statement, with each study representing specific but different variations of the same theme. Typically, PhD defenses, invited seminars, lectures, or talks for a prospective employer (i.e., “job talks”) fall into this category.

➡️ Learn how to prepare an excellent thesis defense

The length of time you are allotted for your talk will determine whether you will discuss a single study or multiple studies, and which details to include in your story.

The background and interests of your audience will determine the narrative direction of your talk, and what devices you will use to get their attention. Will you be speaking to people specializing in your field, or will the audience also contain people from disciplines other than your own? To reach non-specialists, you will need to discuss the broader implications of your study outside your field.

The needs of the audience will also determine what technical details you will include, and the language you will use. For example, an undergraduate audience will have different needs than an audience of seasoned academics. Students will require a more comprehensive overview of background information and explanations of jargon but will need less technical methodological details.

Your goal is to speak to the majority. But, make your talk accessible to the least knowledgeable person in the room.

This is called the thesis statement, or simply the “take-home message”. Having listened to your talk, what message do you want the audience to take away from your presentation? Describe the main idea in one or two sentences. You want this theme to be present throughout your presentation. Again, the thesis statement will depend on the audience and the type of talk you are giving.

Your thesis statement will drive the narrative for your talk. By deciding the take-home message you want to convince the audience of as a result of listening to your talk, you decide how the story of your talk will flow and how you will navigate its twists and turns. The thesis statement tells you the results you need to show, which subsequently tells you the methods or studies you need to describe, which decides the angle you take in your introduction.

➡️ Learn how to write a thesis statement

The goal of your talk is that the audience leaves afterward with a clear understanding of the key take-away message of your research. To achieve that goal, you need to tell a coherent, logical story that conveys your thesis statement throughout the presentation. You can tell your story through careful preparation of your talk.

Preparation of a scientific presentation involves three separate stages: outlining the scientific narrative, preparing slides, and practicing your delivery. Making the slides of your talk without first planning what you are going to say is inefficient.

Here, we provide a 4 step guide to writing your scientific presentation:

  • Outline your presentation
  • Plan your presentation slides
  • Make the presentation slides
  • Practice your presentation

4 steps for making a scientific presentation.

Writing an outline helps you consider the key pieces of your talk and how they fit together from the beginning, preventing you from forgetting any important details. It also means you avoid changing the order of your slides multiple times, saving you time.

Plan your talk as discrete sections. In the table below, we describe the sections for a single study talk vs. a talk discussing multiple studies:

The following tips apply when writing the outline of a single study talk. You can easily adapt this framework if you are writing a talk discussing multiple studies.

Introduction: Writing the introduction can be the hardest part of writing a talk. And when giving it, it’s the point where you might be at your most nervous. But preparing a good, concise introduction will settle your nerves.

The introduction tells the audience the story of why you studied your topic. A good introduction succinctly achieves four things, in the following order.

  • It gives a broad perspective on the problem or topic for people in the audience who may be outside your discipline (i.e., it explains the big-picture problem motivating your study).
  • It describes why you did the study, and why the audience should care.
  • It gives a brief indication of how your study addressed the problem and provides the necessary background information that the audience needs to understand your work.
  • It indicates what the audience will learn from the talk, and prepares them for what will come next.

A good introduction not only gives the big picture and motivations behind your study but also concisely sets the stage for what the audience will learn from the talk (e.g., the questions your work answers, and/or the hypotheses that your work tests). The end of the introduction will lead to a natural transition to the methods.

Give a broad perspective on the problem. The easiest way to start with the big picture is to think of a hook for the first slide of your presentation. A hook is an opening that gets the audience’s attention and gets them interested in your story. In science, this might take the form of a why, or a how question, or it could be a statement about a major problem or open question in your field. Other examples of hooks include quotes, short anecdotes, or interesting statistics.

Why should the audience care? Next, decide on the angle you are going to take on your hook that links to the thesis of your talk. In other words, you need to set the context, i.e., explain why the audience should care. For example, you may introduce an observation from nature, a pattern in experimental data, or a theory that you want to test. The audience must understand your motivations for the study.

Supplementary details. Once you have established the hook and angle, you need to include supplementary details to support them. For example, you might state your hypothesis. Then go into previous work and the current state of knowledge. Include citations of these studies. If you need to introduce some technical methodological details, theory, or jargon, do it here.

Conclude your introduction. The motivation for the work and background information should set the stage for the conclusion of the introduction, where you describe the goals of your study, and any hypotheses or predictions. Let the audience know what they are going to learn.

Methods: The audience will use your description of the methods to assess the approach you took in your study and to decide whether your findings are credible. Tell the story of your methods in chronological order. Use visuals to describe your methods as much as possible. If you have equations, make sure to take the time to explain them. Decide what methods to include and how you will show them. You need enough detail so that your audience will understand what you did and therefore can evaluate your approach, but avoid including superfluous details that do not support your main idea. You want to avoid the common mistake of including too much data, as the audience can read the paper(s) later.

Results: This is the evidence you present for your thesis. The audience will use the results to evaluate the support for your main idea. Choose the most important and interesting results—those that support your thesis. You don’t need to present all the results from your study (indeed, you most likely won’t have time to present them all). Break down complex results into digestible pieces, e.g., comparisons over multiple slides (more tips in the next section).

Summary: Summarize your main findings. Displaying your main findings through visuals can be effective. Emphasize the new contributions to scientific knowledge that your work makes.

Conclusion: Complete the circle by relating your conclusions to the big picture topic in your introduction—and your hook, if possible. It’s important to describe any alternative explanations for your findings. You might also speculate on future directions arising from your research. The slides that comprise your conclusion do not need to state “conclusion”. Rather, the concluding slide title should be a declarative sentence linking back to the big picture problem and your main idea.

It’s important to end well by planning a strong closure to your talk, after which you will thank the audience. Your closing statement should relate to your thesis, perhaps by stating it differently or memorably. Avoid ending awkwardly by memorizing your closing sentence.

By now, you have an outline of the story of your talk, which you can use to plan your slides. Your slides should complement and enhance what you will say. Use the following steps to prepare your slides.

  • Write the slide titles to match your talk outline. These should be clear and informative declarative sentences that succinctly give the main idea of the slide (e.g., don’t use “Methods” as a slide title). Have one major idea per slide. In a YouTube talk on designing effective slides , researcher Michael Alley shows examples of instructive slide titles.
  • Decide how you will convey the main idea of the slide (e.g., what figures, photographs, equations, statistics, references, or other elements you will need). The body of the slide should support the slide’s main idea.
  • Under each slide title, outline what you want to say, in bullet points.

In sum, for each slide, prepare a title that summarizes its major idea, a list of visual elements, and a summary of the points you will make. Ensure each slide connects to your thesis. If it doesn’t, then you don’t need the slide.

Slides for scientific presentations have three major components: text (including labels and legends), graphics, and equations. Here, we give tips on how to present each of these components.

