Transcript of Research paradigms explained: positivism, interpretivism & critical realism

We need to have a little chat about  paradigms. Now, stay with me because   they're not that scary. A lot of people feel quite  intimidated by them, quite freaked out by them,   but there's no getting away from it. If you are  doing a PhD, you need to know your stuff when it   comes to paradigms. And it's actually a lot easier  than you might think. I'm Dr. Elizabeth Yardley,   and I've been supporting graduate students for  the last 20 years. Paradigms are one of the things   that students have asked me about and continue  to ask me about year after year. Unfortunately,   a lot of the academic textbooks on the topic  are completely impenetrable and full of jargon,   and they can make you feel like you are  never going to get your head around this   stuff. But you are, and we're going  to start that process today. So let's   begin by figuring out what on Earth  that term "Paradigm" actually means. Well, I like to think about a paradigm like a kind  of research culture where you've got a particular   way of thinking about research. You've got a set  of values and beliefs about what research should   do, what questions it should ask, what questions  it should answer, and how that research should   actually be conducted. How should you actually  do the research? And I like to use the analogy of   cliques in high school to make sense of some of  the paradigms that you might come across in the   social sciences. In the same way that every high  school is going to have different cliques of kids   – the Goths, the science nerds, the gamers,  the jocks, the social justice activist kids,   etc. – social science has different cliques  as well, different cliques of researchers.   And they all have their own unique culture  and their own unique way of doing things. I like the high school analogy because it  doesn't position these cliques or these groups   of researchers as being completely closed off from  each other. In the same way that the gamers and   the jocks at high school have something in common  – so they play games that follow rules – social   science researchers will have things in common  as well with researchers who belong to different   paradigms. So whether someone's a positivist, an  interpretivist, a critical realist, they will have   things in common with the other paradigms. Most  obviously, they're all interested in understanding   and explaining what goes on in the social world,  but they will go about that in slightly different   ways. The research that they do, the research  that they value, the research that they think is   important, is all going to look quite different  depending on what paradigm they belong to. Now, I mentioned three paradigms just  then: the positivist, the interpretivist,   and the critical realists. So let's  take a closer look at them. Now,   I want to give you some really basic metaphors  for these paradigms, and we're going to stick with   that idea of the high school cliques because I  think that makes them so much easier to remember,   and it helps you to recall the particular  features and the particular characteristics   of them. Paradigm purists are probably going to  be all over me in the comments for doing this,   but I don't care – bring it on, because this whole  paradigm thing has become quite impenetrable,   quite difficult to get our head around, and  I think we just need to start somewhere,   and the simpler we can make it, the  better. So knock yourselves out. Let's look at the positivist first. We'll use  the clique of the high school science geeks to   represent positivism. Positivists believe in hard  facts, quantifiable data, and objective truth.   They're all about measuring and predicting, a  bit like scientists in a lab. They take their   cue from how natural science has made sense of the  physical world, and they believe that we can take   inspiration from that to make sense of the social  world using similar principles and approaches. Next up, the interpretivists. They're a bit like  the artsy, creative clique of high school kids.   They focus on people's stories, meanings,  and subjective experiences. They're all   about understanding the drama of human life,  the richness and the complexity of the human   experience, and they really value the different  perspectives that people bring. They don't think   that you can detach from the world that you're  studying to the same extent that positivists   do because you, as a researcher, you are  ultimately part of the world that you're   doing research within. So you can't just stand  back and be a detached, objective observer. Lastly, we have the critical realists. We're going  to use the high school clique of the activist   kids, the social justice warriors, to represent  the critical realists. Critical realists dig   beneath the surface to uncover the mechanisms and  the structures that shape our social world. They   blend elements of positivism and interpretivism  while championing social justice. So they are   super interested in the lived realities and the  experiences of individual people, just like the   interpretivists are, but they think we should  situate that within the broader context of the   overarching social structures that we have around  us – like the economy, the political system,   religion, education – to understand how particular  people come to have specific experiences. So now we know a little bit about each of those  paradigms. What I want to do now