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Dear students, welcome to our last encounter. Today we are going to end the module of qualitative
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research by discussing the way in which we will transcribe and present and write the data analysis
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part of our work, thesis, article or publication.
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Let me start by telling you what you will find of canvas. I kindly ask you to
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to read the article, the graphic transcript, and then you will also find an optional
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reading which is the handbook, the rules for transcribing conversation and interview,
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according to the rules of conversational analysis.
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Now we are touching a very important topic. We will talk today about the transcription of our data.
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You would probably have recorded or video recorded your interview with participants, or you may
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have, for instance, recorded a
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TV show, if you are analyzing some kind of video documents. Now, what you need to do before starting
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your data analysis, is to transcrib, the verbal accounts in a form that can be analyzed for
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instance, through software's, or, and manually can be shared and can be published on paper.
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So the transcription, of especially verbal interaction, is
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the very first important act of analysis. It's not just transcription, but it's already a
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methodological, and analytical choice. Of course, we can choose different strategies of
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transcription depending on our theoretical approach, depending on our research question and
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depending on the way we are going to analyze the data.
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Unfortunately, that's also the the hard side of doing qualitative research. When you collect data
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through qualitative method. You may gather a very rich material, because of course you often have
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multimodal kind of data, but also because you can very easily collect large amounts for instance of
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discorses
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and interviews. So it is very important that you make some choices before starting the
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transcription of your data, because this will be time-consuming. Will be a very hard work. Of
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course, there are different perspectives on transcription and I just give you two additional
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references if you may want to have
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a different look. So, what is transcription? Basically, transcription is not only the writing of the
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words that our participant told us, but is also an action in which we translate the
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the verbal, for instance, real account of our participant in a form that can be shared with other
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people that are not present at the interview and that can be analyzed by people that are
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different from the interviewer. In order to provide the information about the real person discorse
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We need, of course, not only to give the word.
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Just when we speak our the meaning of what we are saying depends also on the way we say it.
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The poses, the emphasis that we give, when we stress some word, when we do some particular gesture or
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where we look in a particular way the other person. So, all this information should be somehow
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reported in the transcription, because
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we need the other people to know even if they were not present. Here you can find the most common
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standard so far has been the Jeffersonian transcription system. Here you find a very
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simplified example of the system. So for instance, I can use some arrows
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to show, for instance that the pitch of my speech was going upward or downward. That I was
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speaking with faster, or I was speaking slower or that I was stressing some word or for instance,
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that my speech was overlapping with the speech of the other person or that I was making a pose of a
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certain duration. So all these small notation
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help us to read, to understand, how the person was really speaking even if we were not present.
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Here you can find a very short example of how we use these rules. So you see each line of the
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transcription is a number, has a number. So we can easily point to the transcription, and you can
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easily do this by using the Office Word
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function off line numbers. You don't have to do it yourself manually. So you see in this transcription of
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a dialogue there are a lot of signs in between. So the signs in brackets (.) show that there was a
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pause in the speech and the arrows say that there was some change in the pitch, some stressing when
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you see underlining. So I will read for you this example.
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to show you how I can understand the way it was spoken by the participants. Bria. Okay. So
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what do you think on a scale of 1 of 10 is the whole grace situation for you at the summer school
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right now. Devon. Well, like with one being handling it good or handling bed. Uh. Let's make one
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handling it bad than handling it
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excellently.
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Well, then it's probably somewhere between two and four. Yeah, that's was the kind of my impression
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in fact I'm not. Somewhere between two and four and half probably. So you see how I can get the
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moment in which people, for instance, where prolonging the sound to connect with the following
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utterance from the other person. So you
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see that I can have also a lot of information about the porosity for instance.
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But there are of course, other kind of transcriptions because here in the previous example,
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we were performing an analysis that was based only on what people said and some part of the
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verbal information. So for instance when people make a pause probably they're thinking. So we
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can get this information, but we may have a different
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approach to analysis. Where, for instance, we need to know, we need to analyze what people say,
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while they were are doing something. While they're performing some action. Here
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you see there is a transcription, which is telling us what the men operating the system is
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saying or is exchanging some
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information with another person while he is in front of this screen or of this
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desk, technology desk. So we can see that, for instance, he's looking in different directions while
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talking with the person. So we can see that he is referring to some object in the space so we can
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get this information. And here we have another
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example of transcript. So here for instance, the information that you need in our analysis is where
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people are. when they see something. iIn which moment they say something. Here there is a study
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about people cycling and they are speaking while cycling. So how we can convey this
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information. So the
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researcher here, choose to make this kind of comic or graphic transcription. So we can see how
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the people are, a and p they are speaking, they're having a dialogue and you see the
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position of each of the two while they're speaking, and the position along the road. So
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you can see that there are different way of transcribing depending on the different research
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question and the different approaches we are
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using. But also you can see that transcription is already a form of analysis, because we are already
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providing some interpretation and selection of the elements that are in the data. Now, I just give
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you some suggestions about how to concretely make a transcription step by step. Okay, let's imagine
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that you had an interview and you have the video or
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own recording of this interview. So the first thing you have to do is to familiarize with your
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data, because if you are the person that did the interview you were probably listening
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actively. You remember the active listing approach. So you are focused on the person, because you
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had the recording. So, you know that you can focus on the
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interaction with the person while your device is recording. So now you go back to your recording and
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you listen or watch a few times the whole recording. You have to become familiar with it. And you are
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taking notes of, already take notes of what you think maybe relevant. Some for instance special
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moment in which there was a silence or a special moment in which the participants were was showing
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some
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strong emotion to start watching and take notes. Then, of course, you may not want to
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transcribe everything because sometimes the qualitative data can be hours of interviews and it
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it can take months to transcribe all the data. So you can start making some selection of the
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piece of data that are more relevant for your research.