  • Have an informative title slide. Include the names of all coauthors and their affiliations. Include an attractive image relating to your study.
  • Make the foreground content of your slides “pop” by using an appropriate background. Slides that have white backgrounds with black text work well for small rooms, whereas slides with black backgrounds and white text are suitable for large rooms.
  • The layout of your slides should be simple. Pay attention to how and where you lay the visual and text elements on each slide. It’s tempting to cram information, but you need lots of empty space. Retain space at the sides and bottom of your slides.
  • Use sans serif fonts with a font size of at least 20 for text, and up to 40 for slide titles. Citations can be in 14 font and should be included at the bottom of the slide.
  • Use bold or italics to emphasize words, not underlines or caps. Keep these effects to a minimum.
  • Use concise text . You don’t need full sentences. Convey the essence of your message in as few words as possible. Write down what you’d like to say, and then shorten it for the slide. Remove unnecessary filler words.
  • Text blocks should be limited to two lines. This will prevent you from crowding too much information on the slide.
  • Include names of technical terms in your talk slides, especially if they are not familiar to everyone in the audience.
  • Proofread your slides. Typos and grammatical errors are distracting for your audience.
  • Include citations for the hypotheses or observations of other scientists.
  • Good figures and graphics are essential to sustain audience interest. Use graphics and photographs to show the experiment or study system in action and to explain abstract concepts.
  • Don’t use figures straight from your paper as they may be too detailed for your talk, and details like axes may be too small. Make new versions if necessary. Make them large enough to be visible from the back of the room.
  • Use graphs to show your results, not tables. Tables are difficult for your audience to digest! If you must present a table, keep it simple.
  • Label the axes of graphs and indicate the units. Label important components of graphics and photographs and include captions. Include sources for graphics that are not your own.
  • Explain all the elements of a graph. This includes the axes, what the colors and markers mean, and patterns in the data.
  • Use colors in figures and text in a meaningful, not random, way. For example, contrasting colors can be effective for pointing out comparisons and/or differences. Don’t use neon colors or pastels.
  • Use thick lines in figures, and use color to create contrasts in the figures you present. Don’t use red/green or red/blue combinations, as color-blind audience members can’t distinguish between them.
  • Arrows or circles can be effective for drawing attention to key details in graphs and equations. Add some text annotations along with them.
  • Write your summary and conclusion slides using graphics, rather than showing a slide with a list of bullet points. Showing some of your results again can be helpful to remind the audience of your message.
  • If your talk has equations, take time to explain them. Include text boxes to explain variables and mathematical terms, and put them under each term in the equation.
  • Combine equations with a graphic that shows the scientific principle, or include a diagram of the mathematical model.
  • Use animations judiciously. They are helpful to reveal complex ideas gradually, for example, if you need to make a comparison or contrast or to build a complicated argument or figure. For lists, reveal one bullet point at a time. New ideas appearing sequentially will help your audience follow your logic.
  • Slide transitions should be simple. Silly ones distract from your message.
  • Decide how you will make the transition as you move from one section of your talk to the next. For example, if you spend time talking through details, provide a summary afterward, especially in a long talk. Another common tactic is to have a “home slide” that you return to multiple times during the talk that reinforces your main idea or message. In her YouTube talk on designing effective scientific presentations , Stanford biologist Susan McConnell suggests using the approach of home slides to build a cohesive narrative.

To deliver a polished presentation, it is essential to practice it. Here are some tips.

  • For your first run-through, practice alone. Pay attention to your narrative. Does your story flow naturally? Do you know how you will start and end? Are there any awkward transitions? Do animations help you tell your story? Do your slides help to convey what you are saying or are they missing components?
  • Next, practice in front of your advisor, and/or your peers (e.g., your lab group). Ask someone to time your talk. Take note of their feedback and the questions that they ask you (you might be asked similar questions during your real talk).
  • Edit your talk, taking into account the feedback you’ve received. Eliminate superfluous slides that don’t contribute to your takeaway message.
  • Practice as many times as needed to memorize the order of your slides and the key transition points of your talk. However, don’t try to learn your talk word for word. Instead, memorize opening and closing statements, and sentences at key junctures in the presentation. Your presentation should resemble a serious but spontaneous conversation with the audience.
  • Practicing multiple times also helps you hone the delivery of your talk. While rehearsing, pay attention to your vocal intonations and speed. Make sure to take pauses while you speak, and make eye contact with your imaginary audience.
  • Make sure your talk finishes within the allotted time, and remember to leave time for questions. Conferences are particularly strict on run time.
  • Anticipate questions and challenges from the audience, and clarify ambiguities within your slides and/or speech in response.
  • If you anticipate that you could be asked questions about details but you don’t have time to include them, or they detract from the main message of your talk, you can prepare slides that address these questions and place them after the final slide of your talk.

➡️ More tips for giving scientific presentations

An organized presentation with a clear narrative will help you communicate your ideas effectively, which is essential for engaging your audience and conveying the importance of your work. Taking time to plan and outline your scientific presentation before writing the slides will help you manage your nerves and feel more confident during the presentation, which will improve your overall performance.

A good scientific presentation has an engaging scientific narrative with a memorable take-home message. It has clear, informative slides that enhance what the speaker says. You need to practice your talk many times to ensure you deliver a polished presentation.

First, consider who will attend your presentation, and what you want the audience to learn about your research. Tailor your content to their level of knowledge and interests. Second, create an outline for your presentation, including the key points you want to make and the evidence you will use to support those points. Finally, practice your presentation several times to ensure that it flows smoothly and that you are comfortable with the material.

Prepare an opening that immediately gets the audience’s attention. A common device is a why or a how question, or a statement of a major open problem in your field, but you could also start with a quote, interesting statistic, or case study from your field.

Scientific presentations typically either focus on a single study (e.g., a 15-minute conference presentation) or tell the story of multiple studies (e.g., a PhD defense or 50-minute conference keynote talk). For a single study talk, the structure follows the scientific paper format: Introduction, Methods, Results, Summary, and Conclusion, whereas the format of a talk discussing multiple studies is more complex, but a theme unifies the studies.

Ensure you have one major idea per slide, and convey that idea clearly (through images, equations, statistics, citations, video, etc.). The slide should include a title that summarizes the major point of the slide, should not contain too much text or too many graphics, and color should be used meaningfully.

presentation techniques in research methodology

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Writing an Abstract

Oral presentation, compiling a powerpoint.

Abstract : a short statement that describes a longer work.

  • Indicate the subject.
  • Describe the purpose of the investigation.
  • Briefly discuss the method used.
  • Make a statement about the result.

Oral presentations usually introduce a discussion of a topic or research paper. A good oral presentation is focused, concise, and interesting in order to trigger a discussion.

  • Be well prepared; write a detailed outline.
  • Introduce the subject.
  • Talk about the sources and the method.
  • Indicate if there are conflicting views about the subject (conflicting views trigger discussion).
  • Make a statement about your new results (if this is your research paper).
  • Use visual aids or handouts if appropriate.

An effective PowerPoint presentation is just an aid to the presentation, not the presentation itself .

  • Be brief and concise.
  • Focus on the subject.
  • Attract attention; indicate interesting details.
  • If possible, use relevant visual illustrations (pictures, maps, charts graphs, etc.).
  • Use bullet points or numbers to structure the text.
  • Make clear statements about the essence/results of the topic/research.
  • Don't write down the whole outline of your paper and nothing else.
  • Don't write long full sentences on the slides.
  • Don't use distracting colors, patterns, pictures, decorations on the slides.
  • Don't use too complicated charts, graphs; only those that are relatively easy to understand.
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Preparing and Presenting Effective Research Posters

Associated data.

APPENDIX A.2. Comparison of Research Papers, Presentations, and Posters—Contents.

Posters are a common way to present results of a statistical analysis, program evaluation, or other project at professional conferences. Often, researchers fail to recognize the unique nature of the format, which is a hybrid of a published paper and an oral presentation. This methods note demonstrates how to design research posters to convey study objectives, methods, findings, and implications effectively to varied professional audiences.

A review of existing literature on research communication and poster design is used to identify and demonstrate important considerations for poster content and layout. Guidelines on how to write about statistical methods, results, and statistical significance are illustrated with samples of ineffective writing annotated to point out weaknesses, accompanied by concrete examples and explanations of improved presentation. A comparison of the content and format of papers, speeches, and posters is also provided.

