Dissertation Suite: Introduction to Qualitative Research

Join the University of Chester's Academic Skills Team for The Skills Pod. In this episode of our Dissertation Suite, Academic Skills Advisers, Anthony and Stefan, discuss qualitative research methods. They provide an introduction to qualitative research, outline why they would choose to do it, and briefly discuss the different instruments which can be used. 

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Transcript

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Welcome And Topic Setup

Anthony 0:09

Hello everyone and welcome to another episode of the Skills Pod. My name is Tony and I'm one of senior academic skills advisors as part of the Academic Skills team.

Stefan 0:17

And today I'm joined by I'm Stefan and I'm an academic skills advisor here at Chester

Defining Qualitative Research

Speaker 1 0:22

as well.

Anthony 0:22

Thanks, Stefan, for coming along today to talk about qualitative research.

Stefan 0:26

Yeah, really pleased. Really, really excited to get into it. I mean, I'm a huge advocate for qualitative methods and yeah, always love to sit down and chat about them.

Anthony 0:37

Yeah, and as a as a pragmatist researcher, so I use both quants and quals. I do have a soft spot for quals. Um so yeah, if I had to pick, I would be picking quals over quants. Sorry, maths and stats team. Um, but yeah, there's just something about qualitative research, I think, which is which is exciting. And we're gonna talk about those kind of nuances today, aren't we, Stefan? Mm-hmm, definitely. Yeah. So I guess the first thing to start is, you know, you people might have heard of you know quantitative research, qualitative research. So what is qualitative research?

Stefan 1:11

So I would always say that qualitative research is that sort of research where we're trying to understand like the complexities, the nuances, the subjectivities of the human condition, right? It's where we're not trying to quantify things, right? That's down to the quantitative methods, right? It's where we're trying to understand more of the gray areas that can't be boiled down to numbers. So things like feelings, things like experiences, things like why do people do things in a particular way or for a particular reason, etc. etc. That's generally what I think, but what do you think?

Anthony 1:50

Yeah, I think for me it's the the quantitative one is kind of that broad kind of broad brush, like what does X amount of population say? And you can kind of get a general idea. But for me, qualitative is you could have, for example, you could have a hundred people saying yes to a question, but the qualitative will give you the why. Why are they saying yes? So it's really important. I think qualitative is like you said there, Stephanie, it's it's the why, it's getting into the nitty-gritty of people because people are complex, they have you know those preconceived ideas, they've all grown up differently, different educational backgrounds, and how they view certain things isn't a simple black and white yes or no, positive, negative, there's loads of nuances, and we have to go talk to them, observe them, find out what they're doing in order to kind of see why they're doing what they're doing, uh, or why they say what they say, and that's why qual I think is is really really important. And if you are thinking,

Depth, Storytelling, And Researcher Role

Anthony 2:53

oh, that sounds like you know, yeah, that sounds like something I want to do, you know, make sure that you kind of understand where qualitative comes from in terms of your ontological and epistemological stance, because that's really the fundamental difference between qualitative and quantitative. So if you want to know more about that, we have an episode um already released about researcher position where we go into this in more detail. But effectively, if you are somebody who believes there are multiple realities, multiple truths, you believe that because people do have different experiences, there's not just one right answer, then you would take on that paradigm of qualitative nature, and you might be an interpretivist, constructivist, whatever that might be, but that's your fundamental difference. If you believe there's only one truth, then you're more likely to be a quad, a quantitative uh person in nature.

Stefan 3:46

Yeah, absolutely. I think it's uh um I think for me, one of the things that I always just really appreciate about qual is along with that kind of understanding of subjectivities, it's also just the depth that we can go into with it. Um so like we're saying, when it's about the nuance, about the subjectivity, about the sort of gray areas and the complexities, we can sit down with a smaller sample of people and then go into that depth, do an hour-long interview, maybe a two-hour-long interview if we are lucky enough to be given that amount of time with someone, right? Um and often I think there's a certain level of storytelling that can come with qual that doesn't necessarily come with quants. Um, and it's just it just asks fundamentally different questions, right? Different tools for different uh occasions, both types of methods really, really effective, um, depending on what questions you are asking, right? What is it that you're interested to uncover, find out, and then go whichever way works best for that approach.