is show you an   example study and think about the different  ways in which the different researchers from   these three different paradigms might approach  this study. What kind of things might they look   at? What kind of things might they not look  at? What is the aim of doing the research   in the first place? And how is it going to vary  depending on what paradigm they're coming from? The working title of our study is "High School  Students' Use of AI in Assignments." Let's see   how that study might pan out when it's undertaken  by researchers from the different paradigms. First up, a positivist study. Now remember,  the positivists are the science geeks who   are all about hard facts, quantifiable data,  measuring, and predicting, like scientists in   a lab. So they might title this research "The  Impact of Artificial Intelligence Integration   on Academic Performance: A Quantitative Study  of High School Students." And the focus of this   study would be on assessing the impact of AI on  academic performance among high school students. When we look at the objectives of a positivist  study, it might be to quantify AI usage patterns,   to measure academic performance outcomes,  and to identify links, relationships,   and correlations between AI usage and academic  achievement. The sample that they might select   would be a random selection of high school  students from multiple schools. And how they   go about collecting data in this study might be  something like a survey administered to students   to collect quantitative data, quantifiable  data on AI usage patterns. They might also   be interested in self-reported academic  performance and demographic information.   So pieces of data that are quite easy to  quantify, quite easy to number crunch. When it comes to data analysis in this study,  it's probably going to be along the lines   of some statistical analyses, so things like  descriptive statistics, correlation analysis,   regression analysis, because the positivists are  interested in looking at relationships between AI   usage and academic performance outcomes. Those are  the two variables in this study. And zooming out   to think about the bigger picture, they would be  interested in the implications of their findings   for educational policy and practice. So, the  positivist researchers here would focus on   observable facts and measurable data. They gather  quantifiable information about how students are   actually using AI tools, and they'd analyze  this data systematically. And as positivists,   they would aim to identify patterns or rules that  govern students' behavior when they using AI,   such as how often they use AI tools, what  kind of assignments they use them for,   and whether their academic performance changes as  a result of using them. By closely observing and   measuring these factors, positivist researchers  believe that they are going to generate some   reliable data about how students are using AI and  how that impacts upon their academic performance. Next up, let's take a look at an interpretivist  study on the same topic. Now remember,   the interpretivists are the artsy, creative types.  They focus on people's stories, their meanings,   and their subjective experiences. So, the title  that we might come across in an interpretive study   on this topic might be "Exploring High School  Students' Perceptions and Experiences with AI   in Assignments: A Qualitative Inquiry."  So, the focus of this study would be on   understanding the meanings that high school  students give to using AI in assignments. It   would focus on looking at how high school students  interpret AI and how it should be used by them. And the objectives of the study are going  to be around exploring students' perceptions   and attitudes and experiences related to  how they're using AI in assignments. So,   it's looking at how they feel  about it, what they think about it,   what they believe about it. And in terms  of the sample for this piece of work,   it might be purposive sampling of students  from a diverse range of backgrounds. Turning to look at data collection, it's  likely to be something along the lines of   in-depth interviews and focus group discussions  to explore students' perceptions and attitudes   and experiences with AI tools in assignments.  And when it comes to analyzing that data,   it might be something like thematic analysis  of the interview transcripts. And what the   researchers would be trying to do there  would be to identify recurring themes   and patterns in the students' narratives,  in the stories that they told about AI. So, the researchers are going to be interested  in describing students' perceptions and attitudes   towards AI tech and exploring their experiences  of using this particular tech in assignments. So,   we're going to end up with an identification of  themes that perhaps relate to the benefits or   the challenges or the ethical considerations  of using AI in education. And in terms of   zooming out to think about the bigger picture  here, when we're looking at a discussion,   we're looking at the implications for educational  practice, we're looking at what recommendations   could be made for supporting students  as they engage with AI technologies. So, this study from an interpretivist  perspective is going to focus on   students' subjective experiences of using  AI tools. Instead of just using measurable,   observable data like the positivists would do,  an interpretivist study is going to be interested   in exploring the meanings and the motivations of  students who are using AI for their assignments.   