Each component of a research poster about a quantitative analysis should be adapted to the audience and format, with complex statistical results translated into simplified charts, tables, and bulleted text to convey findings as part of a clear, focused story line.

Conclusions

Effective research posters should be designed around two or three key findings with accompanying handouts and narrative description to supply additional technical detail and encourage dialog with poster viewers.

An assortment of posters is a common way to present research results to viewers at a professional conference. Too often, however, researchers treat posters as poor cousins to oral presentations or published papers, failing to recognize the opportunity to convey their findings while interacting with individual viewers. By neglecting to adapt detailed paragraphs and statistical tables into text bullets and charts, they make it harder for their audience to quickly grasp the key points of the poster. By simply posting pages from the paper, they risk having people merely skim their work while standing in the conference hall. By failing to devise narrative descriptions of their poster, they overlook the chance to learn from conversations with their audience.

Even researchers who adapt their paper into a well-designed poster often forget to address the range of substantive and statistical training of their viewers. This step is essential for those presenting to nonresearchers but also pertains when addressing interdisciplinary research audiences. Studies of policymakers ( DiFranza and the Staff of the Advocacy Institute 1996 ; Sorian and Baugh 2002 ) have demonstrated the importance of making it readily apparent how research findings apply to real-world issues rather than imposing on readers to translate statistical findings themselves.

This methods note is intended to help researchers avoid such pitfalls as they create posters for professional conferences. The first section describes objectives of research posters. The second shows how to describe statistical results to viewers with varied levels of statistical training, and the third provides guidelines on the contents and organization of the poster. Later sections address how to prepare a narrative and handouts to accompany a research poster. Because researchers often present the same results as published research papers, spoken conference presentations, and posters, Appendix A compares similarities and differences in the content, format, and audience interaction of these three modes of presenting research results. Although the focus of this note is on presentation of quantitative research results, many of the guidelines about how to prepare and present posters apply equally well to qualitative studies.

WHAT IS A RESEARCH POSTER?

Preparing a poster involves not only creating pages to be mounted in a conference hall, but also writing an associated narrative and handouts, and anticipating the questions you are likely to encounter during the session. Each of these elements should be adapted to the audience, which may include people with different levels of familiarity with your topic and methods ( Nelson et al. 2002 ; Beilenson 2004 ). For example, the annual meeting of the American Public Health Association draws academics who conduct complex statistical analyses along with practitioners, program planners, policymakers, and journalists who typically do not.

Posters are a hybrid form—more detailed than a speech but less than a paper, more interactive than either ( Appendix A ). In a speech, you (the presenter) determine the focus of the presentation, but in a poster session, the viewers drive that focus. Different people will ask about different facets of your research. Some might do policy work or research on a similar topic or with related data or methods. Others will have ideas about how to apply or extend your work, raising new questions or suggesting different contrasts, ways of classifying data, or presenting results. Beilenson (2004) describes the experience of giving a poster as a dialogue between you and your viewers.

By the end of an active poster session, you may have learned as much from your viewers as they have from you, especially if the topic, methods, or audience are new to you. For instance, at David Snowdon's first poster presentation on educational attainment and longevity using data from The Nun Study, another researcher returned several times to talk with Snowdon, eventually suggesting that he extend his research to focus on Alzheimer's disease, which led to an important new direction in his research ( Snowdon 2001 ). In addition, presenting a poster provides excellent practice in explaining quickly and clearly why your project is important and what your findings mean—a useful skill to apply when revising a speech or paper on the same topic.

WRITING FOR A VARIED PROFESSIONAL AUDIENCE

Audiences at professional conferences vary considerably in their substantive and methodological backgrounds. Some will be experts on your topic but not your methods, some will be experts on your methods but not your topic, and most will fall somewhere in between. In addition, advances in research methods imply that even researchers who received cutting-edge methodological training 10 or 20 years ago might not be conversant with the latest approaches. As you design your poster, provide enough background on both the topic and the methods to convey the purpose, findings, and implications of your research to the expected range of readers.

Telling a Simple, Clear Story

Write so your audience can understand why your work is of interest to them, providing them with a clear take-home message that they can grasp in the few minutes they will spend at your poster. Experts in communications and poster design recommend planning your poster around two to three key points that you want your audience to walk away with, then designing the title, charts, and text to emphasize those points ( Briscoe 1996 ; Nelson et al. 2002 ; Beilenson 2004 ). Start by introducing the two or three key questions you have decided will be the focus of your poster, and then provide a brief overview of data and methods before presenting the evidence to answer those questions. Close with a summary of your findings and their implications for research and policy.

A 2001 survey of government policymakers showed that they prefer summaries of research to be written so they can immediately see how the findings relate to issues currently facing their constituencies, without wading through a formal research paper ( Sorian and Baugh 2002 ). Complaints that surfaced about many research reports included that they were “too long, dense, or detailed,” or “too theoretical, technical, or jargony.” On average, respondents said they read only about a quarter of the research material they receive for detail, skim about half of it, and never get to the rest.

To ensure that your poster is one viewers will read, understand, and remember, present your analyses to match the issues and questions of concern to them, rather than making readers translate your statistical results to fit their interests ( DiFranza and the Staff of the Advocacy Institute 1996 ; Nelson et al. 2002 ). Often, their questions will affect how you code your data, specify your model, or design your intervention and evaluation, so plan ahead by familiarizing yourself with your audience's interests and likely applications of your study findings. In an academic journal article, you might report parameter estimates and standard errors for each independent variable in your regression model. In the poster version, emphasize findings for specific program design features, demographic, or geographic groups, using straightforward means of presenting effect size and statistical significance; see “Describing Numeric Patterns and Contrasts” and “Presenting Statistical Test Results” below.

The following sections offer guidelines on how to present statistical findings on posters, accompanied by examples of “poor” and “better” descriptions—samples of ineffective writing annotated to point out weaknesses, accompanied by concrete examples and explanations of improved presentation. These ideas are illustrated with results from a multilevel analysis of disenrollment from the State Children's Health Insurance Program (SCHIP; Phillips et al. 2004 ). I chose that paper to show how to prepare a poster about a sophisticated quantitative analysis of a topic of interest to HSR readers, and because I was a collaborator in that study, which was presented in the three formats compared here—as a paper, a speech, and a poster.

Explaining Statistical Methods

Beilenson (2004) and Briscoe (1996) suggest keeping your description of data and methods brief, providing enough information for viewers to follow the story line and evaluate your approach. Avoid cluttering the poster with too much technical detail or obscuring key findings with excessive jargon. For readers interested in additional methodological information, provide a handout and a citation to the pertinent research paper.

As you write about statistical methods or other technical issues, relate them to the specific concepts you study. Provide synonyms for technical and statistical terminology, remembering that many conferences of interest to policy researchers draw people from a range of disciplines. Even with a quantitatively sophisticated audience, don't assume that people will know the equivalent vocabulary used in other fields. A few years ago, the journal Medical Care published an article whose sole purpose was to compare statistical terminology across various disciplines involved in health services research so that people could understand one another ( Maciejewski et al. 2002 ). After you define the term you plan to use, mention the synonyms from the various fields represented in your audience.

Consider whether acronyms are necessary on your poster. Avoid them if they are not familiar to the field or would be used only once or twice on your poster. If you use acronyms, spell them out at first usage, even those that are common in health services research such as “HEDIS®”(Health Plan Employer Data and Information Set) or “HLM”(hierarchical linear model).