Anthony 4:53

Yeah, and and I guess as well, the other key difference is um in quantitative research. Quite often, as the as the researcher, you are removed from it. You would, you know, you would be objective, you might hear the term objectivity. Um, you know, you kind of remove yourself from it, you are observing that experiment, that survey. Whereas, like you said, this I think one of the beauties of qualitative is you are part of that instrument, you are part of that research. And and for me, you know, I like being tested as a qualitative researcher because my abilities to be a good qualitative researcher can impact how that research goes. Whereas if you're doing quantitative, you might have set your survey up, you've got your your data to analyze using you know formulas and statistics, you're a little bit removed. Whereas for qualitative research, how good you are as a qualitative researcher can really really help because you are part of that, and quite often, not always, but most often, qualitative researchers will do that particular research because they have a fundamental interest, or there's a fundamental problem or scenario that they want to solve, and I think that's what makes you said there, Stefan, really, really great that it's a storytelling aspect, and and it is, um, and that's because you are part of that, you're living it, you're breathing it, and that's what I think makes Qual's quite special.

Stefan 6:14

Definitely.

Bias, Positionality, And Lenses

Stefan 6:15

Um, and so can we can we just touch on that for a bit in terms of that nature of researcher involvement, positionality, and ultimately bias, because the amount of times that I have this conversation with students, because students are so kind of scared of that word bias, right? And when they're coming to design qual research, they start to see, oh, well, actually, my involvement here is is a lot, so therefore there's going to be loads of bias that I'm bringing in. That's bad, right? Well, there is an element within, like a kind of position within uh the qual research philosophy that you can only minimize your bias so much, right? Everyone is coming to their research with particular, as you said earlier, particular experiences, particular lenses on a topic, right? And we can try and minimize our bias to the extent that that we can. And there's different theoretical positions on the extent to which that's that's kind of necessary or even possible, but ultimately we'll never be able to do it completely, right? And I think this just kind of links back to a wider, uh, I guess a bit of a wider trap that I see some students fall into, which is they come to qual through a lens of quant. They are thinking that, oh, well, I'm gonna go and talk to 10 people, and then my analysis is gonna look like 60% of my 10 people said X, Y, and Z. Um and so this kind of nature of seeing qual through the lens of quant leads to some of these issues around like thinking that you have to completely strip yourself of any bias, any involvement, which is borderline impossible. Um, and then translates over into issues around analysis, right? So have you seen that as well, Tony, in terms of coming to qual through a lens of quant, um, and then also some of these questions around bias and things like that as well.