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And you can start transcribing those pieces, and then you will transcribe other pieces if you need
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them. So, once you have selected, let's say few minutes of an interview, then you start a first raw
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transcription. So what you first focus is the words. Sometimes it happens that some words
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are unclear. So in this very first raw transcription, you write down what you easily understand.
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And leave some blank spaces if there are words that you don't understand and you do this repeat
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the step three for two or three times until you are satisfied with the transcription. Until you
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you think you really got all the possible words that can be there. Or maybe
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you had some ambiguous word, that you're not really sure what they
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say, so you listen two or three times until you are completely satisfied. Then you start the
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second round of transcription. I mean so far you focused on the word. Now you focus on the non-verbal
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or the para-verbal. So for instance, you start adding all the notations like in the
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Jeffersonian system. So pauses, the change of tones, the overlapping between
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the two people interacting. And again, you repeat step 5 as many times as you are
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satisfied with the transcription.
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Then you pass to the to the non-verbal, in case for instance you have a video recording. You may be
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interested also in gestures or gazes. So you repeat the same process of listening or
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watching over and over again until you are satisfied with transcription. Finally, when you have this
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transcription, full transcription, you can add
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your observation. Because on the field you may have done some notes, you may remember from the
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interview some specific information that can be added as comment to the transcription. So this is
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the step by step process. Now we touch the last point. Once we have transcribed our
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data, once we have analyzed our data with the strategies. Like we discuss in the previous lecture.
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Now is
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it's time to present our data. So we are now in the phase of writing our data analysis chapter or
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our data analysis section in an article. I will give you here some hints, some
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tips about the process of writing. So first of all, the very important thing you have to decide
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what is your message. As we say it, the
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data analysis is the way we improve knowledge by looking at the empirical data through the lenses of
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our theories. So we are analyzing data to learn something. The structure of data presentation is
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always the same. So you start by introducing and summarizing the content of your data analysis
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chapter, and then you start presenting your analysis. Which always has
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to be structure in the following way. The data analysis is functional to illustrate or to
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justify your theoretical argument. So you start with your theoretical argument. Then you present
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your data and then you close with commenting about your theoretical article. Sorry your data
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analysis. Then at the end of the data analysis section you summarize what we have
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learned from your analysis. And of course if it's a chapter of your master thesis, you connect the
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introduction, and the end with the previous and following chapters. If it's an article, scientific
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article, you do the same. But the idea is always that your data analysis is somehow in the flow and
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consistent with the rest of the discourse.
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Now, just to elaborate a little bit. So here is an example of how you structure your data
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analysis presentation, according to the structure I gave you before. So you start by, you
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open the chapter or the section with the theoretical
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argument cites theory. So you start, again you take back the theory that you have discussed
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previously and you briefly summarize your theoretical argument. Then you present your data analysis.
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So you use the theory to analyze your data and then you have to present the conclusion of
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your of
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analysis. So what you have learned from the analysis. This is the general structure of the data
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analysis writing. Again, this applies both to quantitative and qualitative kind of analysis.
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An example of
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So you see that we somehow are discussing the way you can convince or justify your ideas through
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your empirical data. And this way of writing the result of your analysis, that's very
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important, applies to any kind of work you want to do.
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Doesn't matter if it's quantitative, qualitative or theoretical or mixed methods. So the structure
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of theoretical argument, data analysis and justification of the theoretical argument is always the
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same. What changes is the kind of data and the way of presenting the data that you have. For
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instance, in quantitative work the kind of data that you may have analyzed, the analysis of your
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data can be done, of course, mainly in figures
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and tables. If you have a qualitative kind of analysis, you probably will use tables. Like, for
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instance, if you show your coding your categories, or usually you show excerpts. It means short
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sentences from the interviews to justify your analysis. If you are doing instead of theoretical
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analysis, like a review literature, you can use
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as your data, you represent your data in the form of the arguments, like the articles by Brown (1975)
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write this, this and this citations or you can have a mixed method study in this
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case you will have a combination of this kind of data presentation. But the principle to follow is
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always the same. Every time you say something
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in a scientific writing, in academic writing, every statement, every claim that you made, must always
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be justified and you can justify it in two ways. You can justify to literature. So your
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claim is supported by the literature or is supported by your data analysis. So this is at the level
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of structure. Now,
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we see how practically you can present every claim or every statement you make into the data analysis
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and I will present you different examples. Examples of a quantitative data presentation, qualitative
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and theoretical data presentation.