Poor: “We use logistic regression and a discrete-time hazards specification to assess relative hazards of SCHIP disenrollment, with plan level as our key independent variable.” Comment: Terms like “discrete-time hazards specification” may be confusing to readers without training in those methods, which are relatively new on the scene. Also the meaning of “SCHIP” or “plan level” may be unfamiliar to some readers unless defined earlier on the poster.
Better: “Chances of disenrollment from the State Children's Health Insurance Program (SCHIP) vary by amount of time enrolled, so we used hazards models (also known as event history analysis or survival analysis) to correct for those differences when estimating disenrollment patterns for SCHIP plans for different income levels.” Comment: This version clarifies the terms and concepts, naming the statistical method and its synonyms, and providing a sense of why this type of analysis is needed.

To explain a statistical method or assumption, paraphrase technical terms and illustrate how the analytic approach applies to your particular research question and data:

Poor : “The data structure can be formulated as a two-level hierarchical linear model, with families (the level-1 unit of analysis) nested within counties (the level-2 unit of analysis).” Comment: Although this description would be fine for readers used to working with this type of statistical model, those who aren't conversant with those methods may be confused by terminology such as “level-1” and “unit of analysis.”
Better: “The data have a hierarchical (or multilevel) structure, with families clustered within counties.” Comment: By replacing “nested” with the more familiar “clustered,” identifying the specific concepts for the two levels of analysis, and mentioning that “hierarchical” and “multilevel” refer to the same type of analytic structure, this description relates the generic class of statistical model to this particular study.

Presenting Results with Charts

Charts are often the preferred way to convey numeric patterns, quickly revealing the relative sizes of groups, comparative levels of some outcome, or directions of trends ( Briscoe 1996 ; Tufte 2001 ; Nelson et al. 2002 ). As Beilenson puts it, “let your figures do the talking,” reducing the need for long text descriptions or complex tables with lots of tiny numbers. For example, create a pie chart to present sample composition, use a simple bar chart to show how the dependent variable varies across subgroups, or use line charts or clustered bar charts to illustrate the net effects of nonlinear specifications or interactions among independent variables ( Miller 2005 ). Charts that include confidence intervals around point estimates are a quick and effective way to present effect size, direction, and statistical significance. For multivariate analyses, consider presenting only the results for the main variables of interest, listing the other variables in the model in a footnote and including complex statistical tables in a handout.

Provide each chart with a title (in large type) that explains the topic of that chart. A rhetorical question or summary of the main finding can be very effective. Accompany each chart with a few annotations that succinctly describe the patterns in that chart. Although each chart page should be self-explanatory, be judicious: Tufte (2001) cautions against encumbering your charts with too much “nondata ink”—excessive labeling or superfluous features such as arrows and labels on individual data points. Strive for a balance between guiding your readers through the findings and maintaining a clean, uncluttered poster. Use chart types that are familiar to your expected audience. Finally, remember that you can flesh out descriptions of charts and tables in your script rather than including all the details on the poster itself; see “Narrative to Accompany a Poster.”

Describing Numeric Patterns and Contrasts

As you describe patterns or numeric contrasts, whether from simple calculations or complex statistical models, explain both the direction and magnitude of the association. Incorporate the concepts under study and the units of measurement rather than simply reporting coefficients (β's) ( Friedman 1990 ; Miller 2005 ).

Poor: “Number of enrolled children in the family is correlated with disenrollment.” Comment: Neither the direction nor the size of the association is apparent.
Poor [version #2]: “The log-hazard of disenrollment for one-child families was 0.316.” Comment: Most readers find it easier to assess the size and direction from hazards ratios (a form of relative risk) instead of log-hazards (log-relative risks, the β's from a hazards model).
Better: “Families with only one child enrolled in the program were about 1.4 times as likely as larger families to disenroll.” Comment: This version explains the association between number of children and disenrollment without requiring viewers to exponentiate the log-hazard in their heads to assess the size and direction of that association. It also explicitly identifies the group against which one-child families are compared in the model.

Presenting Statistical Test Results

On your poster, use an approach to presenting statistical significance that keeps the focus on your results, not on the arithmetic needed to conduct inferential statistical tests. Replace standard errors or test statistics with confidence intervals, p- values, or symbols, or use formatting such as boldface, italics, or a contrasting color to denote statistically significant findings ( Davis 1997 ; Miller 2005 ). Include the detailed statistical results in handouts for later perusal.

To illustrate these recommendations, Figures 1 and ​ and2 2 demonstrate how to divide results from a complex, multilevel model across several poster pages, using charts and bullets in lieu of the detailed statistical table from the scientific paper ( Table 1 ; Phillips et al. 2004 ). Following experts' advice to focus on one or two key points, these charts emphasize the findings from the final model (Model 5) rather than also discussing each of the fixed- and random-effects specifications from the paper.

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Presenting Complex Statistical Results Graphically

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Text Summary of Additional Statistical Results

Multilevel Discrete-Time Hazards Models of Disenrollment from SCHIP, New Jersey, January 1998–April 2000

Source : Phillips et al. (2004) .

SCHIP, State Children's Health Insurance Program; LRH, log relative-hazard; SE, standard error.

Figure 1 uses a chart (also from the paper) to present the net effects of a complicated set of interactions between two family-level traits (race and SCHIP plan) and a cross-level interaction between race of the family and county physician racial composition. The title is a rhetorical question that identifies the issue addressed in the chart, and the annotations explain the pattern. The chart version substantially reduces the amount of time viewers need to understand the main take-home point, averting the need to mentally sum and exponentiate several coefficients from the table.

Figure 2 uses bulleted text to summarize other key results from the model, translating log-relative hazards into hazards ratios and interpreting them with minimal reliance on jargon. The results for family race, SCHIP plan, and county physician racial composition are not repeated in Figure 2 , averting the common problem of interpreting main effect coefficients and interaction coefficients without reference to one another.

Alternatively, replace the text summary shown in Figure 2 with Table 2 —a simplified version of Table 1 which presents only the results for Model 5, replaces log-relative hazards with hazards ratios, reports associated confidence intervals in lieu of standard errors, and uses boldface to denote statistical significance. (On a color slide, use a contrasting color in lieu of bold.)

Relative Risks of SCHIP Disenrollment for Other * Family and County Characteristics, New Jersey, January 1998–April 2000

Statistically significant associations are shown in bold.

Based on hierarchical linear model controlling for months enrolled, months-squared, race, SCHIP plan, county physician racial composition, and all variables shown here. Scaled deviance =30,895. Random effects estimate for between-county variance =0.005 (standard error =0.006). SCHIP, State Children's Health Insurance Program; 95% CI, 95% confidence interval.

CONTENTS AND ORGANIZATION OF A POSTER

Research posters are organized like scientific papers, with separate pages devoted to the objectives and background, data and methods, results, and conclusions ( Briscoe 1996 ). Readers view the posters at their own pace and at close range; thus you can include more detail than in slides for a speech (see Appendix A for a detailed comparison of content and format of papers, speeches, and posters). Don't simply post pages from the scientific paper, which are far too text-heavy for a poster. Adapt them, replacing long paragraphs and complex tables with bulleted text, charts, and simple tables ( Briscoe 1996 ; Beilenson 2004 ). Fink (1995) provides useful guidelines for writing text bullets to convey research results. Use presentation software such as PowerPoint to create your pages or adapt them from related slides, facilitating good page layout with generous type size, bullets, and page titles. Such software also makes it easy to create matching handouts (see “Handouts”).

The “W's” (who, what, when, where, why) are an effective way to organize the elements of a poster.

  • In the introductory section, describe what you are studying, why it is important, and how your analysis will add to the existing literature in the field.
  • In the data and methods section of a statistical analysis, list when, where, who, and how the data were collected, how many cases were involved, and how the data were analyzed. For other types of interventions or program evaluations, list who, when, where, and how many, along with how the project was implemented and assessed.
  • In the results section, present what you found.
  • In the conclusion, return to what you found and how it can be used to inform programs or policies related to the issue.

