Avoid These 3 Qualitative Dissertation Mistakes (Full Transcript)

[00:00:00] Speaker 1: I've been supporting students for many years, and especially those who are working on their qualitative dissertation. So there are three mistakes that I have identified that I want to share with you. And if you are a doctoral student, please pay attention to these mistakes so that you will not repeat them. So one of the mistakes is having too many research questions. So in qualitative study, you always want to focus on exploring a specific phenomenon and you want to go deep, right? So having a lot of research questions can be overwhelming because first, you have to collect rich information from participants to address these questions. And then secondly, you have to make sure that you develop themes for all your research questions. So it's going to take you a long time, resources, and data to help you to address your research questions. So it's very important for you to pay attention to the number of research questions that you have. And about one to three research questions for a dissertation is very good. It gives you the time and resources for you to address them in an efficient and adequate manner. So if you have many research questions, this is what you have to think about. You have to explore what is the purpose of your study, right? And then make sure that your research questions are consistent with the purpose of the study or the objective of the study. So it's very important for you to have less research questions so that you will not be overwhelmed in terms of addressing each of them. Imagine you have about 10 research questions, and then you have to go to the data and develop themes to address all these questions. And let's say four themes for each of your 10 research questions. This means that when you are presenting your findings, we're going to talk about 40 themes. It's too much for even your audience to consume your information. Having about one to three research questions is very good for a dissertation. So that you will not be overwhelmed, right? So the second mistake is learning about a software that you want to use at the same time analyzing your qualitative data, right? If you are doing these two things at the same time, it's going to be challenging, and you'll be frustrated because you have a lot of document to analyze, and at the same time, you are also learning about a software. So my recommendation is that before you collect your data, you have to start thinking about the software that you want to use to analyze your data. I have a lot of videos about In Vivo, Deduze, Atlastia. When you go to my channel, I have all these videos. Just explore them and choose the one that you think will be helpful for you to help you to analyze your data. So deciding on the qualitative software that you have to use at the earlier stage before even you collect your data is very important, and then you start learning about it. And I hope my videos will be very helpful for you to learn about all of them. And if you want me to help you to learn, you can also book an appointment with me, and I put my information in the description section there so that you'll be able to get access to the information, and then you'll be able to meet me and have a discussion about the right software that you want to use for your analysis, and also how to use it to make sense of your data. The last one, which is the third mistake, is instead of you addressing your research question, you are analyzing your data to address your interview questions. The essence of having interview questions is to help you to gather rich information from participants. After you have gathered rich information from participants, then you have to move to the next stage where you're going to use the data to address your research question, not the interview questions, right? It's very important for you to think about that. If you don't have your research question, you can use the data to address your research objectives, right? Imagine that you have maybe 20 interview questions, and then you're going to go to the data to address these 20 query search questions. It's going to be a lot for you to do, and also in terms of even presenting the findings, it's going to be a lot for your audience to consume because qualitative data analysis is about data reduction. You want to reduce the data so that it can be easily consumed by your audience. Make sure that you are analyzing the data to address your research question. If you don't have research question, you can create one based on the objectives or based on the purpose of the study. Sometimes you may identify information that you think is so important for you to code, right? But it's not addressing any of your research question. Yes, you can still code the data and then separate them from the research question and put them under a concept, or if you are using maybe InVigor or MassQDA, you can put them under a parent code called Other Findings, and then you can analyze that information data, especially if you think the other information that might not directly address the research question will help your audience to understand the findings, then it makes sense to sometimes code that information, right? But when you are analyzing the data, your responsibility is to address your research question. I hope this one was helpful for you. If you have any questions, you can put in the comment section and I'll be happy to address them for you. Don't forget to subscribe to my channel. More will be coming soon. Thank you.