Art of Presentations

[Guide] How to Present Qualitative Research Findings in PowerPoint?

By: Author Shrot Katewa

[Guide] How to Present Qualitative Research Findings in PowerPoint?

As a researcher, it is quite pointless to do the research if we are unable to share the findings with our audience appropriately! Using PowerPoint is one of the best ways to present research outcomes. But, how does one present qualitative research findings using PowerPoint?

In order to present the qualitative research findings using PowerPoint, you need to create a robust structure for your presentation, make it engaging and visually appealing, present the patterns with explanations for it and highlight the conclusion of your research findings.

In this article, we will help you understand the structure of your presentation. Plus, we’ll share some handy tips that will make your qualitative research presentation really effective!

How to Create a Structure for your Qualitative Research Presentation?

Creating the right structure for your presentation is key to ensuring that it is correctly understood by your audience.

The structure of your Research Presentation not only makes it easier for you to create the document, it also makes it simple for the audience to understand what all will be covered in the presentation at the time of presenting it to your audience.

Furthermore, having a robust structure is a great way to ensure that you don’t miss out on any of the points while working on creating the presentation.

But, what structure should one follow?

Creating a good structure can be tricky for some. Thus, I’m sharing what has worked well for me during my previous research projects.

NOTE – It is important to note that although the following structure is highly effective for most research findings presentation, it has been generalized in order to serve a wide range of research projects. You may want to take a look at points that are very specific to the nature of your research project and include them at your discretion.

Here’s my recommended structure to create your Research Findings presentation –

1. Objective of the Research

A great way to start your presentation is to highlight the objective of your research project.

It is important to remember that merely sharing the objective may sometimes not be enough. A short backstory along with the purpose of your research project can pack a powerful punch ! It not only validates the reasoning for your project but also subtly establishes trust with your audience.

However, do make sure that you’re not reading the backstory from the slide. Let it flow naturally when you are delivering the presentation. Keep the presentation as minimalistic as possible.

2. Key Parameters Considered for Measurement

Once you’ve established the objective, the next thing that you may want to do is perhaps share the key parameters considered for the success of your project.

Every research project, including qualitative research, needs to have a few key parameters to measure against the objective of the research.

For example – If the goal of your project is to gather the sentiments of a certain group of people for a particular product, you may need to measure their feelings. Are they happy or unhappy using the product? How do they perceive the branding of the product? Is it affordable?

Make sure that you list down all such key parameters that were considered while conducting the qualitative research.

In general, laying these out before sharing the outcome can help your audience think from your perspective and look at the findings from the correct lens.

3. Research Methodology Adopted

The next thing that you may want to include in your presentation is the methodology that you adopted for conducting the research.

By knowing your approach, the audience can be better prepared for the outcome of your project. Ensure that you provide sound reasoning for the chosen methodology.

This section of your presentation can also showcase some pictures of the research being conducted. If you have captured a video, include that. Doing this provides further validation of your project.

4. Research Outcomes (Presenting Descriptive Analysis)

powerpoint presentation of qualitative research

This is the section that will constitute the bulk of the your presentation.

Use the slides in this section to describe the observations, and the resulting outcomes on each of the key parameters that were considered for the research project.

It is usually a good idea to dedicate at least 1 or more slides for each parameter . Make sure that you present data wherever possible. However, ensure that the data presented can be easily comprehended.

Provide key learnings from the data, highlight any outliers, and possible reasoning for it. Try not to go too in-depth with the stats as this can overwhelm the audience. Remember, a presentation is most helpful when it is used to provide key highlights of the research !

Apart from using the data, make sure that you also include a few quotes from the participants.

5. Summary and Learnings from the Research

Once you’ve taken the audience through the core part of your research findings, it is a good practice to summarize the key learnings from each of the section of your project.

Make sure your touch upon some of the key learnings covered in the research outcome of your presentation.

Furthermore, include any additional observations and key points that you may have had which were previously not covered.

The summary slide also often acts as “Key Takeaways” from the research for your audience. Thus, make sure that you maintain brevity and highlight only the points that you want your audience to remember even after the presentation.

6. Inclusions and Exclusions (if any)

While this can be an optional section for some of the researchers.

However, dedicating a section on inclusions and exclusions in your presentation can be a great value add! This section helps your audience understand the key factors that were excluded (or included) on purpose!

Moreover, it creates a sense of thoroughness in the minds of your audience.

7. Conclusion of the Research

The purpose of the conclusion slide of your research findings presentation is to revisit the objective, and present a conclusion.

A conclusion may simply validate or nullify the objective. It may sometimes do neither. Nevertheless, having a conclusion slide makes your presentation come a full circle. It creates this sense of completion in the minds of your audience.

8. Questions

Finally, since your audience did not spend as much time as you did on the research project, people are bound to have a few questions.

Thus, the last part of your presentation structure should be dedicated to allowing your audience to ask questions.

Tips for Effectively Presenting Qualitative Research Findings using PowerPoint

For a presentation to be effective, it is important that the presentation is not only well structured but also that it is well created and nicely delivered!

While we have already covered the structure, let me share with you some tips that you can help you create and deliver the presentation effectively.

Tip 1 – Use Visuals

powerpoint presentation of qualitative research

Using visuals in your presentation is a great way to keep the presentations engaging!

Visual aids not only help make the presentation less boring, but it also helps your audience in retaining the information better!

So, use images and videos of the actual research wherever possible. If these do not suffice or do not give a professional feel, there are a number of resources online from where you can source royalty-free images.

My recommendation for high-quality royalty-free images would be either Unsplash or Pexels . Both are really good. The only downside is that they often do not provide the perfect image that can be used. That said, it can get the job done for at least half the time.

If you are unable to find the perfect free image, I recommend checking out Dreamstime . They have a huge library of images and are much cheaper than most of the other image banks. I personally use Dreamstime for my presentation projects!

Tip 2 – Tell a Story (Don’t Show Just Data!)

I cannot stress enough on how important it is to give your presentation a human touch. Delivering a presentation in the form of a story does just that! Furthermore, storytelling is also a great tool for visualization .

Data can be hard-hitting, whereas a touching story can tickle the emotions of your audience on various levels!

One of the best ways to present a story with your research project is to start with the backstory of the objective. We’ve already talked about this in the earlier part of this article.

Start with why is this research project is so important. Follow a story arc that provides an exciting experience of the beginning, the middle, and a progression towards a climax; much like a plot of a soap opera.

Tip 3 – Include Quotes of the Participants

Including quotes of the participants in your research findings presentation not only provides evidence but also demonstrates authenticity!

Quotes function as a platform to include the voice of the target group and provide a peek into the mindset of the target audience.

When using quotes, keep these things in mind –

1. Use Quotes in their Unedited Form

When using quotes in your presentation, make sure that you use them in their raw unedited form.

The need to edit quotes should be only restricted to aid comprehension and sometimes coherence.

Furthermore, when editing the quotes, make sure that you use brackets to insert clarifying words. The standard format for using the brackets is to use square brackets for clarifying words and normal brackets for adding a missing explanation.

2. How to Decide which Quotes to Consider?

It is important to know which quotes to include in your presentation. I use the following 3 criteria when selecting the quote –

  • Relevance – Consider the quotes that are relevant, and trying to convey the point that you want to establish.
  • Length – an ideal quote should be not more than 1-2 sentences long.
  • Choose quotes that are well-expressed and striking in nature.

3. Preserve Identity of the Participant

It is important to preserve and protect the identity of the participant. This can be done by maintaining confidentiality and anonymity.

Thus, refrain from using the name of the participant. An alternative could be using codes, using pseudonyms (made up names) or simply using other general non-identifiable parameters.

Do note, when using pseudonyms, remember to highlight it in the presentation.

If, however, you do need to use the name of the respondent, make sure that the participant is okay with it and you have adequate permissions to use their name.

Tip 4 – Make your Presentation Visually Appealing and Engaging

It is quite obvious for most of us that we need to create a visually appealing presentation. But, making it pleasing to the eye can be a bit challenging.

Fortunately, we wrote a detailed blog post with tips on how to make your presentation attractive. It provides you with easy and effective tips that you can use even as a beginner! Make sure you check that article.

7 EASY tips that ALWAYS make your PPT presentation attractive (even for beginners)

In addition to the tips mentioned in the article, let me share a few things that you can do which are specific to research outcome presentations.

4.1 Use a Simple Color Scheme

Using the right colors are key to make a presentation look good.

One of the most common mistakes that people make is use too many colors in their presentation!

My recommendation would be to go with a monochromatic color scheme in PowerPoint .

4.2 Make the Data Tables Simple and Visually Appealing

When making a presentation on research outcomes, you are bound to present some data.

But, when data is not presented in a proper manner, it can easily and quickly make your presentation look displeasing! The video below can be a good starting point.

Using neat looking tables can simply transform the way your presentation looks. So don’t just dump the data from excel on your PowerPoint presentation. Spend a few minutes on fixing it!

4.3 Use Graphs and Charts (wherever necessary)

When presenting data, my recommendation would be that graphs and charts should be your first preference.

Using graphs or charts make it easier to read the data, takes less time for the audience to comprehend, and it also helps to identify a trend.

However, make sure that the correct chart type is used when representing the data. The last thing that you want is to poorly represent a key piece of information.

4.4 Use Icons instead of Bullet Points

Consider the following example –

powerpoint presentation of qualitative research

This slide could have been created just as easily using bullet points. However, using icons and representing the information in a different format makes the slide pleasing on the eye.

Thus, always try to use icons wherever possible instead of bullet points.

Tip 5 – Include the Outliers

Many times, as a research project manager, we tend to focus on the trends extracted from a data set.

While it is important to identify patterns in the data and provide an adequate explanation for the pattern, it is equally important sometimes to highlight the outliers prominently.

It is easy to forget that there may be hidden learnings even in the outliers. At times, the data trend may be re-iterating the common wisdom. However, upon analyzing the outlier data points, you may get insight into how a few participants are doing things successfully despite not following the common knowledge.

That said, not every outlier will reveal hidden information. So, do verify what to include and what to exclude.

Tip 6 – Take Inspiration from other Presentations

I admit, making any presentation can be a tough ask let alone making a presentation for showcasing qualitative research findings. This is especially hard when we don’t have the necessary skills for creating a presentation.

One quick way to overcome this challenge could be take inspiration from other similar presentations that we may have liked.

There is no shame in being inspired from others. If you don’t have any handy references, you can surely Google it to find a few examples.

One trick that almost always works for me is using Pinterest .

But, don’t just directly search for a research presentation. You will have little to no success with it. The key is to look for specific examples for inspiration. For eg. search for Title Slide examples, or Image Layout Examples in Presentation.

Tip 7 – Ask Others to Critic your Presentation

The last tip that I would want to provide is to make sure that you share the presentation with supportive colleagues or mentors to attain feedback.