Number and Layout of Pages

To determine how many pages you have to work with, find out the dimensions of your assigned space. A 4′ × 8′ bulletin board accommodates the equivalent of about twenty 8.5″ × 11″ pages, but be selective—no poster can capture the full detail of a large series of multivariate models. A trifold presentation board (3′ high by 4′ wide) will hold roughly a dozen pages, organized into three panels ( Appendix B ). Breaking the arrangement into vertical sections allows viewers to read each section standing in one place while following the conventions of reading left-to-right and top-to-bottom ( Briscoe 1996 ).

  • At the top of the poster, put an informative title in a large, readable type size. On a 4′ × 8′ bulletin board, there should also be room for an institutional logo.

An external file that holds a picture, illustration, etc.
Object name is hesr0042-0311-f3.jpg

Suggested Layout for a 4′ × 8′ poster.

  • In the left-hand panel, set the stage for the research question, conveying why the topic is of policy interest, summarizing major empirical or theoretical work on related topics, and stating your hypotheses or project aims, and explaining how your work fills in gaps in previous analyses.
  • In the middle panel, briefly describe your data source, variables, and methods, then present results in tables or charts accompanied by text annotations. Diagrams, maps, and photographs are very effective for conveying issues difficult to capture succinctly in words ( Miller 2005 ), and to help readers envision the context. A schematic diagram of relationships among variables can be useful for illustrating causal order. Likewise, a diagram can be a succinct way to convey timing of different components of a longitudinal study or the nested structure of a multilevel dataset.
  • In the right-hand panel, summarize your findings and relate them back to the research question or project aims, discuss strengths and limitations of your approach, identify research, practice, or policy implications, and suggest directions for future research.

Figure 3 (adapted from Beilenson 2004 ) shows a suggested layout for a 4′ × 8′ bulletin board, designed to be created using software such as Pagemaker that generates a single-sheet presentation; Appendix C shows a complete poster version of the Phillips et al. (2004) multilevel analysis of SCHIP disenrollment. If hardware or budget constraints preclude making a single-sheet poster, a similar configuration can be created using standard 8.5″ × 11″ pages in place of the individual tables, charts, or blocks of text shown in Figure 3 .

Find out well in advance how the posters are to be mounted so you can bring the appropriate supplies. If the room is set up for table-top presentations, tri-fold poster boards are essential because you won't have anything to attach a flat poster board or pages to. If you have been assigned a bulletin board, bring push-pins or a staple gun.

Regardless of whether you will be mounting your poster at the conference or ahead of time, plan how the pages are to be arranged. Experiment with different page arrangements on a table marked with the dimensions of your overall poster. Once you have a final layout, number the backs of the pages or draw a rough sketch to work from as you arrange the pages on the board. If you must pin pages to a bulletin board at the conference venue, allow ample time to make them level and evenly spaced.

Other Design Considerations

A few other issues to keep in mind as you design your poster. Write a short, specific title that fits in large type size on the title banner of your poster. The title will be potential readers' first glimpse of your poster, so make it inviting and easy to read from a distance—at least 40-point type, ideally larger. Beilenson (2004) advises embedding your key finding in the title so viewers don't have to dig through the abstract or concluding page to understand the purpose and conclusions of your work. A caution: If you report a numeric finding in your title, keep in mind that readers may latch onto it as a “factoid” to summarize your conclusions, so select and phrase it carefully ( McDonough 2000 ).

Use at least 14-point type for the body of the poster text. As Briscoe (1996) points out, “many in your audience have reached the bifocal age” and all of them will read your poster while standing, hence long paragraphs in small type will not be appreciated! Make judicious use of color. Use a clear, white, or pastel for the background, with black or another dark color for most text, and a bright, contrasting shade to emphasize key points or to identify statistically significant results ( Davis 1997 ).

NARRATIVE TO ACCOMPANY A POSTER

Prepare a brief oral synopsis of the purpose, findings, and implications of your work to say to interested parties as they pause to read your poster. Keep it short—a few sentences that highlight what you are studying, a couple of key findings, and why they are important. Design your overview as a “sound byte” that captures your main points in a succinct and compelling fashion ( Beilenson 2004 ). After hearing your introduction, listeners will either nod and move along or comment on some aspect of your work that intrigues them. You can then tailor additional discussion to individual listeners, adjusting the focus and amount of detail to suit their interests. Gesture at the relevant pages as you make each point, stating the purpose of each chart or table and explaining its layout before describing the numeric findings; see Miller (2005) for guidelines on how to explain tables and charts to a live audience. Briscoe (1996) points out that these mini-scripts are opportunities for you to fill in details of your story line, allowing you to keep the pages themselves simple and uncluttered.

Prepare short answers to likely questions about various aspects of your work, such as why it is important from a policy or research perspective, or descriptions of data, methods, and specific results. Think of these as little modules from an overall speech—concise descriptions of particular elements of your study that you can choose among in response to questions that arise. Beilenson (2004) also recommends developing a few questions to ask your viewers, inquiring about their reactions to your findings, ideas for additional questions, or names of others working on the topic.

Practice your poster presentation in front of a test audience acquainted with the interests and statistical proficiency of your expected viewers. Ideally, your critic should not be too familiar with your work: A fresh set of eyes and ears is more likely to identify potential points of confusion than someone who is jaded from working closely with the material while writing the paper or drafting the poster ( Beilenson 2004 ). Ask your reviewer to identify elements that are unclear, flag jargon to be paraphrased or defined, and recommend changes to improve clarity ( Miller 2005 ). Have them critique your oral presentation as well as the contents and layout of the poster.

Prepare handouts to distribute to interested viewers. These can be produced from slides created in presentation software, printed several to a page along with a cover page containing the abstract and your contact information. Or package an executive summary or abstract with a few key tables or charts. Handouts provide access to the more detailed literature review, data and methods, full set of results, and citations without requiring viewers to read all of that information from the poster ( Beilenson 2004 ; Miller 2005 ). Although you also can bring copies of the complete paper, it is easier on both you and your viewers if you collect business cards or addresses and mail the paper later.

The quality and effectiveness of research posters at professional conferences is often compromised by authors' failure to take into account the unique nature of such presentations. One common error is posting numerous statistical tables and long paragraphs from a research paper—an approach that overwhelms viewers with too much detail for this type of format and presumes familiarity with advanced statistical techniques. Following recommendations from the literature on research communication and poster design, this paper shows how to focus each poster on a few key points, using charts and text bullets to convey results as part of a clear, straightforward story line, and supplementing with handouts and an oral overview.

Another frequent mistake is treating posters as a one-way means of communication. Unlike published papers, poster sessions are live presentations; unlike speeches, they allow for extended conversation with viewers. This note explains how to create an oral synopsis of the project, short modular descriptions of poster elements, and questions to encourage dialog. By following these guidelines, researchers can substantially improve their conference posters as vehicles to disseminate findings to varied research and policy audiences.

CHECKLIST FOR PREPARING AND PRESENTING AN EFFECTIVE RESEARCH POSTERS

  • Design poster to focus on two or three key points.
  • Adapt materials to suit expected viewers' knowledge of your topic and methods.
  • Design questions to meet their interests and expected applications of your work.
  • Paraphrase descriptions of complex statistical methods.
  • Spell out acronyms if used.
  • Replace large detailed tables with charts or small, simplified tables.
  • Accompany tables or charts with bulleted annotations of major findings.
  • Describe direction and magnitude of associations.
  • Use confidence intervals, p -values, symbols, or formatting to denote statistical significance.

Layout and Format

  • Organize the poster into background, data and methods, results, and study implications.
  • Divide the material into vertical sections on the poster.
  • Use at least 14-point type in the body of your poster, at least 40-point for the title.

