 Hello, I welcome you all once again to my channel Explore Education and I am Dr. Rashmi Singh, Assistant Professor, Department of Education, S.S. Khanagal's Recoil University of Allahabad and today I am going to discuss a very interesting topic under qualitative research that is triangulation. What is triangulation in qualitative research? We will go to discuss and this lecture will be in bilingual mode as usual and it will be useful for your research purposes and for your education, examinations, various competitive teaching examinations too. Okay, so let's start. First of all, triangulation. The role of triangulation in qualitative research is very important and it is very interesting to know. What is triangulation? Why do we need to study it? What are the benefits of using it in qualitative research? So, data triangulation in qualitative research is used as means to make sure that the research is. In qualitative research, we need to make sure that the data triangulation is accurate. Why do we need to make sure that the research is fluent, robust, comprehensive or well developed? Why do we need to talk about all this because all these things are connected with qualitative research. That it is not fluent, robust, or well developed. Why? Because when qualitative research is done, when it comes to literature, it is the talk of quantitative research. It is a talk of logical possibilities, it is a talk of systematic analysis, statistical analysis, statistics and overall. It is a talk of generalization, prediction, etc. At that time, if you take different approaches, it is necessary to be pretty. That is why you need to prove qualitative research again and again. If you do this and that, then you are also credible, we are also credible. We also have the knowledge of yoga. That is why we are doing all these things, studying qualitative research. You can also say that it is fluent, robust, well developed, well developed, well developed. Translation refers to use of multiple methods or data sources in qualitative research to develop a comprehensive understanding of phenomena. What do we want to do in qualitative research? There is no phenomena that we want to do. There is no experience that we want to do. There is no insight that we want to explore. So, translation means that we have to use a lot of methods and methods to understand data. That is why we have done a lot of business for this. Translation also has been used as a qualitative research strategy to test validity through the convergence of information from different sources. You can use this strategy to test validity through various sources. Sorry. If you seek information, you can see that our result is very different. What is rational? What is logic behind it? The basic idea behind this or the rational for using this approach is that one can be more confident and can increase the credibility and validity of the findings when different methods are the same. You can be wrong. You can be wrong in your way. You can be wrong in your interpretation. But when a lot of people are reaching that result, a lot of ways are reaching that result. A lot of data is the same thing. This means that our truth value increases. Our finding and our finding validity increases. This is the question behind this. Because this has been said in qualitative research that you will not be in the film. You will be in the film with your own mind. What is the end of the story? If you have an insight, then my insight can also be there. So, what was necessary that we go to the film. We write a story with our mind and sit at home to research. In this way, you can say that So, we feel that... So, we are saying that we are also reaching there, someone else is also reaching there. Someone is reaching there. A, B, C, D, everyone is reaching there. We are collecting data in many ways. For example, we are doing interviews, we are doing FGDB, we have done participant observation, we have recorded a clip, we have done some content analysis of a book. If we are doing so much work, then we are getting the same result. This means that you can say that the result is its credibility and its findings are valid. This is the rationale behind it. When I applied to qualitative research, this method may be defined as an attempt to map out and explain fully the richness and complexity of human behavior by studying it from a more than one standpoint. No, we will see it from one perspective. If we are seeing it from many perspectives, we are getting the same result. This means that we can explain our findings with more richness and its credibility and validity will no doubt increase. Types. They have told us that there are 4 types of triangulation. I will tell you in 5 episodes later. But in general, if you search, in books, in your literature, you will find these 4 types of triangulation. What are they? Method triangulation, investigator triangulation, theory triangulation and data source triangulation. These are the 4 main methods in which we can do the triangulation of our research. We will apply a lot of methods like the method triangulation. Okay. In investigator triangulation, we will do a lot of research. We will investigate. In theory triangulation, we will see a lot of theoretical points in our research. And in data source triangulation, we will use a lot of methods of data collection. This is its source. In method triangulation, it means using different methodologies to approach the same topic. To approach the same topic, we will use a lot of methodologies. This is the most common type of triangulation in research. So, often combining qualitative and quantitative research methods in a single stream. See, it is said that there is nothing quantitative in this. You have not put any stats or anything. So, we can say that we are doing a mixed method. There is no hurry. We have done qualitatively and then we have done something quantitatively. So, we will use a lot of methods. So, triangulation and triangulation will be done. It is useful because you avoid the flaws and biases that come with reliance on a single research technique. Both of them have some shortcomings. So, if we take both of them, we will take the good ones. So, our research will become better. So, this is method triangulation. What is theory triangulation? Using varying theoretical perspectives in your research. Unlike investigator triangulation, this method typically entails using professionals outside of your field of study. So, what we will do in this? We will see a lot of scientific aspects of our research. So, a lot of science can be a science of psychology. It can be a science of sociology. It can be a science of education. It can be a science of theory. And if we reach there from every angle, this means that our research, our finding, it has a lot of logic. It is not logical. We have not written it from our own mind. We have gone there. We have done our work. Why? Because