Anthony 8:21

Absolutely. I mean, I said before at the start, you know, I'm a pragmatist, but I didn't start off that way. I started off as a quantitative researcher. So through my undergrad and master's, all of my research was very, very quantitative in nature. And if I'm honest, I didn't have much time for qualitative because I kind of subscribed to the old trap of um the paradigm wars. You might have heard of them, you know, quads versus quals. And I came from a very science-y kind of background, um, and I much preferred quantitative because I like my black and white, my yes, my no. And then when I was a research assistant, my first two jobs as a research assistant was something incredibly qualitative. They were all interviews, and I really struggled with that process of coming to Quals, as you said there, Stefan, through the lens of quantitative nature. So, my entire career up to that point has been told remove yourself from the research, you don't want to be biased, you don't want to influence it, to then realizing, well, actually, I am part of the research, I can't remove myself from that. And I think the biggest trap as well that students fall into that I did as well was there must be one right answer. I'm going to interview 10, 20 people, um, yet if 80% of them say they found the skills pod really, really useful because of X, Y, and Z, then that's the right answer. And it took me ages to get into my head that actually there is no right answer to anything in qual because it is subjective. There are things which are getting close to a consensus, but they're not like quantitative where you can get a significance or an insignificance. And I think most students do get a little bit afraid, like you said, Stefan, about qualitative because of bias, and because it is that I'm not gonna get a full picture, a full, a full right answer here, and particularly if they come in from a very quantitative background, um, they're looking for that, they're looking for that one fundamental right answer, and yeah, they're coming to it through that quantitative lens. And we see it time and time again, students who are using thematic analysis in qualitative, and they're pulling their themes and they're saying, Well, this theme had this came up 20 times, therefore, that's the main theme I'm talking about. It's like, no, A, that's borderline content analysis, but B, you're looking at it through a through a very quantitative lens. And actually, what I try and say to students, and we'll touch on analysis a bit later on, but you might have a theme that only comes up once or twice across your entire data set, but that could be one of the most important themes, even though it's not been talked about by everyone, that's so important. So, yeah, it's something I definitely struggle with, and it takes time to kind of pull yourself away from that. Um, but yeah, you just have to know that quantity quality are fundamentally very different, they're trying to find very different things. Think of it as quant is that broad brush, and qual is more that nitty-gritty, that detail. And he said you can't remove yourself from that. Definitely. I think as well, Stefan, it's important, isn't it, that to talk about we mentioned their bias, and yes, there are ways we would remove that through our questions that we we set in advance, but actually, bias can be really, really useful in a way because um, particularly if you're doing interviews, you might have the insider versus outsider perspective. Um, so this is kind of the idea that let's say you are investigating student views of a particular topic, and you if you're a student yourself, when you have two cards to play, you can play the I'm an insider. So as a student, you recognize the challenges that you face as a student, and that can be really useful because A, you can kind of analyze your own experiences against that of that similar population. Are they agreeing, are they disagreeing? And you're also potentially more likely to probably get an interview because they would identify, oh, you're facing the similar challenges, I'll go talk to you. As an uh outsider, um, as an outsider perspective, so for example, for me, I'm no longer a student, so my participants may be reluctant to have that interview because they're like, you don't really know what I'm going through. But one of the good things about being um

Insider–Outsider Dynamics

Anthony 12:34

playing the outsider card is that subgroup are more likely to explain things in depth because they recognize that I don't experience those things, whereas an insider they would. But having that bias and how you play it can actually be really, really useful to how you do your research. So it's not all bad bias.

Stefan 12:53

Uh definitely. This is it, yeah. Not not all bias is bad. And it just comes back to that kind of notion of that's embedded within qualitative research, and I would argue research more broadly, um, but especially within quals, where who you are shapes the research you produce, right? Um, whether it's like you say Tony in the context of uh that kind of insider-outsider dichotomy, identifying where you are within that spectrum and recognizing that it is actually quite a spectrum, and you can put different hats on in different times, but also things down to things like race, gender, class, accent, all of this sort of stuff um really shapes the way that your participants will engage with you, right? I was sat with a student the other day who was uh preparing for their interviews, and we were kind of talking about uh particularly bias and the role of the researcher in the research. And I was saying, I was like, you could go and do these interviews, ask the exact same questions, um, and then I could go and do these interviews, ask the exact same questions, and we would be given quite different answers, or at least perhaps similar answers, shaped in different ways, right? Um people would be more willing to divulge particular information to you and then different information to me or shape it in different ways purely because of who we are sat opposite them, right? And uh, that is one of those dynamics of qual, which again, like you say, Tony, can be a little bit intimidating at first, particularly when we're trying to have that hat on of uh, oh, we can't be bringing in who we are, et cetera, et cetera. And it's at that point we realize that we can't completely stop that, right? Um, so yeah, I think the idea that who we are shapes the research that we produce is a really, really important thing to reflect on as well, in the context of quals, especially.