Narrative Description

  • Rehearse a three to four sentence overview of your research objectives and main findings.
  • Summary of key studies and gaps in existing literature
  • Data and methods
  • Each table, chart, or set of bulleted results
  • Research, policy, and practice implications
  • Solicit their input on your findings
  • Develop additional questions for later analysis
  • Identify other researchers in the field
  • Prepare handouts to distribute to interested viewers.
  • Print slides from presentation software, several to a page.
  • Or package an executive summary or abstract with a few key tables or charts.
  • Include an abstract and contact information.

Acknowledgments

I would like to thank Ellen Idler, Julie Phillips, Deborah Carr, Diane (Deedee) Davis, and two anonymous reviewers for helpful comments on earlier drafts of this work.

Supplementary Material

The following supplementary material for this article is available online:

APPENDIX A.1. Comparison of Research Papers, Presentations, and Posters—Materials and Audience Interaction.

Suggested Layout for a Tri-Fold Presentation Board.

Example Research Poster of Phillips et al. 2004 Study.

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Guide to Research Methods

About the guide

This guide will

  • Introduce you to a range of research methods
  • Help you think about the value and limitations of different research methods
  • Identify when to use alternative research methods

You should use the guide

  • After or while you establish your research questions (See the Guide to Research Questions )
  • When you are completing your Research Design Framework
  • When you are thinking about who you want to talk to and why (See the Guide to Sampling )

You should print or read this guide

These slides are set up so that they can be printed back to back (two/four sided) to give:

  • A short hand overview about when to use each method
  • A summary of the method, what it’s good for and limitations (linking to other slides in this pack)

Choosing research methods

When you need to think about which method is best in theory and in practice

Choosing Research Methods

Providing a rationale for the methods you choose to use and how you employ them.

  • What are your research goals? If you are looking to influence experts or policy makers, quantitative approaches will add weight to your findings. If you are looking to understand problems, inform innovation or develop a prototype, look at qualitative methods or user research
  • What are your research questions? If they begin with ‘explore’ or ‘what’ look at qualitative methods (talking). If they begin with ‘identify’ or ‘why’ look at quantitative (see guide to research questions )
  • What research traditions exist? You may choose to follow or challenge them. Think about whether you want your research to be noted for its quality and robustness or creative approach and unique insights
  • What are your/your teams skills? You may not be an expert in the most appropriate method so consider asking for other team members or commissioning out research
  • Who are you research participants? Think about your relationship to participants (especially if you are doing qualitative research) and how they will respond to you and the method. Consider if they are often consulted or surveyed and whether if could be helpful or unhelpful to stick with their comfort zone or not.

Using online tools

When you need to decide which tools to use for research

What to think about when choosing a tool to conduct research

  • What’s the cost to the research quality ? Most tools are ‘freemium’, use a basic version for free. BUT these are designed to annoy you to pay to do good research. Consider privacy settings, data access, storage and value for money. Survey tools will have no option to filter participants (if yes/no answer this q), a 10Q limit, no branding. Mapping/visualisations are published online and open source tools aren’t always user friendly
  • Start with user needs, understand the context and think about everyone. Consider what technology they have, how they will access the tool and what they need to do this. Do they have internet, data, time?
  • Be creative: Online tools may not be designed for research, but Google Forms, Trello, Workflowy and Slack are all valuable collaboration tools. Twitter and Facebook polls may increase participation in research. However, think about what they are missing, what they can’t do and pilot your analysis approach first
  • See what’s out there: This online sheet of Applied Social Research Guides and Resources includes a list of online tools for research and evaluation to test. Those widely used for your research method or sector are likely to be the best starting point. Some tools allow you to do research (see Tags for Twitter data capture), analyse it or present it in new ways (see Raw Graph s for data visualisation)

Contents: Methods summary

  • Structured Interviews : When you want to gain a broad range of perspectives about specific questions
  • Semi-Structured Interviews : When you want to gain in-depth insights about broad questions
  • Unstructured Interviews : When you want to gain in-depth insights about a complex research topics
  • Telephone Interviews : A tool for when you want to interview people quickly and easily
  • Guerilla Interviews : When you want to carry out user research or explore general perspectives quickly
  • Contextual Interviews : When you want to understand actions and particular experiences indepth and in context
  • Focus Groups : When you want to understand shared experiences and different perspectives
  • Participant Observation : When you want to ‘learn by doing’ or observe social interactions and behaviour
  • Ethnography : When you want to experience social practices, interactions and behaviour with minimal influence
  • Surveys: When you want to generate numerical data about the scale of people’s opinions and feelings
  • Mixed Methods: When one method cannot fully answer your main research question
  • User Research : When you want to learn about the behaviours and motivations of your target audience
  • Service Design Research : When you want to design a service to meet people’s needs.
  • Content Analysis : When you want to understand public discourse through secondary or online data
  • Workshops : When you want to engage stakeholders in research, generate ideas or codesign solutions
  • Usability tests : When you want to test prototypes or learn about problems with an existing service

Find out more

How to do good…

  • Applied social research: A curated online sheet of Applied Social Research Guides and Resources
  • Surveys : Guide to creating questions here and here , build on existing data/questions , analysis guide
  • Interviews : A nice overview here which includes how to structure an interview
  • User research : The GDS for intro guides and DisAmbiguity blog
  • Service design: This is Service Design Doing has great tools and formats for workshops

Inspiration for emerging research methods and creative formats for research

  • Ethnography and mixed methods presented well: Ikea At Home Report
  • User mapping techniques as a social research method NPC Report
  • User Research to understand domestic abuse experiences and the potential for technology Tech Vs Abuse
  • Using Twitter data for social research Demos
  • Data visualisation as a tool for research communication - Nesta data visualisation and Women’s Aid Map
  • Data journalism and data storytelling - Guardian reading the riots
  • An online games to shift perspective on a social problem - Financial Times Uber Story
  • Content analysis to map trends - Nesta analysed creative skills in job adverts
  • Issue mapping online - networks of websites and people on Twitter - Warwick University Issue Mapping

Structured Interviews

When you want to gain a broad range of perspectives about specific questions

Also consider

Semi-structured interviews

A conversation with a set structure (a script of fixed questions) and specific purpose. Can be a method to undertake a survey or called a ‘directed’ interview.

  • Asking standardised questions across many participants makes data easier to analyse and compare
  • Giving participants a clear guide about what you want to learn from them
  • Topics that would be too complex to capture in a questionnaire tick box/short response
  • Respondents with limited time, who want to consider responses in advance or do not want to write
  • The quality of the interview is less dependent on the interviewer and their rapport with the interviewee

Limitations (and how to avoid or what to consider instead)

  • The structure prevents participants from bringing in other ideas (consider semi-structured interviews )
  • Whilst quicker to conduct and analyse than semi-structured interviews, they are still resource intensive and only possible to do with limited numbers of people (consider questionnaires online - see surveys )

Semi-Structured Interviews

When you want to gain in-depth insights about broad questions

Participant Observation

User research

Focus groups

Semi-Structured interviews

Conversation with a structure (set of open questions) and clear purpose. Also called directed interviews.