They'd use qualitative research methods to  enable them to dive into the complexities of   how students perceive AI, of how students make  sense of AI when it comes to their assignments,   by uncovering the underlying meanings and  the social processes that shape students'   interactions with AI. Interpretivist  researchers are essentially aiming to   get a richer understanding of the impact  of AI on students' academic experiences. Lastly, let's take a look at a critical  realist study on the same topic. Now,   thinking back to the high school cliques,  remember, the critical realists are the   activist kids. They are the social  justice warriors, and they dig beneath   the surface to uncover those deeper structures of  mechanisms that underpin our lived experiences. So, a title of a critical realist study  in this area might go something like this:   "Uncovering Mechanisms of AI Adoption  Among High School Students: A Mixed   Method Study." The focus of this study would  be on uncovering those underlying mechanisms   and those structures that influence high  school students' use of AI in assignments. So, the objectives are to identify those  contextual factors, those social mechanisms,   as well as the individual choices that  shape students' engagement with AI. So,   the type of research study they do would  likely be a mixed methods approach, with   a combination of qualitative and quantitative data  collection. So, on the qualitative side of things,   there might be semi-structured interviews  and observations to kind of explore students'   experiences and interactions with AI. And  that would then be paired with a quantitative   arm of the research as well, which might be  something like a survey to look at AI usage   patterns and attitudes and perceptions  among the high school students about it. And when it comes to analysis, there'd be  an integration of the qualitative and the   quantitative data to uncover any patterns,  any mechanisms, any contextual factors,   to put all of the pieces together, essentially,  and look at what is going on when it comes to AI   usage among high school students. How is it an  individual thing? How is it a social, cultural   thing? How do all of those factors come together  to create particular situations and experiences? So, there's a desire to identify those underlying  mechanisms, those underlying structures that shape   students' adoption of AI in assignments. So,  we've got the analysis of contextual factors,   like the school culture, and maybe things like  teacher support. And we're looking at how those   might influence AI usage. But a critical realist  study would also be looking at individual choices,   student decision-making, how they actually go  about handling this on an individual basis,   and what some of those processes around that are. And zooming out to look at the discussion, look  at the "so what" question, we'd be concerned   with implications for educational policy  and practice, as has been the case with   the other approaches. But from a critical realist  angle, there'd probably be a focus on addressing   the structural barriers and promoting  equitable access to AI technologies. So,   critical realists wouldn't just be  looking at the things that we can see,   the things that we can actually  observe, like how often students   use AI and that kind of thing. But we'd also  be looking at what is going on underneath,   what is going on underneath the surface. So,  those causal mechanisms, those structures,   those inequalities that might be driving students  to actually use this tech in the first place. And the critical realists would be taking  into account factors like school policies,   teacher attitudes, socioeconomic  backgrounds, and cultural influences,   which might impact on how students engage with  AI. All critical realists would be interested   in power dynamics and social justice. They'd  be considering how access to AI, for example,   might be influenced by things like poverty and  inequality. By acknowledging the importance of   what we can see and what we can't see, the  critical realists are essentially aiming   to come up with a holistic understanding of  students' experiences with AI technologies. So, they're motivated by a commitment  to address the underlying structures of   oppression and inequality that exist in the  world. And they're aiming to use the research   findings to advocate for social change and  to promote greater equity in education. To recap, in this video, I've introduced you  to the topic of paradigms in social research,   a subject that has many graduate students  scratching their heads. We've compared   paradigms to high school cliques, each of  which have their own culture and beliefs   and approaches when it comes to doing  research. And we've looked at three   social science paradigms: positivism,  interpretivism, and critical realism. These are just three of the social  science research paradigms but   hopefully now you know a little bit more  about them you feel a bit more confident   in your knowledge of them and you're  in a position where you can actually   start thinking about where you might  sit in terms of a research paradigm. If you found this video helpful give it  a thumbs up, if you've got any questions   drop them in the comments and I'll be  back soon with more tips and advice   on navigating the messy and the magical  of the PhD journey - I'll see you then!