This step can be critical to iron out the chinks in the armor. As research project manager, it is common for you to get a bit too involved with the project. This can lead to possibilities wherein you miss out on things.

A good way to overcome this challenge is to get a fresh perspective on your project and the presentation once it has been prepared.

Taking critical feedback before your final presentation can also prepare you to handle tough questions in an adept manner.

Final Thoughts

It is quite important to ensure that we get it right when working on a presentation that showcases the findings of our research project. After all, we don’t want to be in a situation wherein we put in all the hard-work in the project, but we fail to deliver the outcome appropriately.

I hope you will find the aforementioned tips and structure useful, and if you do, make sure that you bookmark this page and spread the word. Wishing you all the very best for your project!

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INTRODUCTION TO QUALITATIVE RESEARCH

Published by Λήδα Κουβέλης Modified over 4 years ago

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Presentation on theme: "INTRODUCTION TO QUALITATIVE RESEARCH"— Presentation transcript:

INTRODUCTION TO QUALITATIVE RESEARCH

Participant Observation

powerpoint presentation of qualitative research

Reviewing and Critiquing Research

powerpoint presentation of qualitative research

Research Methodologies

powerpoint presentation of qualitative research

Publishing qualitative studies H Maisonneuve April 2015 Edinburgh, Scotland.

powerpoint presentation of qualitative research

 It’s an approach to research that examines a concept or phenomenon from the perspective of the individual who is experiencing it  The research purpose.

powerpoint presentation of qualitative research

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

powerpoint presentation of qualitative research

Case Study Research By Kenneth Medley.

powerpoint presentation of qualitative research

Chapter 14 Overview of Qualitative Research Gay, Mills, and Airasian

powerpoint presentation of qualitative research

Chapter 10 Conducting & Reading Research Baumgartner et al Chapter 10 Qualitative Research.

powerpoint presentation of qualitative research

Qualitative Research.

powerpoint presentation of qualitative research

Research Methods in Psychology (Pp 1-31). Research Studies Pay particular attention to research studies cited throughout your textbook(s) as you prepare.

powerpoint presentation of qualitative research

Chapter 10 Qualitative Methods in Health and Human Performance.

powerpoint presentation of qualitative research

Chapter 11: Qualitative and Mixed-Method Research Design

powerpoint presentation of qualitative research

Designing a Qualitative Study

powerpoint presentation of qualitative research

TRUSTWORTHINESS OF THE RESEARCH Assoc. Prof. Dr. Şehnaz Şahinkarakaş.

powerpoint presentation of qualitative research

Creswell Qualitative Inquiry 2e 11.1 Chapter 11 Turning the Story and Conclusion.

powerpoint presentation of qualitative research

Qualitative Research EDUC 7741/Paris/Terry.

powerpoint presentation of qualitative research

Research for Nurses: Methods and Interpretation Chapter 1 What is research? What is nursing research? What are the goals of Nursing research?

powerpoint presentation of qualitative research

Chapter Nine: Qualitative Procedures

powerpoint presentation of qualitative research

ABRA Week 3 research design, methods… SS. Research Design and Method.

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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.

Monograph Matters

Qualitative analysis: process and examples | powerpoint – 85.2.

Authors Laura Wray-Lake and Laura Abrams describe qualitative data analysis, with illustrative examples from their SRCD monograph,  Pathways to Civic Engagement Among Urban Youth of Color . This PowerPoint document includes presenter notes, making it an ideal resource for researchers learning about qualitative analysis and for instructors teaching about it in upper-level undergraduate or graduate courses.

Created by Laura Wray-Lake and Laura S. Abrams. All rights reserved.

Citation: Wray-Lake, L. & Abrams, L. S. (2020) Qualitative Analysis: Process and Examples [PowerPoint]. Retrieved from https://monographmatters.srcd.org/2020/05/12/teachingresources-qualitativeanalysis-powerpoint-85-2

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Qualitative Research Resources: Presenting Qualitative Research

Created by health science librarians.

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  • What is Qualitative Research?
  • Qualitative Research Basics
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  • Training Opportunities: UNC & Beyond
  • Help at UNC
  • Qualitative Software for Coding/Analysis
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  • Finding Qualitative Studies
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Presenting Qualitative Research, with a focus on posters

  • Qualitative & Libraries: a few gems
  • Data Repositories

Example posters

  • The Meaning of Work for People with MS: a Qualitative Study A good example with quotes
  • Fostering Empathy through Design Thinking Among Fourth Graders in Trinidad and Tobago Includes quotes, photos, diagrams, and other artifacts from qualitative study
  • Examining the Use and Perception of Harm of JUULs by College Students: A Qualitative Study Another interesting example to consider
  • NLM Informationist Supplement Grant: Daring to Dive into Documentation to Determine Impact An example from the Carolina Digital Repository discussed in a class more... less... Allegri, F., Hayes, B., & Renner, B. (2017). NLM Informationist Supplement Grant: Daring to Dive into Documentation to Determine Impact. https://doi.org/10.17615/bk34-p037
  • Qualitative Posters in F1000 Research Archive (filtered on "qualitative" in title) Sample qualitative posters
  • Qualitative Posters in F1000 Research Archive (filtered on "qualitative" in keywords) Sample qualitative posters

Michelle A. Krieger Blog (example, posts follow an APA convention poster experience with qualitative posters):

  • Qualitative Data and Research Posters I
  • Qualitative Data and Research Posters II

"Oldies but goodies":

  • How to Visualize Qualitative Data: Ann K. Emery, September 25, 2014 Data Visualization / Chart Choosing, Color-Coding by Category, Diagrams, Icons, Photographs, Qualitative, Text, Timelines, Word Clouds more... less... Getting a little older, and a commercial site, but with some good ideas to get you think.
  • Russell, C. K., Gregory, D. M., & Gates, M. F. (1996). Aesthetics and Substance in Qualitative Research Posters. Qualitative Health Research, 6(4), 542–552. Older article with much good information. Poster materials section less applicable.Link is for UNC-Chapel Hill affiliated users.

Additional resources

  • CDC Coffee Break: Considerations for Presenting Qualitative Data (Mark D. Rivera, March 13, 2018) PDF download of slide presentation. Display formats section begins on slide 10.
  • Print Book (Davis Library): Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook, 3rd edition From Paul Mihas, Assistant Director of Education and Qualitative Research at the Odum Institute for Research in Social Science at UNC: Qualitative Data Analysis: A Methods Sourcebook (4th ed.) by Miles, Huberman, and Saldana has a section on Displaying the Data (and a chapter on Designing Matrix, Network, and Graphic Displays) that can help students consider numerous options for visually synthesizing data and findings. Many of the suggestions can be applied to designing posters (April 15, 2021).
  • << Previous: Publishing Qualitative Research
  • Next: Qualitative & Libraries: a few gems >>
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Sage Research Methods Community

Qualitative Presentation Strategies

By Dr. Linda Bloomberg, and hosted by Janet Salmons, Ph.D., Research Community Manager for Sage Methodspace.

Dr. Bloomberg is the author of Completing Your Qualitative Dissertation : A Road Map From Beginning to End. Use the code COMMUNITY3 for a 20% discount when you order her book, valid worldwide until March 31, 2024.

How do you present and share your study’s findings based on your selected research design?

Each qualitative research design encompasses specific ways of addressing a researchable problem; setting up the study; and collecting, analyzing, and presenting data.  A researcher must ensure that methods of data presentation will be in alignment with their selected research design.

In this presentation, Linda Bloomberg explains how to think through key questions associated with presentation of findings, and walks through an example that demonstrates ways to align research designs with presentation strategies.

powerpoint presentation of qualitative research

Use the code MSPACEQ423 for a 20% discount.

See the whole series!

This is the fourth of a four-part series about qualitative research designs and methods drawn from Completing Your Qualitative Dissertation .

Q1: Design Strategy: How to Choose a Qualitative Research Design

Q2: Data Collection Strategy: How to Choose What Data to Collect from Whom

Q3: Analytic Strategy: How to Choose the Approach

Linda Dale Bloomberg EdD., currently develops curriculum for qualitative research in graduate online programs for National University, serving as faculty coach, dissertation chair, and doctoral subject matter expert. She formerly served as an adjunct faculty and dissertation advisor in the department of adult learning and leadership at Teachers College, Columbia University, and She also serves as consultant to various research, higher education, and nonprofit advisory boards including The Future Talent Council, and is founder of Bloomberg Associates and ILIAD (Institute for Learning Innovations and Adult Development) and cofounder of Columbia University’s Global Learning and Leadership Institute. As senior researcher for the South African Human Sciences Research Council and National Institute for Personnel Research, Dr. Bloomberg’s work focused on change management; diversity, equity, and inclusion initiatives; and enhanced workplace learning.

She is the author of multiple publications in the fields of qualitative research, organizational evaluation, leadership development, ensuring equitable student success, adult learning, and distance education, and is a contributor to The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation (2018). Her two most recent books include the 5th edition of Completing your qualitative dissertation: A road map from beginning to end (2023) from Sage; and Designing and delivering effective online instruction: How to engage adult learners (2021) from Teachers College Press, Columbia University. This publication was nominated for the 2021 and 2022 Division of Distance Learning (DDL) for the Association of Educational Communications and Technology (AECT), one of the premier international organizations for instructional design and ed-tech. Dr. Bloomberg presents regularly at national and international professional conferences on topics related to diversity initiatives in higher education, adult learning, qualitative research, and dissertation instruction. She holds master’s degrees in counseling psychology, organizational psychology, and education, and is credentialed with the International Coaching Federation (ICF). In 2006, she received her doctorate in adult education and organizational learning from the AEGIS program Columbia University that was established by Jack Mezirow, founder of Transformative Learning theory.

More Methodspace Posts about Academic Writing

Writing Across Qualitative Research

by Maria Lahman, Ph.D. and Tyler Kincaid Ph.D., panelists for the How to Do Research and Get Published webinar, “How to write a paper: Qualitative methodology” share their insights.

Conduct a reference search and format your reference section

Conduct a reference search and format your reference section was offered as part of the How to Do Research and Get Published webinar series. Watch the recording and find lots of useful resources in this post.

Resources about getting scholarly articles published

Find a collection of resources about writing and publishing articles and more!

Dr. Linda Bloomberg and Dr. Merle Werbeloff discuss methodology with publication options

Learn about research design, doctoral writing, and academic publishing with these posts and recordings from Dr. Linda Bloomberg and Dr. Merle Werbeloff.

What is a "holistic publication strategy"?

Think about your own big picture, and how to paint it. There are many options for sharing ideas and disseminating findings. What will work for you, based on the nature of your research, your findings, and your career goals?

Revive an Old Writing Project, or Let It Die?

Look candidly at your unfinished project. Is it a stepping stone, and completion will be allow you to move ahead? Or is it an obstacle that prevents you from moving forward? Find ideas to help you determine whether to revive that piece of writing or let it go.