Anthony 15:01

Yeah, and I think that's it's spot on it. And I guess as well, it's it's that human element, isn't it, Stefan? It's you know, if you're going to observe humans and how they interact, you can't not be human yourself. You know, there has to be part of you in that in that research. And then I know students who are like, oh, well, if my participant says something and I really agree or I really disagree, I can't answer that, I can't say anything. It's like you can, like, that's part of a discussion, you're having that conversation. Um, so yeah, it is yeah, it's exciting, it is daunting, like you said there, Stefan. And I guess as well with qualitative stuff, there are different ways you go about it, and there are different little hats within that. I mean, obviously, in quantitative research, there are different ways you could analyze your data, but they're very procedural, whereas people could do interviews, and yes, we have like a semi-structured interview, we have a structured interview, an unstructured one, and there are guidance of how you would do that. But fundamentally, everybody is going to interview differently. Like me and you, Stefan, we could do, couldn't we? We could do semi-structured interviews. We're fully trained in qual, but we're gonna come at it ever so slightly different because, like you said, it's you as the researcher, it's that human element. So that can be scary, I think, for students where they're like there's no one full

Core Qualitative Methods Overview

Anthony 16:21

set procedure to follow. It's it's tweaks, its nuances. Um, do you think it's worth Stefan's just talking about kind of the the high-level kind of um instruments that students might use if they're doing qualitative?

Stefan 16:36

Absolutely. Um, yeah, so there's a bunch of different uh kind of research instruments or methods that we can draw on. Um interviews are some of the most common, right? And within interviews, you've got uh semi-structured interviews, probably being the most common sort of type there. Um but within that spectrum, you've got structured interviews, unstructured interviews, and then semi-structured interviews in between. But really, it is a huge spectrum between um those kind of positions, those those uh approaches. Um you've got ethnography, which is what I did for my PhD, alongside kind of ethnographic semi-structured interviews. Um, we've got discourse analysis, we've got some content analysis. Um ethnography is that kind of participant observation, right? Where we'll go into a research environment, be kind of very embedded, very involved, very um kind of situated within that that place with those people and observe, observe the um the kind of human interactions, the human behavior. Um, interviews where you're sat having a one-on-one uh conversation with someone. You can also do like dyads and triads before they formally become a focus group. Uh so dyads, one interviewer with two interviewees, and then triads, one interviewer with three interviewees. Um and then we do also have focus groups as well, which is where we get a group of people together to kind of talk through a topic themselves with the researcher asking those questions too. Discourse analysis can come in many different shapes and sizes. That's where we are perhaps analyzing texts or analyzing uh can be images as well, um, and kind of looking for meaning within perhaps uh kind of media excerpt excerpts or something like that. Um anything I've missed there, Tony?

Anthony 18:40

I think that's that's most of the key ones, I would say. Uh is content analysis as well, I guess, but that's very similar to discourse um where you're looking for how many times certain phrases or words appear in those texts or those conversations. Um, but yeah, it's and you know, we touched on before, like there you mentioned like observation, so you know that there's different ways you can go about that. Are you structured? So are you looking for individual things? Are you unstructured? And obviously, in future podcasts, um don't forget to check out our Moodle page as well under our qualitative section where we have more information on how to do these things. Um, but the good thing about qualitative is we can kind of tweak it to tailor it to our to our research, and what's quite useful about qual as well, and again, it does depend on your level of study for an undergraduate research. You probably only really have the word count and the time to do one of these things, so be that a semi-structured interview or to do some observations, but as you progress through your levels, particularly level seven, and then moving on to like PhD level, quite often having those different methods within qual is really really useful. So, what I found really useful in particular with my PhD was having those one-to-one interviews um with students and staff, and then observing them on field work and seeing, okay, did what they say in that room actually match up to reality? Um, and if it does, great because you've got that triangulation. If it doesn't, that's a really interesting discussion point to have. So, you know, as you progress through those levels, using these different flavours of qual helps you to explore that issue in a little bit more detail.

Stefan 20:21

Definitely, definitely, definitely. And then there's the whole conversation around mixed methods, right? Uh huh. Sometimes mixed methods will be used, other times they won't be. I think oftentimes students will say, Well, I'm gonna do mixed methods because I don't want to go all one way or the other. And then by the time they actually get to be doing their research, they have realized that actually it's better to do one in depth rather than two, and then not kind of doing justice to either. But there are particular situations where mixed methods research is absolutely the way forward, it's just much less often than what people initially assume.