all the theories are coming to the end. So, unlike investigator triangulation, what happens in investigator triangulation is that we say to some other researcher, you also see the data. You also see the data. You also see the data. So, a lot of people work on it. They have discussions and negotiations. So, these things come out. But in theory triangulation, we say that we need professionals outside of our field of study. We need psychologists, we need sociologists, we need educationists, whatever we feel, we also need that. So, that is why theory triangulation is different from investigator triangulation. Then, what is investigator triangulation? It involves multiple researchers. We will not only study the data. We will also study it from other researchers who are working on qualitative research. So, it involves multiple researchers in collecting and analyzing data. I mean, we will also help them in collecting and analyzing data. The findings from each evaluator would be compared. Everyone's finding would be compared. If the findings from the different evaluators arrive at the same conclusion, then validity has been established. If a lot of evaluators are coming at the same level, we will say that our research finding is valid. It has been done correctly. And data source triangulation using data from different time spaces and people. We are taking data from people for a long time. And even then, if we reach the same conclusion, it means that it is correct. Environmental triangulation is not mentioned in the denzine or pattern. And it is not available everywhere. But you should also know this. What is this? This type of triangulation involves the use of different locations. We have changed the environment. We use many types of environments. For example, in data, in data, in investigators, in environmental triangulation, we will study the environment or find it. We will investigate it. So, use of different locations, settings and other key factors related to the environment. We are changing the factors related to environment. In which this study took place. Such as time of the day, day of the week or season of the year. We are changing the weather. We are changing the day of the week. We are changing the weather. If all the environments factor on this study, then the use of environmental triangulation is limited only to those studies where the findings can be influenced by a certain environmental factor. So, only in those studies will this work where our data is really affecting the environment. For example, mood. How is someone's morning and evening mood? How is the mood at night? How is the mood at night? It depends on this. Often, during the evening, we feel very lonely. The time when the evening and night are connected, you will often see that people feel very lonely at that time. At that time, no one feels at ease. And in the morning, we often feel sad. Our mind is happy. Something is going wrong at night. So, in the morning, when someone wakes up from a fresh mood, we are going to do such a study and we are taking data that is affecting time. So, this is environmental triangulation. I mean, we will change it and see whether we are reaching the right conclusion. So, the environmental factor is changed to see if the findings are the same. If the environmental factor is also changing, even then, if the same thing is happening, if the same thing is happening, that means we can say that our data is right. If the findings remain the same under varying environmental conditions, then validity has been established. And if the different changes are taking place under different conditions, even then, if the findings remain the same, then we can say that this is a bad thing. Isn't it? Then, challenges. Looking at it, it feels very good that we have taken a lot of data from many places. We have worked with many investigators. We have put a lot of methods and theories and then, everything is going perfectly. That means there is a very good result. But, what is the problem? The amount of additional time is different. For example, qualitative research is taking time. It is consuming time. You need to work with different investigators. You need to take a lot of data. You need to apply many methods. You will definitely have a constraint of time. You need a lot of time to do it. The complexities of dealing with large quantities of data are the most difficult qualitative research on data. You have so much data like transcripts, recorded lecture, you have noted every detail. how to make it a category, how to code it, how to do content analysis, how to submit it, how to reduce it, we have so much of it. This is the biggest difficulty. Now a lot of software has arrived and a lot of people are doing all this with the computer. But there are still a lot of things in the computer that are shortcoming, right? You can't see everything from there. You have noted it, you have seen the expression, you have seen the gesture. So you can't take the help of the computer in everything. And all of them are not so technosavvy and the usage of the computer is not so much in qualitative research. So the potential conflicts between different investigators. Oh my God, this is the most difficult. You are an investigator and the second investigator. Everyone has subjectivity. The issue of intersubjectivity is how to believe that data is saying the same thing. But the investigator is not getting one. So how to deal with this conflict, how to deal with this challenge. Theories, hypothesis and or methods, the difficulties of interpretation when data do not converge into a clean, clear picture. You are saying that data has come out that someone is showing another picture to the same data. Someone is showing another picture of another investigator. Because the subjectivity is involved, your self-involved, your past experiences are involved. So how to make a clear picture. And limited understanding among policy decision makers about how triangulation works and why it was used in a given situation. And until now, there is no such understanding that we will take this, we will do this in such a way. We will do data triangulation, we will do method triangulation, we will do everything. No matter how much we do, there are no decisions and policy makers on this. So this is also a very big challenge. So there are challenges like this. But if you do one, two data triangulation or investigator triangulation, then your result will increase its validity, its credibility, its value. This is a very interesting topic for qualitative researchers. So, sorry, I have completed one more important interesting phenomena and strategy topic under qualitative research methodology. That is triangulation of data or triangulation of method or self-triangulation. Okay, so thank you and don't forget to like and subscribe my channel, explore education, and join my telegram group too. Then traumatize it.