Choosing digital tools for qualitative data analysis

Christina Silver explains why and how to use qualitative data analysis software to manage and analyze your notes, literature, materials, and data. Sign up for her upcoming (free) symposium!

How to present numeric data

Find tips to help you share your research and numerical findings.

PhDs, Publications, and Academic Careers

This list of books and articles include a range of discussions about academic and research careers.

How do you publish an open-access article?

Want anyone, whether or not they are associated with an institution that allows them access to an academic library? Learn about open access and how to publish your OA article.

Digital Workflows: Special Issue Roundtable 2

Jessica Lester and Trena Paulus co-edited a December 2023 special issue for the Sage journal, Qualitative Inquiry, “Qualitative inquiry in the 20/20s: Exploring methodological consequences of digital research workflows.” Read the articles and watch a roundtable with contributors. This is the second of two discussions of the special issue.

Digital Workflows: Special Issue Roundtable 1

Jessica Lester and Trena Paulus co-edited a December 2023 special issue for the Sage journal, Qualitative Inquiry, “Qualitative inquiry in the 20/20s: Exploring methodological consequences of digital research workflows.” Read the articles and watch a roundtable with contributors. This is the first of two discussions of the special issue.

Image Use and Reuse

Academic writing is not always writing! Pictures and media enliven our writing, and can be important for showing concepts and contexts.

How to Make a Cogent Argument

How and why should you argue in academic writing? Learn more from Dr. Alastair Bonnett, author of How to Argue.

Research Proposals: Writing Strategies and Ethical Considerations

This post includes tips about writing qualitative proposals excerpted from Research Design by Creswell and Creswell.

Calling, Change, and Your Research Career

Thinking about research careers and calling: finding the right fit.

Writing for Journals: Editorials with Practical Suggestions

What do journal editors want? Read an open-access collection of editorials that offer practical suggestions about how to organize and write an article that will pass the review process and get published.

Academic Writing: From Global Authors to Global Readers

Safary Wa-Mbaleka, Arceli Rosario, and Anna Cohen Miller discussed opportunities and challenges for global researchers and academic writers in this roundtable discussion.

How to Avoid Predatory Publishers

Don’t get caught by predatory publishers!

Organize Your Writing Projects

Celebrate Academic Writing Month 2023 by getting organized! Find open-access resources to help you avoid being distracted by details and lost files.

Use AcWriMo to reconnect with your desire to write

Jo VanEvery believes that a writing practice based on the desire to write and enjoyment of the intellectual challenge will produce the outputs you are under pressure to produce. Learn how in this post!

Learning to be Original: In the Age of AI, Students Need to be Taught the Skills of Innovation&nbsp;

AI can do a lot of things but it cannot do originality. Learn more from Dr. Alastair Bonnett, author of How to Be Original.

Qualitative Presentation Strategies

In this presentation, Dr. Linda Bloomberg explains how to think through key questions associated with presentation of qualitative findings, and walks through an example that demonstrates ways to align research designs with presentation strategies.

Managing and Writing the Doctoral Thesis or Dissertation

Dr. Linda Bloomberg offers detailed suggestions for getting organized and starting a dissertation or thesis.

If AI wrote your article, what would you lose? Some thoughts on wellbeing and writing

Connect or reconnect to the joy of writing with these tips from Dr. Katherine Firth.

The Link between Critical Reading, Thinking and Writing

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Philosophy of science and doctoral research design: The case of the Idea Puzzle software.

Learn how to design and defend your PhD research with the Idea Puzzle software from Ricardo Morais.

Writing The Ethnography Quartet

Between 2015 and 2022 Paul Atkinson produced four books about ethnography. How and why did that happen, and what did he want to achieve? Learn about this quartet of books.

Equity-Focused Research Dissemination Planning

Applying an equity focused lens specifically to reporting and dissemination necessitates a careful and deliberate approach. Learn more in this post!

Disseminating Research with an Equity-Focused Lens

Learn about disseminating research with an equity lens in this guest post from the CTE Research Network Equity Working Group.

Qualitative Research: From Design to Publication

Managing and writing the doctoral thesis or dissertation.

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QUALITATIVE RESEARCH METHODS

Any kind of research that produced findings not arrived at by ... establish rapport, good listener, politeness, articulate enough to prompt respondents to talk ... – powerpoint ppt presentation.