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Here an example of how you write a quantitative study. Actually, these are examples from real
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articles. So published articles. So you see in a quantitative study you first present your
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statement. In this case within classroom levels for reading
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and math skills are significantly different,
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between classroom. This is the statement that you are making, the claim thar you're making.
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How you justify this claim? By the data. So you present, in this case, the percentages and the
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significance test. The level of significant test in the data and then you comment the data. So how
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these results are actually justifying your initial claim. So that's a case of quantitative
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study. Let's move to a qualitative study, is exactly the same. You have a claim, an initial claim, so
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that the multidisciplinarity and multi-professionality are embedded in teachers meeting.
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Here,
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you have the data analysis, in this case the data analysis is the data that you present to justify
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your statement are short quotes from the interviews. I didn't report it here, but you can see after
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answer one and nine. So it means that I have reported word of the mother in this case.
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And then you comment on the data. So what is the meaning of this
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these results of the example you present for to justify your initial claim. And finally, you do
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exactly the same in a theoretical study. So in a theoretical study, you present your
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statement. In this case, the data that you use to justify your claim, are other articles, other
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literature, because it's a theoretical article and then you comment the data and you justify your
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statement or your conclusion.
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In this case Caravaggio' seemed to paint from live models, but the solution
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that painter was adopted was completely different. So
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justification of the theory I can make a final claim. So the structure of presenting your data
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analysis is always the same and your data analysis chapter will be a sequence of this
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ternary structure for each of the
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claim, each of the points, that you want to make. Finally. Now. Let's go back to our reading, just give
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you some orientations about how to read today pensum. So the article about the graphic transcript is
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presenting the very different ways in which you can describe your data. This is
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Treffsikkerhet: 79% (H?Y)
00:25:02.949 --> 00:25:10.300
important because the transcription process and specially when you are writing an academic article
00:25:10.300 --> 00:25:19.600
or a thesis is not only about an analysis, is about making your analysis visible to another person and
00:25:19.600 --> 00:25:26.900
making another person understand your analysis and agree with your analysis.
NOTE
Treffsikkerhet: 91% (H?Y)
00:25:27.000 --> 00:25:33.300
So what are the key concepts of this article? The first one is the article stresses the importance
00:25:33.300 --> 00:25:40.700
of multimodal communication. As we said verbal communication and verbal transcripts are only a
00:25:40.700 --> 00:25:47.200
small part of the phenomena we observe and qualitative research is very helpful because can
00:25:47.200 --> 00:25:53.900
give you the whole of the communication interaction situation. The second point, very important
00:25:53.900 --> 00:25:57.100
point. Is that all phenomena take place
NOTE
Treffsikkerhet: 86% (H?Y)
00:25:57.100 --> 00:26:08.900
in a space-time. So the same sentence by participants can have a completely different meaning
00:26:08.900 --> 00:26:17.000
if it's uttered in a specific space-time situation. So we must also be able to make
00:26:17.000 --> 00:26:19.699
visible the space-time dimension.
NOTE
Treffsikkerhet: 70% (MEDIUM)
00:26:19.699 --> 00:26:27.000
Another problem, which is related to the transcription and in which some creativity
00:26:27.000 --> 00:26:32.700
is important, is the ethics and privacy. So for instance, when we work with children, we cannot show
00:26:32.700 --> 00:26:40.300
the faces of children. So, how we can, for instance, in my analysis is very important the kind of
00:26:40.300 --> 00:26:48.000
gesture that the child is making while speaking. Okay, so how I can show the gesture without
00:26:48.000 --> 00:26:49.949
showing the actual child.
NOTE
Treffsikkerhet: 86% (H?Y)
00:26:49.949 --> 00:26:57.100
And in this article you can find a lot of very interesting examples, solutions. And again, the point
00:26:57.100 --> 00:27:05.100s
is that you must be creative in every step of the research. Being creative is not the opposite of
00:27:05.100 --> 00:27:13.900
being rigorous or of being scientific. But is part of the scientific process itself. And finally, as
00:27:13.900 --> 00:27:19.600
I said in this article, you will find a lot of very useful practical example, that
00:27:19.600 --> 00:27:19.950
you
NOTE
Treffsikkerhet: 91% (H?Y)
00:27:19.950 --> 00:27:28.650
can to apply to your future researches. So I think that we came to the end of this
00:27:28.650 --> 00:27:35.150
qualitative research module. I hope that you enjoyed. I hope that you found it interesting.
00:27:35.150 --> 00:27:42.900
And of course we will have the opportunity to continue the discussion in the lectures, but also on
00:27:42.900 --> 00:27:48.949
the online forum. So thank you very much for your attention and wish you the best for your studies.
00:27:48.949 --> 00:27:50.400
Bye.