  • Exploring a range of perspectives on research questions, engaging experts and getting buy-in to research
  • Gaining in-depth insights about how people feel or interpret complex issues
  • Topics which are sensitive, difficult to express in writing or to articulate views about in a survey
  • Allowing participants to respond in their words, framing what they see as important

Limitations

  • Quality can depend on interviewer skills and put people on the spot (consider setting topics in advance)
  • The set-up affects the quality of engagement and discussion (consider location, relationship with the interviewee and whether you should do a face to face or Telephone/Online interview )
  • Time consuming to do, analyse and compare (consider Structured Interviews or Focus groups )
  • Can lack validity as evidence (consider Surveys )
  • Explore what people say, think and remember, not what they actually do (consider Participant Observation contextual interviews or User Research ) or shared perspectives (consider Focus groups )
  • Easy to provide too much structure and prevent open exploration of a topic (see unstructured interviews )

Unstructured Interviews

When you want to gain in-depth insights about a complex research topics

Contextual interviews

Unstructured interviews

A loosely structured open conversation guided by research topics (also called non-directed interviews)

  • Very exploratory research and broad research questions
  • Letting the participant guide the interview according to their priorities and views
  • In-depth and broad discussion about a person's expertise, experiences and opinions
  • Participant can feel like the they are not saying the ‘right’ thing (explain technique and rationale well)
  • Whilst useful for expert interviews, an unstructured approach can give the impression that the interviewer is unprepared, lacks knowledge or the research purpose is unclear (consider semi-structured interviews )
  • Interviews are longer, resource intensive and only smaller numbers are possible (consider focus groups )
  • Generates in-depth insights that are difficult to analyse and compare
  • A lack of structure can encourage participants to focus in-depth on one thing they are positive about or know very well in-depth (consider using desk research to inform the interview topics)

Guerilla Interviews

When you want to carry out user research or explore general perspectives quickly and easily

An ‘impromptu’ approach to interviewing, often talking to real people on the street or at a key site

  • Gaining immediate responses to a tool or design and insights into a problem
  • Informal method means participants can be more relaxed and open
  • Speaking to a lot of people, simply, quickly and cheaply about one key question
  • User research and user experience of interacting with digital products
  • Speaking to people for convenience (users are available in a single place and time) introduces sample bias (but you can add more targeting and profiling of participants, see the Guide to Sampling )
  • The lack of formal structure can mean that you miss important questions or insights
  • Findings are often unreliable and not generalisable because they rely on a single type of user
  • Difficult to understand complexity or gain contextual insights

Telephone / online interviews

A tool for when you want to interview people quickly and easily

Telephone or Online interviews

A tool to conduct an interview (it is not a method in itself) which is not in person/ face to face

  • Conducting interviews without the costs of travel and meeting time (often shorter)
  • Expert and stakeholder interviews, when you already know the participant well or they are short of time
  • Taking notes and looking up information whilst interviewing is less disruptive than in person, easy to record
  • Sending informed consent information and interview questions in advance
  • Can be difficult to undertake an engaging interview (hard to build rapport on the phone)
  • Often need to be shorter and put alongside other meetings

What method are you using?

  • Structured interviews : When you want to gain a broad range of perspectives about specific questions
  • Semi-structured interviews : When you want to gain in-depth insights about broad questions
  • Unstructured interviews : When you want to gain in-depth insights about a complex research topics

Further guides to Interviews : A nice overview here , including how to structure an interview

Contextual Interview

When you want to understand actions and particular experiences in-depth and in context

Ethnography

Interviews conducted with people in a situational context relevant to the research question; also known as contextual inquiry.

  • Understanding what happens, experiences and emotions whilst interacting with a tool, service or event.
  • Easier for research participants to show rather than explain, participants are active and engaged
  • Uncover what happens, what people do, how they behave in the moment, rather than how they remember this and give meaning to these responses later.
  • Open and flexible method giving depth of insights about a tool or specific interaction
  • Time and resource intensive for the researcher
  • Each context is unique - making it difficult to generalise from or to answer broader research questions about experiences (consider semi-structured interviews )
  • The researcher influences the interactions and events (consider ethnography or participant observation )

When you want to understand shared experiences and different perspectives

Focus Groups

An organised discussion with a group of participants, led by a facilitator around a few key topics

  • Gaining several perspectives about the same topic quickly
  • Research contexts and topics where familiarity between participants can generate discussion about similar experiences (or different ones) which may not arise in a one to one interview
  • When attitudes, feelings and beliefs are more likely to be revealed in social gathering and interactions
  • Including tasks and creative methods to elicit views (e.g. shared ranking of importance of statements)
  • Difficult to identify the individual view from the group view (consider semi-structured interviews )
  • Group dynamics will affect the conversation focus and participation levels of different members
  • The role of the moderator is very significant. Good levels of group leadership and interpersonal skill are required to moderate a group successfully.
  • The group set-up is an ‘artificial’ social setting and discussion (consider Participant Observation )

Participant observation

When you want to ‘learn by doing’ and observe social interactions and behaviour

Participant observation/ shadowing

The researcher immerses themselves in lives of participants as an ‘observer’ of their behaviours, practices and interactions. A type of ethnography. The people being observed know about the research.

  • Understanding everyday behaviours, interactions and practice in the context that they occur
  • Gaining an intuitive understanding of what happens in practice and what this means for those involved
  • Allowing research participants to show you what they do, when they can’t describe and remember this well
  • Establishing topics for further investigation through more structured or focused research methods
  • If explicit (shadowing for example) the research situation is still ‘artificial’
  • Your audience may not respect it and can be difficult to generalise from (consider mixed methods)
  • The quality of the data is dependent on the researchers’ skills and relationships with participants

When you want to experience social practices, interactions and behaviour with minimal influence on what happens

The systematic study of a group of people or cultures to understand behaviours and interactions. The researcher becomes an ‘insider’. It is a way of presenting research findings, as well as a method, which can include participant observation, document analysis and visual methods.

  • When you need to be an ‘insider’ to fully access the research context (such as organisational cultures)
  • Presenting how everyday behaviours, interactions and practice occur in context
  • Gaining an in-depth knowledge of your research context, participants and social relationships
  • When little is known about a research context or topic
  • If covert (at a conference or workplace for example) it has implications for informed consent
  • If explicit (shadowing for example) the researcher’s presence can affect the interactions and findings

Example use case : Ikea At Home research study to understand how people feel about their home

When you want to generate numerical data about the scale of people’s opinions and feelings

Mixed Methods

A process of systematically collecting information from a large number of different people. Responses are summarised as statistics (online surveys automate this analysis for you).

  • Targeting specific types of research participant and providing data about their views
  • If designed well, they can be quick, simple and non intrusive for research participants
  • Findings can have more credibility than other methods because of their breadth
  • Describing, measuring and understanding (a basic questionnaire)
  • Statistical analysis, modelling cause and effect (large scale survey designed to represent the population)
  • Can raise more questions about what happens and why, lack depth of insight (consider mixed methods )
  • Hard to design well and require a lot of time upfront and data skills to analyse the results
  • Low completion rates and people feel ‘over surveyed’ (consider incentives )
  • Assumes people will be honest and sufficiently aware of the research context to provide credible answers.

Further information: A great guide to creating questions here and here , build on existing data/questions here

When one research method cannot fully answer your main research question

Mixed methods

Combining different methods to answer your research questions, can be a mix of quantitative or qualitative methods or both. It may mean working with different types of data, research designs or being part of a research team (covering different research disciplines)

  • Overcoming the limitation of relying on a single research method or approach
  • Triangulating findings (i.e. using an additional method) can give them more validity
  • Accessing different types of research participants
  • A more holistic understanding about how, why and the extent to which something happens
  • Answering different types of research questions about frequency and perceptions
  • Giving findings more validity and influence because of the range of data and insights
  • Requires a broader range of skills and more time to deliver, analyse and report on
  • Research design must have strong sequencing (when each method is used and analysed , why) to make the most of a mixed methods approach - not always possible in a tight timescale or short research project

User Research

When you want to learn about people’s needs, behaviours and motivations for using a service

Service Design

S emi-Structured Interviews

Usability testing

A research approach employed to understand users and their needs, motivations and behaviours, primarily to inform service design.