  • Any kind of research that produced findings not arrived at by means of statistical procedures or other means quantification.
  • It is concerned more with meanings and processes rather than simply measurements.
  • Qualitative research is based on a methodology which seeks to understand human behaviour from the subjects own frame of reference, hence it is called Phenomenological.
  • Aims to elicit the individual contextualized understanding of a problem
  • Achieved through designs that minimize researcher manipulation of social setting
  • Close interaction with subjects
  • Meaning and interpretation cannot be dealt with statistically
  • Human behaviours is significantly influenced by the setting in which it occurs
  • The technique in quantitative research can affect the findings
  • One cannot understand the human behaviour without understanding the framework within which subjects interpret their feelings, thoughts and actions
  • More valid results based on research experiences.
  • Nature of research problems some problems lend more to qualitative research
  • Helps to understand what lies behind any phenomenon about which little is known
  • Details of phenomena that are difficult to convey with quantitative methods
  • Questionnaires developed in the West threat to validity in our setting Qualitative methods in the initial phase avoid type III error
  • Culturally appropriate measuring instruments Etic Vs. Emic approach
  • It helps in identifying variables important to the phenomenon under study
  • To understand the perceptions and experiences of participants and community
  • Field study research can explore the process and meaning and provide comprehensive description
  • Developing and delineating program elements before a quantitative evaluation
  • Boosting the power of quantitative design
  • Broadening the observation field
  • Analyzing process and individual cases to explain the how and why of an outcome
  • Generating theory
  • Refers to the belief that social science can be scientific in the same way as physical science and prefer quantitative methods
  • Assume that reality is objectively given and can be described by measurable properties independent of the observer
  • Prefers a method standardized, repeatable and that test a pre-existing hypothesis
  • Study situations in the everyday world - viewpoint of the experiencing person
  • Focus on the social construction of the life world, emphasizing that peoples actions can only be understood when they are situated in the meanings and routines that control their everyday life.
  • Gain understanding of the essence of phenomena Eg. Sufferings of schizophrenia
  • Closely associated with anthropological research
  • Focus on culture of a group of people
  • Interpret and present findings from a cultural perspective
  • Heart of Ethnography- Thick description obtained through an immersion in the every day life of the group or a given social setting
  • Through the process of role taking a person imagines how they appear to others ,thus becoming a symbolic object to themselves
  • Experiences takes on meaning as they become symbolically significant through shared interactions
  • Meanings are continually created,recreated and modified in interactions
  • It is argued (Dorothy Smith) as a consciousness raising that it attempts to identify how private experiences of oppression may be understood as part of a general system of oppression that shapes womens experience
  • Many womens private issues are not recorded as shared public issues
  • Advocates methods that enable women to express their experiences from their own perspective
  • Examine the way people develop interpretation of their life in relation to their life experiences
  • Similar to phenomenology ,but takes a broader view of both past and future and broader cultural factors Eg Story telling
  • An inductive technique developed by Glaser and Strauss(1967)
  • Grounded Theories are grounded ( it has its root) in the empirical data and built up inductively through a process of careful analysis and comparison
  • Developed in opposition to positivist and deductive approach
  • To inform what people are doing, thinking, and saying about a problem
  • To identify the important problem to be solved at community/local/policy levels
  • Generate a list of options for interventions
  • To investigate how best to implement promising interventions
  • To monitor response to interventions and assess how best to present its results to public and scientific community
  • When numbers are needed to make a decision (what proportion of people )
  • Results are to be projected to the total population (unless generalisability ensured by researcher through appropriate measures)
  • Qualitative Research required theoretical and social sensitivity
  • Ability to maintain analytical distance while drawing upon experience and knowledge to interpret what is seen
  • Power of observation
  • Good interactional skills.
  • Ability to organize and synthesize many different types of data
  • Ability to gain trust of individuals / groups
  • Respect for individuals and awareness of the ethical responsibilities
  • Knowledge and experience of social,cultural,reli gious and economic characteristic of group/community/setting.
  • Data come from various sources
  • Different analytic or interpretive procedures.
  • E.g. Coding, Writing of memos, diagramming
  • Written and Verbal reports.
  • NATURALISTIC Natural setting as source of data
  • INDUCTIVE It seeks to build theory from data avoid imposing researcher own categories of analysis
  • HOLISTIC It looks at the phenomenon in totality takes an overall perspective
  • THICK DESCRIPTION Descriptive in that the researcher is interested in process, meaning understanding gained through words pictures use quotations
  • PERSONAL CONTACT Shares the experience of subjects , not trying to be an objective outsider
  • DYNAMIC There is constant shifting with changing phenomenon context
  • UNIQUE CASE SELECTION Not concerned about generalization stress on uniqueness of each case
  • CONTEXT SENSITIVITY Emphasis many aspects of social, historical physical contexts
  • EMPATHETIC Trying to take view of other person via introspection reflection, yet non-judgemental
  • FLEXIBLE DESIGN- Emergent design as opposed to pre-determined in quan.methods
  • INTERPRETIVE Aimed at discovering the meaning the events have for the individuals who experience them interpretation of these meaning by researcher
  • PROCESS ORIENTED Primarily concerned with process rather than outcome
  • RESEARCHER AS INSTRUMENT Data are mediated through human instrument rather than inventories or questionnaires
  • MULTIPLE SOURCES OF EVIDENCE-Multiple forms of evidence. Judgment at usefulness and credibility is left to the researcher
  • Particularistic, guided by objectives
  • Generalize and extrapolate findings
  • Holistic, rich in context, emphasizes interactions
  • Recognizes the individuality of responses and findings.
  • Unfamiliar, artificial
  • PRE-determined structured design. Manipulation control
  • Familiar, natural
  • Flexible evolving design
  • Cross sectional studies, cohort, case control, RCT
  • Semi structured / unstructured interviews, Focus group discussions, observations, key informantinterviews, case study
  • Deals with words, texts and observations
  • Open ended. Depth of information.
  • Produce a wealth of detailed data about a much smaller number of people. Depends on purpose, resources and interests of those involved.
  • Deals with numbers
  • Use of standardized approach - the experiences of people are limited to certain predetermined response categories
  • Measure reactions of many subjects to set of questions, thus facilitating comparison and statistical aggregation of data
  • Probability Sampling
  • Non-Probability sampling-Typically focus in depth on small samples selected purposively
  • Large Sample Size
  • No rule for sample size. Depends on what you want to know purpose of enquiring what will be useful, what will have credibility and what can be done with available resources.
  • Researcher as primary instrument Personal involvement empathic understanding
  • Inanimate Instruments- Scales,Tests, Questionnaires
  • Detachment objective portrayal
  • Analysis tend to be deductive. Test hypothesis using quantitative methods Statistical analysis
  • Usually inductive. unit of analysis can be individuals, families, groups. No statistical techniques used.
  • Generalizations made. Statistical predictions because of representative sample.
  • Reliability
  • More in depth data and help us to find out how and why of an outcome. Sequence of event depicted.
  • NON- PROBABILITY SAMPLING
  • Purposeful selection
  • Goal is to understand phenomena, not to represent population
  • Selection of information-rich cases for intensive study
  • Quota Sampling
  • Snowball Sampling
  • Typical Case Sampling
  • Critical Case Sampling
  • Homogeneous
  • Maximum variation
  • Extreme or deviant cases
  • Criterion Sampling
  • It is a form of convenient sampling
  • Selection of quota groups of accessible sampling units by age, sex, social class etc
  • Assignment of quota groups specified by predetermined traits in specific proportions
  • A method of stratified sampling in which selection within strata is non-random
  • Subjects are asked to recommend others they know for the researcher to contact
  • Useful in studies of social networks or in difficult to find populations
  • Use in research on sensitive issues like sexual practices ,IV drug use etc.
  • To describe a typical case serves as a profile for understanding the principal features of a group of programes or class of individuals.
  • Sample typical case as illustrative
  • In deviant case sampling, cases at either end of a continuum or unusual cases are selected
  • More useful in finding critical variables contributing to the phenomenon
  • Its effectiveness depends on understanding what is happening in that case
  • Identification depends on key factors that make a case as critical
  • The results of intervention would provide a critical case for the feasibility of the programe
  • If it works here ,it will work everywhere
  • Subjects with similarities in background are selected
  • Better able to focus on a central issue that is relevant to all of them
  • Eg. Focus Group Discussion (stimulating people with a common identity to discuss their shared experiences)
  • Selecting sample with maximum variation in defined attributes eg. Education, gender
  • To highlight the experiences or outcomes which these maximally varied samples have in common
  • Document unique experiences shared patterns
  • Sample cases to meet a criterion of importance to the study eg. membership in a particular group or participation in a programme
  • May be done as follow up of a survey to identify particular subjects for in-depth analyses
  • The validity, meaningfulness and insights generated from qualitative enquiry have more to do with the information,richness of cases selected and the observational/ analytical capabilities of the researcher than with sample size (patton)
  • Depends upon completion of data- sample selection to the point of redundancy
  • Might begin with small sample based on expected reasonable coverage and expand if needed
  • Large enough to make meaningful comparisons
  • Small purposive samples based on study purpose, but describe, justify and explain
  • Care not to over generalize from purposive samples
  • No of comparison groups- more groups more samples
  • Complexity and depth of information- more in-depth information go for small sample
  • Explain similarities and differences in particular context
  • Availability of resources
  • In-depth Interviews
  • Key informant Interviews
  • Observation
  • Focus Group Discussions
  • Case studies
  • Illness narratives, Surrogate patient studies
  • PRA / PLA Techniques
  • It is a qualitative research technique that allows person to person discussion which can lead to increased insight into peoples thoughts, feelings and behaviour on important issues.
  • It can be used as one of the effective ways for understanding reasons for problem behaviours and gather ideas to guide measures to correct a problem
  • Characterized by extensive probing and open-ended questions
  • Subject matter is complex
  • Detailed information sought
  • Highly sensitive subject matter
  • Interest on individual experiences and its unique interpretation
  • Respondents dissimilar to be meaningfully grouped
  • Identification of the respondents
  • Ensure Trained interviewer
  • Selection of a comfortable location
  • Other logistics- transport, audio or video etc
  • Consider access to local population
  • Limit to a small sample size
  • Select people who are well informed about the issue
  • Purposive sampling
  • Respondents fairly representative of the various groups in the study population
  • Informant preferably unknown to interviewers
  • Interview guide
  • Structured open-ended schedule
  • Different sets may be needed suitable to different categories in the study population
  • The guide makes the interviewing more systematic and comprehensive
  • List the important topics to be explored in the study Eg. Malnutrition among children- Feeding adequacy, Care of the child, Health seeking
  • Write sub themes for each topic Eg. Under feeding adequacy, elicit information Breast feeding ,weaning, complimentary feeding, food preferences etc.
  • Make a draft of possible questions based on conceptual frame work
  • Check that they can help you obtain all the information you need
  • Questions not to elicit simple Yes or No answers
  • Construction of probes
  • Probes are devices used to prompt a respondent to speak further when an initial question fails to elicit the desired information
  • Sequence of topics- Never rigid. Phrasing and order may be redefined to fit the characteristics of respondent
  • Ensure that your questions are
  • Clear and unambiguous
  • Simple and easy to understand
  • Reasonable and within the experience of the targeted population
  • Experienced/Skilled
  • Knowledge about the topic
  • Personality traits easily gain peoples confidence and cooperation, good speech and language proficiency
  • Other qualities self confidence, ability to establish rapport, good listener, politeness, articulate enough to prompt respondents to talk
  • Training is a pre-requisite if team work
  • Unstructured interviews
  • Semi-structured interviews
  • Structured open-ended interviews
  • Self introduction
  • Explain the general purpose of the interview
  • Impress upon the respondent that his opinions are important
  • Seek privacy
  • Establish rapport and assure confidentiality
  • Consent for the interview recording
  • Carry the interview in a natural, conversational style
  • Know the objectives of each question to make sure that the answers satisfy it
  • Interview runs dry use expressions like Uh-huh or That is interesting or I see
  • Be alert to discover drifting of conversation
  • Wrapping-up of interview
  • Ask clear and open-ended questions
  • Ask behaviour /experience before opinion questions
  • Sequence-follow a funnelling method-general to specific
  • Probe and follow-up questions Eg . Could you tell me more about it?
  • Reluctant participant
  • Speculation can help to open up .eg. I am not sure, could it be that women do not have access to health care, compared to men ?
  • Try to explore their thoughts Eg. Could you elaborate on that? Or explain why you think that way?
  • Rambler Politely control Eg. Excuse me, could we change the subject a bit and get back on your thoughts on ..
  • Participant uncomfortable- Let them talk about the part he/she comfortable with.
  • Confused OK, Sorry, let me rephrase it
  • Contradictory statement-seek clarification
  • Begin with a friendly greeting
  • Maintain privacy and confidentiality
  • Listen with an open mind
  • Use probes where appropriate
  • Ensure a natural flow of interview
  • play dumb give informant time to talk
  • Be open to unexpected information
  • Judgemental attitude
  • Move quickly from one topic to the next
  • Letting silence grow while interviewing
  • Arguing or enter into dispute
  • Field editing
  • De-briefing
  • Transcribing
  • Translation if needed
  • A brief description of the participants
  • Memos Helps one to reflect on the interview
  • Theoretical memos/notesSummarises theoretical ideas surfaced
  • Methdological memos What happened during the interview, quality of data,participantcomfortleve l
  • Personal memos Interviewer relaxed ? Were he inhibited in asking certain questions?
  • Explanatory tool
  • Emic perspective
  • Facilitate rapport
  • More appropriate in rural setting
  • Responses more valid
  • Disadvantages
  • Replicality difficult
  • Results not strictly comparable
  • Time consuming
  • Require familiarity with language and culture
  • Reading Developing an intimate relationship with the data
  • Coding Identifying emergent themes
  • Choosing and using a software if needed
  • Displaying data
  • Developing hypothesis, questioning, verifying
  • Data reduction Getting the big picture and interpretation
  • Deductive coding
  • Done prior to data collection
  • Use existing literature or theoretical frames to develop categories for coding prior to field work
  • Provides a conceptual framework to guide the research
  • Inductive Coding
  • Designs coding scheme from data collected through interviews, FGDs etc
  • They are like street signs inserted into margins of notes or typed in after a segment of text
  • Main purpose is to allow research findings to emerge from frequent dominant or significant themes inherent in raw data
  • Condense extensive raw text
  • Establish clear links between research objectives and findings derived from raw data
  • Develop a model or theory about underlying structure of experience or processes evident in the raw data
  • Open coding involves fracturing, taking data apart and examining discrete parts for differences and similarities
  • Axial coding connections are made between categories and sub categories
  • Selective coding identifying one or more core categories to which all other sub categories relate
  • Create 3-8 summary categories from many pages of text
  • If more than 8 major themes re-examine them
  • Decisions on combining and removing unimportant categories need to be made
  • Free-listing
  • Pile-sorting
  • Domain identification
  • Summarizing
  • Comparative table across stakeholders (if more than one)
  • In your opinion, who are the people that generally do not bring their children for polio drops on NIDs?
  • Sometimes, it happens that parents are unaware of it or neglect it or there are some parents who do not give importance to it or they go outstation. Till now, they have not understood the importance of the drops and that it should be given. Some parents feel we have given three doses (routine doses) to out children and if these are not given it will do. These are the people who dont bring. Usually they are from slum areas. Others are educated, they know about it, constantly hear on TV/radio, so they bring. The area which I had got was a Mehammedan area so the women do not go out of the house. They did not even know that it had to be given. There was an announcement through the mosque but people might not have heard or something else, so many children did not turn up.
  • Domain Evolution
  • 0. Dont know
  • None (everybody received OPV)
  • Laborers / daily wages / beggars (affordability)
  • No one at home / adult sickness
  • Migrants / tribal (accessibility / out of station / traveling
  • People with remote residence / adverse weather / transport difficulties (accessibility)
  • Bad past experience (due to /fear of side effects) / fear of polio even after polio drops (acceptability)
  • Non believers (no faith / believers of other systems / superstitions / rumours / socio-cultural / religious / death / caste)
  • Misinformed groups (rich / educated) / do not like to go to IP / go to private practitioner / wrong impression)
  • Lack of awareness / Illiterate
  • Children with illness / new born (acceptability)
  • Negative influences of the other family members / decision of family members
  • Not applicable
  • Develop an outline for report
  • Review all field-notes and organize along identified domains in conformity with report outline