Mixed Methods: Promise And Pitfalls

Anthony 21:01

Yes, yeah. Um, yeah, because I I would argue as a pragmatist that mixed methods is the way to go because you know quants giving me that broad view, quals giving me the detail, and I need both of them to really explore an issue in in depth. Um, and that's why that's why I'm a pragmatist, that's why I like to go between the two. Um, but yeah, a lot of students sometimes, particularly at level seven, have the opportunity to implement some you know um mixed methods stuff, but they do just feel like it's too daunting, it's it's too much, I can't do it. But if you have the time, you know, and it's part of the research you think is really, really useful, then yeah, you absolutely can use mixed methods. And again, some students think fall into a bit of the trap where they say, I'm using mixed methods, but really what they're using is a survey that then just has some open ended questions in. And that's a bit of a gray area in in in qual. So, like, yes, you are looking at words, but actually you're doing it much more through a quantitative thing. So You know, if you're using the server, it wouldn't necessarily say that you are a mixed methods researcher. So just be careful with that one.

Stefan 22:09

And I think that's it. It's like if if resource and time were were not an issue, then mixed methods would be the absolute best way every time, right? Um and if we can carve out the the time and also the word count for going into a mixed methods analysis, I think it's absolutely brilliant. Um I think the the issue is is when if students are working with a shorter dissertation, and as I say, in many cases, mixed methods will work very effectively if it can be done. It's that big if, right? Um, so I think if you're considering doing mixed methods, have a solid rationale for that rather than just thinking, well, I can't decide e whichever one, so I'm going to do both. It's better to come at mixed methods from a kind of actual research design perspective, like you say, Tony, particularly if you're thinking from a kind of pragmatist perspective, there's a very meaningful kind of philosophical rationale there for why that is the case. Um, but yeah, don't fall into the trap of just thinking, well, I kind of want a little bit of everything. So therefore I'm gonna do it. But I actually don't have the word count or the time to do it in in justice. What what what do you think to that?

Anthony 23:33

Yeah, I think for me, particularly for students, like when you're at PhD level, it's great because you've got a big word count, you've got a couple of years to do it. For your undergrad and your masters, um, and it's one reason again I I did quants for for both of undergrad and masters was because you know I had a set target, 150 responses for my survey, and I was like, I could get that. Um, and I think when you were trying to think of mixed methods, not only do you have to hit that big number of to make sure that your statistics are going to be viable, but then you mentioned the start, Stefan, you know, you maybe need five one-hour interviews. So to ask your student to go and get 150 responses and five one-hour interviews with participants, that's asking a lot, you know. Um even at PhD level, sometimes you know, they might have just eight in-depth interviews before they do all the other stuff. So, yeah, it it's you have to make sure it's sensible. And you know, as someone who and you're the same Stefan, we love research, and it's really hard sometimes to pull yourself back and realize that actually less is more in in research because as we've touched on for qualitative research, you know, you can interview five people and get a general gist maybe of where that's going, but then it's impractical to interview every single person ever, and even if you did, you'd probably get loads of different answers. There might be a common consensus, but you're never going to get to that one truth, so you have to pull it back a bit. I think that's really difficult. I mean, I say as a student, it's really difficult now as a researcher when we're writing papers and we're like, oh, we could do this or we could do that, and you know, and I look back at my papers, my research, and there are so many different ways I could have gone off stories I didn't tell in that final output because I just didn't have the word count, didn't have the time. Um, so yeah, it's yeah, it's it's keep it less is more, I think. And I think that's where quals sometimes can be quite useful, but there is that tendency, I think, to want to do more because you have less with it.

Stefan 25:37

Agreed, and I think that's gonna be a really interesting one to go into uh further down the line is that dealing with qual data when you've got this absolute ocean of words, these almost books and books and books of individual stories that all tell something really important, and you have to try and refine that down, and it comes with including some things and excluding others, and uh it's difficult, it's it's hard, but that's gonna be a great one to go into on in the future for sure.