  • User-centered design processes which look to ensure services meet the needs of their audience
  • Gaining specific insights into how a person interacts with a digital tool or service
  • Exploring general needs, behaviours and motivations for a specific target group using a range of services
  • Focus on a tool or service can prevent wider analysis, relevance and applicability
  • Research can lack credibility due to small numbers, set up, documentation (often highly specific focus)
  • Can overlook those who do not use a service for a whole range of reasons

What method?

  • User research involves any method which looks at who users are, the problems they face, what they are trying to do and how they use existing services. This can create user personas, user journeys and user experience maps. It largely includes qualitative research methods.

When you want to design a service to meet people’s needs, including planning, organising, infrastructure, communication and components)

A research approach employed in the activity of planning and organising of people, infrastructure, communication and material components of a service, in order to improve quality and interaction.

  • Gaining a holistic picture of all components (infrastructure, people, organisations, culture) affecting how a person interacts with a service
  • Service design often begins with user research but participants in research include all those involved in delivering (not just using) a service, such as employees and stakeholders in an organisation as well as looking at the context and system which affect how a service works and its effectiveness

Content analysis

When you want to understand public discourse through secondary or online data

A systematic process of classifying and interpreting documents, text or images to analyse key discourses (their meaning) or to quantify patterns (such as word frequencies). This can be done manually or it can be automated.

  • Exploring the focus of messages, text or imagery and change over time
  • Secondary data sources, such as archives, online social media data (such as Tweets) and news articles
  • Gaining a qualitative or quantitative insights about key messages
  • Focuses on public and documented interpretations of events and experiences
  • Documents are not exhaustive and not all are accessible (or available online/freely)
  • Qualitative coding is time intensive to manually classify, reliant on researcher interpretation
  • Automated coding for key words can miss nuances and difficult to produce meaningful findings

When you want to engage stakeholders in research, generate ideas or codesign solutions

Also consider:

A tool to undertake research. It is an interactive session, often taking a full day, in which research participants sor stakeholders work intensively on an issue or question. The process can combine elements of qualitative research, brainstorming or problem solving.

  • Engaging stakeholders - building empathy with and understanding of research findings
  • Understanding problems or prototyping solutions, linked to user research and service design approaches
  • Participatory research, allowing participants to shape agendas and outcomes
  • Creative, collaborative and engaging activities to build rapport and understanding with participants
  • Participatory design, enabling participants to co-design solutions which work for them
  • Highly dependent on the right people attending and the facilitation skills
  • Can be a lot of time and effort to coordinate a workshop effectively and analyse findings
  • The immersive and collaborative environment makes it difficult to document effectively
  • Collaborative solutions may duplicate existing problems or solutions

When you want to test prototypes or learn about problems with an existing service

A user research method where you watch participants try to complete specific tasks using your service. Moderated testing involve interaction with the research participant, asking them to explain what they are doing, thinking and feeling. Unmoderated testing is completed alone by the participant.

  • Identify any usability issues with a digital service - for example, problems with the language or layout
  • Seeing if users understand what they need to do in order to complete designated tasks
  • Generating ideas to improve a prototype of existing digital service
  • Assessing user experience
  • Focus is not on ‘natural’ use (consider contextual interviews , participant observation , ethnography )
  • Data is about a specific design and interaction with a tool at that moment
  • Findings cannot be generalised or applicable more broadly to understand users and behaviours

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Education Standards

Radford university.

Learning Domain: Social Work

Standard: Basic Research Methodology

Lesson 10: Sampling in Qualitative Research

Lesson 11: qualitative measurement & rigor, lesson 12: qualitative design & data gathering, lesson 1: introduction to research, lesson 2: getting started with your research project, lesson 3: critical information literacy, lesson 4: paradigm, theory, and causality, lesson 5: research questions, lesson 6: ethics, lesson 7: measurement in quantitative research, lesson 8: sampling in quantitative research, lesson 9: quantitative research designs, powerpoint slides: sowk 621.01: research i: basic research methodology.

PowerPoint Slides: SOWK 621.01: Research I: Basic Research Methodology

The twelve lessons for SOWK 621.01: Research I: Basic Research Methodology as previously taught by Dr. Matthew DeCarlo at Radford University. Dr. DeCarlo and his team developed a complete package of materials that includes a textbook, ancillary materials, and a student workbook as part of a VIVA Open Course Grant.

The PowerPoint slides associated with the twelve lessons of the course, SOWK 621.01: Research I: Basic Research Methodology, as previously taught by Dr. Matthew DeCarlo at Radford University. 

presentation techniques in research methodology

Different Types of Research Presentations

Different Types of Research Presentations

There are many different types of research presentations, but the different types of presentations can be divided into two general categories: written presentations and oral presentations. Written research presentations include dissertations and theses, posters, grant and project proposals, blogs, websites, PowerPoint slides, etc. Oral research presentations include lectures, conference presentations, job talks, etc. Often, oral and written methods of presentation are combined to effectively convey information about research. For example, posters or PowerPoint slides may be used to support oral presentations of research, or information on posters may be supplemented with oral explanations. Whichever type of research presentation you choose for your research, you should remember the following about the similarities and differences between oral and written presentations.

Similarities Between Oral and Written Presentations

The fundamental elements of successfully presenting research apply to both oral and written presentations. Whether you choose to present your research orally or in written form, you should know and actively engage your audience in the presentation of your research to effectively deliver your ideas. Organization is also important in both written and oral presentations. You can create outlines of your research that you can use to help you organize information for both oral and written presentations.

Differences Between Oral and Written Presentations

The most important difference between oral and written presentations is the time that is available for your audience to process what you have presented about your research. In written presentations, your audience has an unlimited amount of time to read, re-read, and analyze your research; if your audience does not understand particularly dense elements of your research, your audience has plenty of time to mull over your research until it becomes more understandable. In oral   presentations, however, you generally have a limited amount of time to present your research, and your audience has even less time to understand what you have said. In both oral and written presentations (but particularly in oral presentations), you can help your audience understand your research by defining important key terms. After you have defined the key terms for your written or oral presentation, you must use them and any other jargon consistently throughout your entire presentation to help your audience avoid confusion.

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Lecture Notes on Research Methodology

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Lecture Notes on Research Methodology

Introduction to Research Methodology

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Sabine Mendes Lima Moura Issues in Research Methodology PUC – November 2014.

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Today Concepts underlying inferential statistics

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Richard M. Jacobs, OSA, Ph.D.

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Research Methodology Lecture 1.

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Chapter 12 Inferential Statistics Gay, Mills, and Airasian

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Sample Design.

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Copyright © 2008 by Pearson Education, Inc. Upper Saddle River, New Jersey All rights reserved. John W. Creswell Educational Research: Planning,

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Magister of Electrical Engineering Udayana University September 2011

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Chapter 1: Introduction to Statistics

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RESEARCH A systematic quest for undiscovered truth A way of thinking

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Research Methodology.

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Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.

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Research Seminars in IT in Education (MIT6003) Quantitative Educational Research Design 2 Dr Jacky Pow.

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PROCESSING OF DATA The collected data in research is processed and analyzed to come to some conclusions or to verify the hypothesis made. Processing of.

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Academic Research Academic Research Dr Kishor Bhanushali M

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Question paper 1997.

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Chapter 6: Analyzing and Interpreting Quantitative Data

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Module III Multivariate Analysis Techniques- Framework, Factor Analysis, Cluster Analysis and Conjoint Analysis Research Report.

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Chapter 7 Measuring of data Reliability of measuring instruments The reliability* of instrument is the consistency with which it measures the target attribute.

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