  • Compare across stakeholder categories if needed
  • Compare results of other qualitative methods with these findings
  • Focus group discussions are group discussions with a small group of individuals from a well defined target population on pre-selected topics that rely on interaction between group members, under the guidance of a trained facilitator. Each participant is stimulated by the comments of others and in turn stimulate them.
  • It is a qualitative method which helps to find out the How Why of human behaviour
  • It can provide insight into how a group thinks about an issue, the range of opinions and ideas, and the inconsistencies and variations that exist in a particular community in terms of beliefs and their experiences practices
  • Obtaining a range of perceptions, opinions or beliefs about an issue
  • Gathering exploratory data to be used in future research Eg. Local names for diseases, local pattern of healthcare seeking
  • Hypothesis generating
  • Assist in explaining and illustrating results of a quantitative survey
  • Intervention programmes- To identify various social or cultural factors that need to be taken into account in the design and implementation of the programme
  • Ongoing assessment of programmes or as an evaluation tool
  • Obtaining feed back for the cross cultural adaptation of materials.
  • As a means of validating findings obtained by other means (Triangulation)
  • As a Rapid Assessment Procedure for getting quick results
  • The topic should is narrowly focused
  • Selection of participants is also focused by targeting individuals who meet specific criteria
  • Topic should be of interest to both the investigator and respondents.
  • The emphasis should be on interaction between or among the group members.
  • A set of detailed guidelines designed to generate discussion of concepts and ideas
  • A trained moderator and a note taker
  • Recording the discussion to permit later analysis of the result
  • Setting the objectives
  • Determine the target population
  • Plan the number of of sessions
  • Follow the guidelines regarding selection of participants, role of moderator/facilitator etc
  • Developing F.G.D.guide
  • Conducting F.G.D.
  • Analysis and interpretation of results
  • Define the problem and decide on the issues or areas you want to explore
  • Decide on how the information be used Is this the only method to gather information or will it be used with other methods
  • For eg. Are they to supplement quantitative data, used to define pretest questionnaires
  • Determine who can provide the information you require and what characteristics define the individuals to be participated
  • Often incorporate different subsets with potentially contrasting views or experiences concerning the issues under investigation
  • Eg. Rural Vs Urban and Adolescents Vs Elderly
  • Decide on the no. of sessions to be held
  • Number of sessions is based on
  • Resources (time and money)
  • Types of different groups targeted
  • Comparisons you wish to stress in the analysis.
  • The composition should be homogeneous.
  • Participants with different backgrounds and experience restrict the openness of discussion
  • Representative of the population in which the investigator is interested.
  • Ideally efforts may be made to select people who do not know each other personally.
  • Exclude people previously participated in a FGD on the same subject.
  • The number of participants should range between six to ten.
  • Small group lt6 can be dominated by one person and variation of thought and queries remain restricted.
  • Large group gt12 does not provide chance to all participants and often give way for small group formation.
  • Any place people can easily go.
  • Acceptable and convenient to the participants
  • Any place where 6 to 10 people can be seated.
  • Should not be held in open place (Guard against unwarranted intrusions)
  • Best is to have participants in a circular fashion.
  • Each participant should have the provision to see all other participants.
  • Each one should feel physically and psychologically comfortable.
  • Run FGs until you dont hear anything new Redundancy of information. Not over sample
  • Either random or convenient sampling .
  • Usually recruited through informal networks.
  • Make sure representative ness of study population
  • A flexible unstructured interview guide is used to conduct the discussion.
  • keep the questions open- ended Eg. How do you feel about
  • Questions should seek to discover the prevailing attitudes of the community, not just those of the group.
  • Start with general question and then get more specific as the session progress. ( funnelling effect)
  • The number of items in the guide should not exceed 6 or 7.
  • The guide must be phrased in simple language using local terminology.
  • Adequate knowledge on background information about the topic and experience in conducting FGD
  • Good listening skills
  • Leadership skills
  • Relationship with the participants
  • Patience and flexibility
  • Orient the group in a proper manner.
  • Put forth issues / sub issues in appropriate questions.
  • Create a non-judgmental environment in which group members feel free to express.
  • Encourage interaction between participants.
  • Encourage quiet participants to speak up and quieten garrulous talkers.
  • Guide the direction of discussion so that it does not wander too far from the designated focus.
  • Pace the discussion appropriate for the participant
  • Subtly control the time allotted to each question and to the entire discussion.
  • Primarily an observer, tape record the session.
  • Observe the nature of interaction , record non-verbal communication level of consensus
  • Should know what type of data she/he is expected to collect.
  • If facilitator has omitted a question from the guide, the recorder can point them out.
  • Identify the speakers. Note down the first few words every time a new person speaks and make brief notes of the content
  • Diagrammatic representation of entire session of FGD
  • Offers a useful method of conceptualising group dynamics drawing comparisons between focus groups reflecting on moderating technique
  • Greet the participant as they arrive
  • Create a warm and friendly environment to build the rapport and gain their confidence
  • Speak casual-talk general non-controversial subjects of mutual interest
  • Self introduction Socio-demographic details can be collected
  • Seek verbal consent and permission for using tape recorder
  • Explain purpose of study and its utility.
  • Spell out the ground rules of FGD
  • Clarify that it is not a question answer session, but a discussion.
  • Ensure confidentiality of their views.
  • Emphasis that there is no right and wrong answers.
  • Encourage participants to talk freely and should even express contradictory /opposite views
  • Tell them that they should speak clearly , one at a time ,avoid interrupting one another
  • Start with generic topic before coming to specific area of enquiry
  • Initiate discussion by suitably framing the issues as statements
  • Guide the discussion by logically steering the issues. Picking up responses and probing further can be done
  • Avoid questions eliciting Yes/ No answer
  • Make sure not to leave any issue
  • Atmosphere Warm, friendly and non-judgemental
  • Pauses and prompts
  • - Pausing allow to think more on the topic, but should not last more than five seconds
  • -Establishing eye contact, nodding and other gestures encourage people to talk
  • -Verbal prompts I see, keep on,mmm, uh-huh
  • The probe Encourage speaker to give more information
  • -Prepare probes for each question
  • -Use probes where ever needed during discussion eg. Could you explain further?, Would you give an example?
  • Rephrasing- A question can be rephrased using different words, not diluting the issue
  • Clarification- To clarify an issue,facilitator can request Can you repeat it or Please elaborate
  • Reorientation-Facilitator use participants response to restate the question for another participant
  • Hypothetical Question- Suppose the baby develops high fever what would you do?
  • Dominant participant.
  • Facilitator should avoid eye contact. Facilitator can change the subject. If the said strategies failed, the facilitator can politely request that the others be allowed to speak.
  • Can offer lot of useful information, but should not be allowed to take over and prevent others from speaking
  • Facilitator should have more eye contact.
  • Facilitator can ask the person to comment on what another person has said or to summarize what the group has discussed.
  • Answering one by one-Explain once more that discussion among participants are crucial
  • Participant bring small child If dont disrupt, let him/her remain
  • Leave the group early- allow
  • Bored/ look sleepy- Cut jokes, brief break serve cold/hot drinks
  • Note the details of discussion
  • The note should also include
  • -Information required for the session report
  • -Group dynamics
  • -The intermission and distractions occur
  • - What makes the participants laugh
  • What seems to make them reluctant to answer.
  • Whether the facilitator lost control of the meeting.
  • How the discussion is concluded
  • Should use quotation marks to indicate participants words.
  • Inform participants that discussion is going to end and if they have any query or want to contribute they can do.
  • Thank them for their cooperation and valuable comments.
  • Assure the participants that under no circumstances the discussion would prove counter productive to the interest of the group
  • During this debriefing period, tape recorder should remain on valuable comments are some times made at this time.
  • Lot of information - quickly less costly
  • Excellent in obtaining information from illiterate communities
  • Flexibility- discover attitudes and opinions that might not be revealed otherwise
  • Well accepted by the community
  • If simple issues- managed by people not trained in qualitative research methods
  • Most valuable when used in conjunction with other quantitative information
  • Not suitable for arriving at generalizable conclusions
  • Quality of information depends heavily on moderator skills
  • Limited value in exploring complex beliefs
  • Number of questions are limited
  • Sensitive and personal issues-Socially acceptable responses unless put as general questions
  • Data source for analysis
  • Debriefings
  • Quick and easy way of summarizing data immediately after the field work.
  • Notes and comments of both verbal and non verbal information compiled by the moderator and observer.
  • Transcripts
  • Transcribing is very demanding,
  • Translation from Local Language if necessary
  • Two approaches
  • Systematic coding using content analysis
  • Ethnographic Summary
  • Transcript analysis soon after transcripts available
  • - Not after completion of all FGDs.
  • Edit Transcript
  • - Removing sections poorly transcribed or do not make sense
  • Read the transcript with objectives fresh in mind. Look for major opinions and attitude.
  • Evolving Domains
  • Look for patterns and themes evolving from the data
  • Marking the transcripts using codes
  • Sorting the coded transcripts and summarize.
  • Log Book (Overview grid)
  • Useful summarizing tool.
  • Enable to find out how many times an issue was discussed across all the Focus Groups as well as how many times a response was given.
  • Try to Avoid quantification while summarizing,
  • Semi quantification can be done with groups as unit of analysis.
  • Comparison can be done across different categories of stakeholders
  • Writing the report
  • Using Log book, codes from transcripts, observers notes as well as debriefing notes.
  • Present findings according to topics
  • Use quotations to illustrate strongly expressed thoughts, beliefs and emotions
  • Describe overall consensus of the group, Majority minority feelings as well as differences by characteristics of respondents.
  • Common style is to say The majority of participants said .. Or few of them..
  • Interpretation
  • Interpretation involved explaining your findings in terms of the problem or question you want to answer.
  • The format of FGD report should consist of three parts
  • 1. Description of setting and participants.
  • 2. Discussion of findings.
  • 3. Conclusion and recommendations.
  • Observation may be defined as a systematic viewing of a specific phenomenon in its proper setting for the specific purpose of gathering data for a particular study
  • It is a technique that involves directly observing behaviour with the purpose of describing it .
  • To observe means to examine an object, an individual, group of people or an event with all of the senses in order to describe it. It includes seeing, hearing and perceiving.
  • It is a method to collect firsthand data on programme, processes or behaviours being studied-what people actually do
  • Opportunity to collect data on a wide range of behaviours to capture a great variety of interactions to openly explore a topic
  • Holistic perspective, understanding of the context within which it operates
  • Serves a formulated research purpose
  • Planned deliberately
  • Recorded systematically
  • Subject to checks and controls on validity and reliability
  • Validity is assessed by examining how well the observations agree with alternative measures of the same construct
  • Reliability entails consistency and freedom from measurement error
  • Participant
  • events planed in advance
  • use of observational guide
  • No predetermined guide
  • Observer is part of the phenomenon or group which is observed
  • Roots in ethnographic research-immerse in the culture to see how people respond to situations, how they organise their lives, learning what is meaningful in their lives
  • See things from people perspective and a deeper understanding of them
  • Often conduct casual informal interviews while watching and recording to increase understanding
  • Level of participation depends upon the nature of study desired outcome
  • Requires lengthy period of engagement in the field
  • The observed may not be aware of the researcher purpose
  • Useful in understanding basic values behaviour associated with particular actions
  • Discover the relationship between knowledge, attitude and practice
  • Observer will be able to record context which gives meaning to the observed behaviour and heard statements
  • Can be effectively combined with other methods
  • Narrows the range of observation
  • To the extent that observer participates emotionally, the objectivity is lost
  • Participation can interfere with observation and recording.
  • Research skills essential
  • Systematically observing and documenting something in its natural setting
  • Silent observers
  • Researcher watches records information about people or event without intruding into the scene
  • Look for many things and describe the situations at many different levels
  • Ethical issues need to be addressed
  • No rule as to how many- spread observations over time
  • Unstructured observation involves broadly focussed encounters without a pre-determined guide
  • Data primarily used for descriptive accounts
  • More of exploratory in nature
  • Observes events that have been planned in advance
  • Validate data obtained from other methods
  • Standardization of observational technique
  • Typified by clear and explicit decisions on what, how and when to observe (Persons/locations, duration of observations, time to conduct, frequency)
  • Can be quantified , but with little contextual description
  • Selection criteria - Depends on the purpose of the study
  • Sampling purposive Sampling
  • Sources of information consider what is to be observed, who is the foci of attention, where will the observation take place and what is the most appropriate recording system
  • Observer qualities Familiarity with cultural background of people being observed
  • Knowledge of social research technique
  • Observers role unobtrusive, interest in the events being observed
  • Training to enable them take note of un-forseen events, share study objectives, how to conduct and how to deal with field problems
  • Issues to be observed prepared in advance based on the research objectives
  • Inputs from observers / observers familiar with the issues in the study
  • Goal oriented and suitable to local condition
  • The items should appear in logical grouping and in the order in which to observe them
  • Prior site selection and permission from authorities
  • No of observation sites availability, accessibility and study specific
  • Date and time- Remember that observations are activity linked
  • No of observations per site - depend upon the purpose of study
  • Inform and explain your presence
  • Gain confidence and cooperation of subjects
  • Remain detached yet involved with the group
  • Take note of the observation situations and also of non-verbal communication
  • Avoid making extensive notes during observation
  • Use all senses to describe the setting-physical and social environment non-verbal communication
  • Field notes- include observation notes, feelings and reflections
  • Direct quotations
  • Technological tools-Tape recorder, camera, Laptop etc.
  • Categorization of data Qualitative part
  • Coding Quantitative aspects and categorized data
  • Summarizing Report as percentages and / or in a narrative style depending on data
  • Findings combined with other methods to make a complete report
  • Recording in context possibility of cross check
  • Basic to other more systematic research
  • Discover the relationship between K, A and P
  • Opportunity for identifying unanticipated outcome
  • Ideally long periods of intense field work
  • Local language fluency
  • Replicality a problem
  • Difficult to quantify
  • No use in studying past event or activity
  • Observer bias
  • Change in behaviour
  • Questionable reliability
  • Observer may influence behaviour
  • Actins can only be observed-not thinking
  • Several researchers make observations
  • Systematically repeat observations
  • Repeat observations. Spent time to reduce self-consciousness
  • Mix with other methods like interview
  • Strategies to ensure rigour systematic research design, data collection, interpretation and communication techniques
  • Create an account of method and data which can stand up to independent scrutiny
  • Produce coherent explanation of the phenomena under scrutiny
  • Maintain record of interviews and observations
  • Document entire processes
  • Develop coding framework
  • Presence of audio or video tapes provides opportunities for analysis by independent observers
  • Internal Validity
  • Quan Measuring what you intend to measure
  • Qual Findings need to reflect the truth
  • External validity
  • - Quan Generalizability through stat inference
  • - Qual Transferability through understanding of relationship between context and findings
  • Main research tool researchers themselves
  • Subjective nature of data can open it to criticism
  • Method to enhance quality of data through triangulation data, researcher, combining methods
  • Can be assessed by
  • Careful documentation of research process
  • Independent replication of research process
  • Comparison with findings with previous research
  • Triangulation
  • Consistency checks Independent coder given research objectives categories and their description without raw text
  • Then given a sample of raw text and asked to assign section of text from which initial categories where developed.
  • Stake holder check Participants, service providers, funding agencies comment on categories or interpretations made
  • QDA does not completely analyze data
  • A tool that supports the process of qualitative data analysis
  • Large volume of data can be structured very quickly and clearly presented
  • Helps the researcher in searching texts, memos or coded passage easily
  • Great flexibility
  • Complex analysis becomes feasible
  • Analysis can be more systematic
  • Easy to handle large amount of data
  • Increases the status and believability
  • Danger of loosing touch with data
  • We can perform quick but irrelevant analysis
  • High degrees of complexity can lead to poor manageability
  • Can lead to dull and meaningless analysis result
  • Text Base Beta
  • The Ethnograph