Anthony 26:13

Yeah, so I I think yeah, I think we'll definitely do an episode uh on that, and I say with that, you know, thematic analysis springs to mind there. And I say on our Moodle page we have a little intro to thematic analysis about how you might start to kind of group those things into themes and how you might kind of pick apart. Um, but yeah, analysis is definitely for another day. Um, but yeah, it's um it's yeah, I'm just thinking of all the research I've

Scope, Word Count, And “Less Is More”

Anthony 26:40

done, and it's like, yeah, there's a lot um in there, but that's again it's useful and it's a tool. And you know, for me when I started off on that journey of qualitative research, it is scary, it is daunting, you know, and the fact I said there as a researcher, you play a really big part in qualm. So, you know, your ability to do those interviews well, those abilities to observe participants well, the ability to collect that information, the ability to sympath, synthesise it, that all comes down to you as a researcher. It's very much kind of you focused and your ability, and I think that's the scary part when you're like, I want to do it, but I don't know if I'm capable of, and you will be, but there's a help of the team, help of your supervisor, help of the materials, and you'll get there. And I say it's very easy for me and Stefan to talk about quals in a very nice way because we've done it for many years, and it that's the thing, it's the experience because quite often, throughout your schooling, potentially for your undergrad as well, quite often there's a very quantitative focus because it's relatively easy, I think, for some people to quantify and to understand. Qualitative is um in a little bit more depth, there's a little bit of nuances to it, um, and quite often, sometimes people only teach what they know, so you might only be um exposed to one type of qualitative thing, maybe an interview rather than a focus group or um an observation. So, yeah, if you were if you want to do qual and you're a little bit worried, come talk to the team. Say book a one-to-one uh with the team, check our Moodle resources, and we can kind of get you on the way. But we'll have a couple of more podcasts um come in for qualitative research where we'll focus on those different instruments and our analysis. But that's yeah, it'll be really, really good. So um I think that's a nice kind of intro to

Key Takeaways And Closing

Anthony 28:32

qualitative. I think the take-home message is if we wanted to still it down, if you want to look at a broad population and you you like numbers and you believe there's one truth, so you can get a yes or no answer, then quantitative nature is the way for you. If you feel like you want to get those nuances of people, you want to understand how things like you know, race, gender, how they grow up impacts what they say and why they say it, and you believe there are multiple right answers to a particular question, that qualitative is the way to go. Um, so thank you, Stefan, for coming on today to talk All Things Qualm. Thank you very much. And we will see you all again soon. Bye.

Analysis Teaser And Skills Building

Emma 29:13

If you're a University of Chester student, here are the ways you can access support from your academic skills team.

Student Support And How To Get Help

Anthony 29:20

On our Moodle pages, we've got lots of interactive resources for you to use. On our literacies Moodle page, you'll find help with a range of skills from academic rating to revision. On our Maths and Statistics Moodle pages, you'll find help with different statistical tests, calculations, and formulas.

Emma 29:37

You can also use our feed forward email assistance service. You can send 750 words, which is around three paragraphs of your work to ask at chester.ac.uk and we'll respond within three working days with generic and developmental advice on aspects such as paragraph structure, criticality, and referencing.

Anthony 29:57

You can also book a one-to-one with the Academic Skills Advisor via our Moodle pages. These appointments typically last 30 minutes and are available online and in person. Be able to see the campuses we're at by looking at our booking scheduler. You can send across an extract of your work for us to look at in preparation for the one-to-one. Or you can book a one-to-one to discuss a generic skill such as referencing or critical thinking.

Emma 30:21

If you and a group of your course mates are struggling with the same academic skill, you can book an Ask Together session by emailing ask at chester.ac.uk with details of your availability, how many people are in your group, what skills you want to cover, and where you'd like the session to take place.

Anthony 30:38

You can follow us on Instagram and Facebook using the handle ACEDSkills UOC, where we post practical tips on a range of academic skills, and it's also a great way to see what the team are up to.

Emma 30:50

And of course, you've got the skills pod. If you have a topic that you'd like us to cover or you'd like to be involved with our podcast, please email ask at chester.ac.ut.

Anthony 31:01

Ask.

Emma 31:02

Supporting your success.