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  • 1. -JAISMEEN KAUR DEPARMENT OF PSYCHOLOGY PUNJABI UNIVERSITY PATIALA 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 1
  • 2. Contents:  Introduction to qualitative research  History  Characteristics  Methods  Issues in qualitative research  Basic steps of qualitative research  Strategies for analysing  Writing the research reports  Ethics revisited 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 2
  • 3. Introduction to Qualitative Research:  What is qualitative research? Qualitative research is a type of scientific research. In general terms, scientific research consists of an investigation that:  seeks answers to a question  systematically uses a predefined set of procedures to answer the question  collects evidence •  produces findings that were not determined in advance  produces findings that are applicable beyond the immediate boundaries of the study 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 3
  • 4.  Qualitative research shares these characteristics. Additionally, it seeks to understand a given research problem or topic from the perspectives of the local population it involves.  Qualitative research is especially effective in obtaining culturally specific information about the values, opinions, behaviours, and social contexts of particular populations. 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 4
  • 5. History :  Robert Bogdan in his advanced courses on qualitative research traces the history of the development of the fields, and their particular relevance to disability and including the work of his colleague Robert Edgerton and a founder of participant observation, Howard S. Becker.[8] As Robert Bogdan and Sari Biklen describe in their education text, "historians of qualitative research have never, for instance, included Freud or Piaget as developers of the qualitative approach, yet both relied on case studies, observations and indepth interviewing".[9]  In the early 1900s, some researchers rejected positivism, the theoretical idea that there is an objective world which we can gather data from and "verify" this data through empiricism. These researchers embraced a qualitative research paradigm, attempting to make qualitative research as "rigorous" as quantitative research and creating myriad methods for qualitative research. Of course, such developments were necessary as qualitative researchers won national center awards, in collaboration with their research colleagues at other universities and departments; and university administration funded Ph.D.s in both arenas through the ensuing decades. Most theoretical constructs involve a process of qualitative analysis and understanding, and construction of these concepts (e.g., Wolfensberger's social role valorization theories).[10] 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 5
  • 6.  In the 1970s and 1980s, the increasing ubiquity of computers aided in qualitative analyses, several journals with a qualitative focus emerged, and postpositivism gained recognition in the academy. In the late 1980s, questions of identity emerged, including issues of race, class, gender, and discourse communities, leading to research and writing becoming more reflexive. Throughout the 1990s, the concept of a passive observer/researcher was rejected, and qualitative research became more participatory and activist-oriented with support from the federal branches, such as the National Institute on Disability Research and Rehabilitation (NIDRR) of the US Department of Education (e.g., Rehabilitation Research and Training Centers for Family and Community Living, 1990). Also, during this time, researchers began to use mixed-method approaches, indicating a shift in thinking of qualitative and quantitative methods as intrinsically incompatible. However, this history is not apolitical, as this has ushered in a politics of "evidence" (e.g., evidence-based practices in health and human services) and what can count as "scientific" research in scholarship, a current, ongoing debate in the academy. 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 6
  • 7.  What can we learn from qualitative research? The strength of qualitative research is its ability to provide complex textual descriptions of how people experience a given research issue. It provides information about the “human” side of an issue – that is, the often contradictory behaviours, beliefs, opinions, emotions, and relationships of individuals. • Qualitative methods are also effective in identifying intangible factors, such as social norms, socioeconomic status, gender roles, ethnicity, and religion, whose role in the research 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 7
  • 8. issue may not be readily apparent. When used along with quantitative methods, qualitative research can help us to interpret and better understand the complex reality of a given situation and the implications of quantitative data. Although findings from qualitative data can often be extended to people with characteristics similar to those in the study population, gaining a rich and complex understanding of a specific social context or phenomenon typically takes precedence over eliciting data that can be generalized to other geographical areas or populations. In this sense, qualitative research differs slightly from scientific research in general. 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 8
  • 9. Characteristics of Qualitative Research:  Qualitative research is an effort to understand situations in their uniqueness as part of a particular context and the interactions there (Patton, 1985).  A second characteristic of all forms of qualitative research is that the researcher is the primary instrument for data collection and analysis.  A third characteristic of qualitative research is that it usually involves fieldwork. The researcher must go to the people, setting, site, institution, in order to observe behavior in its natural setting 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 9
  • 10.  A fourth characteristic of qualitative research is that is uses an inductive research strategy. This type of research builds abstractions, concepts, hypothesis, or theories rather than tests existing theory • Data sources are real-world situations • Data are descriptive • Emphasizes a holistic approach (processes and outcomes) • Data analysis is inductive • Describes the meaning(s) of research finding(s) from the perspective of the research participants 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 10
  • 11. Qualitative Methods:  Historical research …studies available data to study, understand, and interpret past events • Ethnography … studies cultural patterns and perspectives of participants in their natural settings • Case Study … examines the characteristics of a particular entity, phenomenon, or person 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 11
  • 12.  Ethology … examines the characteristics of a particular entity, phenomenon, or person • Ethnomethodology …studies how people make sense of their everyday activities in order to behave in socially accepted ways • Grounded theory …investigates how inductively-derived theory about phenomenon is grounded in the data of a particular setting 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 12
  • 13.  Phenomenology …considers how the experience of particular participants exhibits a unique perspective • Action research …teacher-initiated, school-based research used to improve the practitioner’s practice by doing or changing something 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 13
  • 14. Issues in qualitative research... • gaining entry  contacting potential research participants  selecting participants  enhancing validity and reducing bias  leaving the field 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 14
  • 15.  Gaining entry...  access is very much dependent upon the researcher’s personal characteristics and how others perceive the researcher  may require considerable negotiation and compromise with a gatekeeper  trust is earned, not given  contacting participants... gaining access  dealing with gatekeeper(s)  issues of building trust and ensuring confidentiality and anonymity 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 15
  • 16. selecting participants...  two general guidelines: the number of participants is sufficient when…  …the extent to which the selected participants represent the range of potential participants in the setting  …the point at which the data gathered begins to be redundant (“data saturation”) 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 16
  • 17. The threats to validity in qualitative studies...  observer bias… …invalid information resulting from the perspective the researcher brings to the study and imposes upon it • observer effects… …the impact of the observer’s participation on the setting or the participants being studied 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 17
  • 18. strategies to enhance validity and to reduce bias...  extend the time for observing the setting  include more participants to make the study more representative  focus upon building participant trust in order to access more detailed and honest data  identify biases and preferences, seek them out by asking others 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 18
  • 19.  work with another researcher and compare field notes and impressions from independent observations  after observations are completed, offer participants an opportunity to validate accuracy of the verbatims  journalize one’s own reflections, concerns, and uncertainties during the study and refer to them when examining the data  carefully examine unusual or contradictory results for explanations (“outliers”) 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 19
  • 20.  utilize a variety of data sources to confirm one another to corroborate participant information (“triangulation”)  leaving the field…  The question is when and how to exit  the bonds formed with study participants complicate leaving the setting  time constraints  when the amount of accessible data is sufficient 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 20
  • 21. The basic steps of qualitative research...  Write a tentative research proposal  Intensive participation in a field setting  Collect detailed data from field activities • Synthesize and interpret the meanings of the field data • Write the research report 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 21
  • 22. Strategies for analyzing qualitative data...  constant comparison method …compares new evidence to prior evidence to identify similarities and differences between observations • negative case and discrepant data methods …the search for contradictory, variant, or disconfirming data within the body of data collected that provides an alternative perspective on an emerging category or pattern 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 22
  • 23.  Writing the research report...  provide a setting where the data were collected • identify characters who provide information • describe the social action in which the characters are engaged • offers an interpretation of what the social action means to the characters • follow all APA Publication Manual guidelines 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 23
  • 24. Ethics Revisited  The subjects’ identities should be protected so that the information you collect does not embarrass or harm them.  Treat subjects with respect and seek their cooperation in the research  Make it clear to the participants in the study what the terms of the agreement (consent form) are and abide by that.  Tell the truth when you write up your final report. 10-02-2017 © Jaismeen Kaur, Punjabi University, Patiala 24

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Qualitative Research

Apr 01, 2019

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Qualitative Research. Qualitative Research Methods. Its aim is to give a complete, detailed descriptions of the phenomena to be studied Objective facts + values Key philosophical assumption - understanding how people make sense of their worlds and the experiences people have

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Qualitative Research Methods • Its aim is to give a complete, detailed descriptions of the phenomena to be studied • Objective facts + values • Key philosophical assumption - understanding how people make sense of their worlds and the experiences people have • Key concern - knowing or understanding from the participants’ perspectives • Key focus - understanding (rather than predicting or controlling) social settings or social phenomena

In qualitative research, the researcher constructs knowledge in collaboration with research participants through interaction and reflection Knowledge is considered as a social construct Tries to include values and motives of the actors in the Knowledge Construction Process Focus is to have a deeper understanding of the selected phenomena in its holestic state Qualitative ---

Nature of Qualitative Research • the problem is general and ask general questions about the phenomena being studied • As the researcher gets increasing understanding of the phenomena, he/she asks specific questions • The methodology is decided over the course of investigation

Qualitative Data • Mostly words, phrases, sentences and may include visual images, audio and video recordings. • Obtained from recordings of interviews, field notes of observations, and analysis of documents as well as reflective notes of the researcher. • Mass of qualitative data is organised, summarised, described and interpreted

When to choose? • Describe the phenomena • Build a theory • To gain new insights about a particular phenomena • Develop new concepts or theoretical perspectives about the phenomena • Discover the problem that exists in the phenomena • Verification – to test the validity of certain assumptions, claims, theories or generalization with the real world • Evaluation – to evaluate the effectiveness of a particular policies, design artifacts, programs, etc

Define problem Review literature Conceptual framework/ Proposal Collect Data Data Analysis BuildTheory Or Framework Data Interpretation/ Report Findings

Type of Qualitative Research • Case study • Phenomenological study • Ethnography • Grounded theory • Content Analysis • Etc. • There are more than one hundred qualitative research methods.

What is a case study? • case study is an empirical research method. • it is not a subset or variant of other methods, such as experiments, surveys or historical study. • Best suited to applied problems that need to be studied in context. • Phenomena under study cannot be separated from context. Effects can be wide-ranging. • How and why questions • Settings where researcher has little control over variables, e.g. field sites. • Effects take time to appear. • Days, weeks, months, or years rather than minutes or hours.

Why conduct a case study? • To gain a deep understanding of a phenomenon • Example: To understand the capability of a new tool • Example: To identify factors affecting communication in code inspections • Example: To characterize the process of coming up to speed on a project • Objective of Investigation • Exploration-To find what’s out there • Characterization-To more fully describe • Validation-To find out whether a theory/hypothesis is true • subject of Investigation • An intervention, e.g. tool, technique, method, approach to design, implementation, or organizational structure • An existing thing or process, e.g. software implementation, project success, defects

Parts of a Case Study Research Design • A research design is a “blueprint” for a study • Deals more with the logic of the study than the logistics • Plan for moving from questions to answers • Ensures that the data is collected and analyzed to produce an answer to the initial research question • Strong similarities between a research design and a system design • Five parts of a case study research design • Research questions • Propositions (if any) • Unit(s) of analysis • Logic linking the data to the propositions • Criteria for interpreting the findings

Part 1: Study Questions • Case studies are most appropriate for research questions that are of the “how” and “why” variety • The initial task is to clarify precisely the nature of the study questions (i.e. make sure they are actually “how” or “why” questions) • Examples: • “Why do 2 organizations have a collaborative relationship?” • "Why do developers prefer this tool/model/notation?" • "How are inspections carried out in practice?“ • "How does agile development work in practice?" • "Why do programmers fail to document their code?“ • "How does software evolve over time?“ • "Why have formal methods not been adopted widely for safety critical applications?“ • "How does a company identify which software development projects to start?"

Types of Case Studies Explanatory Adjudicates between competing explanations Example: How important is implementation bias in requirements engineering? Rival theories: existing architectures are useful for anchoring,vs. existing architectures are over-constraining during RE Descriptive Describes sequence of events and underlying mechanisms Example: How does pair programming actually work? Example: How do software immigrants naturalize?

Types of case … Causal Looks for causal relationship between concepts Example: Requirements errors are more likely to cause safety-related defects than programming errors are See study by Robyn Lutz on the Voyager and Galileo spacecraft Exploratory Criteria or parameters instead of purpose Example: Christopher Columbus’ voyage to the new world Example: What do CMM level 3 organizations have in common?

Part 2: Study Propositions • Propositions are statements that help direct attention to something that should be examined in the case study, i.e. point to what should be studied • Example: “Organizations collaborate because they derive mutual benefits” • Propositions will tell you where to look for relevant evidence • Example: Define and ascertain the specific benefits to each organization • Some studies may not have propositions –this implies a topic of “exploration” • Note: Even exploratory studies should have both clearly-stated purposes and clearly-stated criteria for success

Part 3: Unit of Analysis • The unit of analysis defines what a “case” is in a case study • Example: a unit of analysis (case) may be an individual, and the case study may be the life history of that person • Other units of analysis include decisions, social programs, processes, changes • Note: It is important to clarify the definition of these cases as they may be subjective, e.g. the beginning and end points of a process • What unit of analysis to use generally depends on the primary research questions • Once defined, the unit of analysis can still be changed if desired, e.g. as a result of discoveries based on data • To compare results with previous studies (or allow others to compare results with yours), try to select a unit of analysis that is or can be used by others

Examples of Units of Analysis • For a study of how software immigrants naturalize • Individuals • Development team • Organization • For a study of pair programming • Programming episode • Pairs of programmers • Development team • Organization • For a study of software evolution • Modification report • File • System • Release • Stable release

Part 4: Linking Logic • Logic or reasoning to link data to propositions • One of the least well developed components in case studies • Many ways to perform this, but none as precisely defined as the treatment/subject approach used in experiments • One possibility is pattern matching • Describe several potential patterns, then compare the case study data to the patterns and see which one is closer

Generalizing from Case Study to Theory • “The appropriately developed theory is also at the level at which generalization of the case study results will occur” • Theory for case studies is characterized as analytic generalization and is contrasted with another way of generalizing results known as statistical generalization • Understanding the difference between these two types of generalization is important

Statistical Generalization • Making an inference about a population on the basis of empirical data collected about a sample • This method of generalization is commonly recognized because research investigators have quantitative formulas characterizing generalizations that can be made • Examples: significance, confidence, size of the effect, correlation • Using this as a method of generalizing the results of a case study is a “fatal flaw”, since cases are not sampling units, nor should they be chosen for this reason • Statistical generalizations are considered a Level One Inference

Analytical Generalization • Previously developed theory is used as a template with which to compare the empirical results of the case study • If 2 or more cases support the same theory, replication may be claimed • Results may be considered more “potent” if 2 or more cases support the same theory but don’t support the same rival theory • Analytical generalizations are considered a Level 2 Inference • Aim toward analytical generalization in doing case studies • Avoid thinking in terms of samples when doing case studies

Validity and Reliability in Case Study • Using the same criteria for other empirical research • Construct Validity • Concepts being studied are operationalized and measured correctly • Internal Validity • Establish a causal relationship among variables in the study • External Validity • Establish the domain to which a study’s findings can be generalized • Experimental Reliability • Demonstrate that the study can be repeated with the same results

Data Analysis • Analytic Strategies • 3 general strategies • 5 specific analytic techniques • Criteria for high quality analysis

Criteria for High Quality Analysis • Present all the evidence • Develop rival hypotheses • Address all major rival interpretations • Address most significant aspect of the case study • Use prior or expert knowledge

Three General Strategies • Relying on Theoretical Propositions • Thinking about Rival Explanations • Developing a Case Description

Strategy 1 -Relying on Theoretical Propositions • Shapes the data collection plan and gives priorities to the relevant analytic strategies • Helps to focus attention on certain data and to ignore other useless data • Helps to organize the entire case study and define alternative explanations to be examined

Strategy 2 -Thinking About Rival Explanations • Defines and tests rival explanations • Relates to theoretical propositions, which contain rival hypotheses • Attempts to collect evidence about other possible influences • The more rivals the analysis addresses and rejects, the more confidence can be placed in the findings

Strategy 3 -Developing a Case Description • Serves as an alternative when theoretical proposition and rival explanation are not applicable • Identifies • an embedded unit of analysis • an overall pattern of complexity to explain why implementation had failed

Five Specific Analytic Techniques • Pattern Matching • Explanation Building • Time-Series Analysis • Logic Models • Cross-Case Synthesis • Note: They are intended to deal with problems of developing internal and external validity in doing case studies

AT 1 -Pattern Matching • Pattern matching compares an empirically based pattern with a predicted one • If the patterns coincide, the results can strengthen the internal validity of the case study • Types of pattern matching: • Nonequivalent dependent variables as a pattern • Rival explanations as patterns

Nonequivalent dependent variables as a pattern • Quasi-experiment may have multiple dependent variables (variety of outcomes) • If, for each outcome, the initially predicted values have been found, and at the same time alternative “patterns” of predicted values have not been found, strong causal inferences can be made

PM 2 -Rival Explanations • Each case has certain type of outcome, and the investigation has to be focused on how and why this outcome occurred • This analysis requires the development of rival theoretical propositions, articulated in operational terms • Each rival explanation involves a pattern of independent variables that is mutually exclusive: If one explanation is to be valid, the others cannot be valid

AT 2 -Explanation Building • Analyzes the case study data by building an explanation about the case • Stipulates a presumed set of causal links, which are similar to the independent variables in the use of rival explanations • Has mostly occurred in narrative form • May lead to starting a cross-case analysis, not just an analysis of each individual case • Disadvantage: may drift away from original focus

AT 2 -Explanation Building • Series of iterations in building explanation • Making initial theoretical statement • Comparing the findings of the initial case against such a statement • Revising the statement • Comparing other details of the case against the revision • Comparing the revisions to the facts of 2nd, 3rd or more cases • Repeating the process if needed

AT 3 -Time Series Analysis • The objective of time series analysis is to examine relevant “how” and “why” questions about the relationship of events over time • Time series analysis can follow intricate patterns • The more intricate the pattern, the firmer the foundation for conclusions of the case study • Three types of Time Series Analyses: • Simple Time Series • Complex Time Series • Chronologies

TA 1 -Simple Time Series • Trace changes over time • Match between a trend of data points compared to • Significant trend specified before investigation • rival trend specified earlier • any other trend based on some artifact or threat to internal validity • Yin (2003) recommended two identify two patterns from the data and compare with theoretical proposition (“effects” and “no effect”) • One fits best than the other

TA 2 -Complex Time Series • Contain multiple set of variables (mixed patterns) which are relevant to the case study • Each variable is predicted to have different pattern over time • Create greater problems for data collection, but lead to elaborate trend that strengthens the analysis • Any match of a predicted with an actual time series will produce strong evidence for an initial theoretical proposition

TA 3 -Chronologies • Trace events over time • Sequence of a cause and effect cannot be inverted • Some events must be followed by other events on a contingency basis after an interval of time • Cover many different types of variables • Goal is to compare chronology with that predicted by the explanatory theory • Example – Internet Introduced->computer use->efficient communication ->organizational performance

AT 4 -Logic Models • Stipulate a complex chain of events over time • Events are staged in repeated cause-effect-cause-effect patterns • Match empirically observed events to theoretically predicted events • Four types of logic models: • Individual-Level Logic Model • Firm or Organizational-Level Logic Model • An alternative configuration for an Organizational-Level Logic Model • Program-Level Logic Model

Logic Models • A) Individual-level logic model • Assumes the case study is about an individual person • B) Firm or organizational-level logic model • Traces events taking place in an individual organization • C) An alternative configuration for an organizational-level logic model • Encounters dynamic events that are not progressing linearly • Changes may reverse course and not just progress in one direction (Transformation and reforming) • D) Program-level logic model • Analyzes data from different case studies by collecting data on rival explanations

Further Notes on Data analysis • Coding is the process of examining the raw qualitative data in the transcripts and extracting sections of text units (words, phrases, sentences or paragraphs) and assigning different codes or labels so that they can easily be retrieved at a later stage for further comparison and analysis, and the identification of any patterns. • Codes can be based on: • Themes, Topics • Ideas, Concepts • Terms, Phrases • Keywords • Which are found in the data

Example • You have uncovered eight descriptions of the principal’s behaviour in staff meetings and the following codes are assigned. B1 – hot tempered; B2 – lost his cool B3 – refused to listen B4 – just went on and on B6 – scolds B7 – ridiculed for questioning B8 – one man show

Case Study as a Research Method • The case study is a distinct research method with its own research designs • It is not a subset or variant of research designs used for other strategies (such as experiments) • Scientific • Synergistic relationship between theory and data • Starting a case study requires a theoretical orientation, which drives data collection • Useful for answering “how” and “why” questions • In contrast to who, what, when, how many, how much • How, why = explanatory, descriptive • Does not require control over events • More observational • Focus on contemporary events • Less historical

Qualitative research and computer science • Used to understand user problems for design such in diagnosing user problems and needs • Used in artifact evaluation- researchers qualitatively evaluate a product by interviewing and observation • Used to uncover non-technical factors affecting the adoption and evolution of a new software product and other IT systems • Used to develop theories such as HCI theory

Application of Qualitative - Example • System Development Research Process that Nunamaker, et al (1991) proposed five stages or activities • construct a conceptual framework, • develop a system architecture, • analyze and design the system, • build the (prototype) system, and • observe and evaluate the system. • The last stage explicitly includes “Develop new theories/models based on the observation and experimentation of the system’s usage”

Review Questions • What is the nature of qualitative research • What are the different types of qualitative research methods • When do you case study research method • What are the different type of case study research? Exaplain them? • What data analysis technique you use for case study research? Explain them? • What the procedures you follow to do case study research? • When do you qualitative methods in computer science research?

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  1. How to layout qualitative slides

  2. RESEARCH METHODOLOGY (PRESENTATION)

  3. 04. Lecture 2.1 tables for qualitative data

  4. Qualitative Research Proposal Template PowerPoint Presentation Slides

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  6. Ray's Research Corner: Qualitative and Quantitative Research

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  1. PDF PowerPoint Presentation

    2. Generating research hypotheses that can be tested using more quant.tat.ve approaches. 3. Stimulating new .deas and creative concepts. 4. Diagnosing the potential for prob ems with a new program, service, or product. 5. Generating impressions of products, programs, services, institutions, or other objects of interest.

  2. Qualitative Research

    Nov 6, 2013 •. 125 likes • 124,906 views. Abhimanyu Singh. Follow. Education Technology. 1 of 52. Download Now. Download to read offline. Qualitative Research - Download as a PDF or view online for free.

  3. An introduction to qualitative research

    AI-enhanced description. Najibullah Safi. This document provides an introduction to qualitative research methods. It outlines some key differences between qualitative and quantitative research, including that qualitative research is subjective, holistic, and aims to understand why and how phenomena occur rather than objective measurements.

  4. [Guide] How to Present Qualitative Research Findings in PowerPoint?

    In order to present the qualitative research findings using PowerPoint, you need to create a robust structure for your presentation, make it engaging and visually appealing, present the patterns with explanations for it and highlight the conclusion of your research findings. In this article, we will help you understand the structure of your ...

  5. INTRODUCTION TO QUALITATIVE RESEARCH

    LEARNING OBJECTIVES This introductory lecture will help you to: 1. Recognise the meaning of research design, research methodology and research methods. 2. Recognise the key characteristics of qualitative research. 3. Distinguish between qualitative and quantitative methods in research. 4. Describe qualitative research approaches (designs). 5. Describe methods of data collection and analysis in ...

  6. Qualitative Research Methods

    7. II Different Research Strategies 2.2 Qualitative research strategy - Usually emphasizes words rather than quantification in the collection and analysis of data - Predominantly emphasizes an inductive approach to the relationship between theory and research, in which the emphasis is placed on the generation of theories - Has rejected the practices and norms of the natural scientific model in ...

  7. PDF Asking the Right Question: Qualitative Research Design and Analysis

    Limitations of Qualitative Research. Lengthy and complicated designs, which do not draw large samples. Validity of reliability of subjective data. Difficult to replicate study because of central role of the researcher and context. Data analysis and interpretation is time consuming. Subjective - open to misinterpretation.

  8. Chapter 20. Presentations

    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 ...

  9. Qualitative Analysis: Process and Examples

    By Monograph Matters May 12, 2020 Teaching and Research Resources. Authors Laura Wray-Lake and Laura Abrams describe qualitative data analysis, with illustrative examples from their SRCD monograph, Pathways to Civic Engagement Among Urban Youth of Color. This PowerPoint document includes presenter notes, making it an ideal resource for ...

  10. PPT

    Difference b/t Qualitative & Quantitative Where quantitative research which attempts to gather data by objective methods to provide information about relations, comparisons, and predictions and attempts to remove the investigator from the investigation, the researcher is an integral part of qualitative research. (Smith, 1983)

  11. Qualitative Research Resources: Presenting Qualitative Research

    Find sources of qualitative training & support at UNC. How to search for and evaluate qualitative research, integrate qualitative research into systematic reviews, report/publish qualitative research. Includes some Mixed Methods resources. Some examples and thoughts on presenting qualitative research, with a focus on posters

  12. Qualitative Presentation Strategies

    Qualitative Presentation Strategies. Nov 14, 2023. By Dr. Linda Bloomberg, and hosted by Janet Salmons, Ph.D., Research Community Manager for Sage Methodspace. Dr. Bloomberg is the author of Completing Your Qualitative Dissertation: A Road Map From Beginning to End. Use the code COMMUNITY3 for a 20% discount when you order her book, valid ...

  13. Top 10 Qualitative Research Report Templates with Samples ...

    Template 4 : Thematic Analysis Qualitative Research PPT PowerPoint Presentation Outline Rules CPB . Thematic analysis is a technique used in qualitative research to arrive at hidden patterns and other inferences based on a theme. Any research can employ our Thematic analysis qualitative research PPT. By using all the features of this adaptable ...

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    Features of Qualitative Research (Hoepfl) . Natural setting as source of data Researcher acts as human instrument Inductive data analysis Reports are descriptive Incorporating "voice". Download Presentation. quite likely. observer expectations. interviews. coding observational data. interviewing content analysis ethnography.

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    Qualitative Research. Theoretical Approaches Modalities of Qualitative Research Sampling Methods Software Packages. Qualitative Research. Qualitative research seeks to gain a comprehensive and holistic view of social life through the study of people in a wide range of natural settings. 795 views • 17 slides

  16. Qualitative research designs

    65 likes • 32,268 views. Muthu Venkatachalam. Follow. qualitative research designs, qualitative research designs in nursing, qualitative nursing research. Health & Medicine. 1 of 40. Download Now. Download to read offline. No single truth Primarily found in anthropology, sociology, history, political science, medicine, psychology, and education.

  17. QUALITATIVE RESEARCH METHODS

    WHAT IS QUALITATIVE RESEARCH (contd) Aims to elicit the individual contextualized. understanding of a problem. Achieved through designs that minimize researcher. manipulation of social setting. Close interaction with subjects. Meaning and interpretation cannot be dealt with. statistically. 4.

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    Presentation Transcript. Introduction to Qualitative Research Design By: S. Babar Ali. QUALITATIVE RESEARCH: GROWING IN POPULARITY IN HEALTH AND MEDICINE • Qualitative methods are becoming increasingly prevalent in medical and related research. They provide additional ways for health researchers to explore and explain the contexts in which ...

  20. Qualitative research

    6. In the 1970s and 1980s, the increasing ubiquity of computers aided in qualitative analyses, several journals with a qualitative focus emerged, and postpositivism gained recognition in the academy. In the late 1980s, questions of identity emerged, including issues of race, class, gender, and discourse communities, leading to research and writing becoming more reflexive.

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    Presentation Transcript. Qualitative Research. Qualitative Research Methods • Its aim is to give a complete, detailed descriptions of the phenomena to be studied • Objective facts + values • Key philosophical assumption - understanding how people make sense of their worlds and the experiences people have • Key concern - knowing or ...

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    Elegant Black & White Thesis Defense. Present your research findings with grace and assertiveness through this template. Available for Google Slides and PowerPoint, this design set offers minimalistic charm with its simple, gray scale elegance. The template not only provides a polished platform to showcase your thesis but also ensures seamless ...