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- 1. Qualitative Analysis PE701
- 2. Methods of Data Collection • Questionnaires • Interviews/focus groups – Via email, face-to face • Observations • Documentary Analysis • Individual narrative • Web debates – possible that this may be considered documentary analysis, but equally could be interactive
- 3. Data Generated Transcripts Field notes
- 4. Analysis • Reading and organising • Emergent themes – reading and coding • Consideration for literature in the area and the theoretical framework of the study - interpretation • Themes and categories re- visited - interpretation – Continual note- taking/annotation throughout the process
- 5. Ontological and Epistemological positions and their relationship to qualitative different methods of analysis Naive Radical realist relativist Grounded Grounded theory theory (Social constructionist Discursive (realist version) Psychology version) Case studies Interpretive Phenomenological Analysis (IPA) Adapted from Willig (2001) Foucauldian Discourse Analysis
- 7. Checking Your Analysis • Member validation • Alternative explanations • Audit trail • Critical reflection
- 8. Task • Read the papers: – Smith and Parr (2007) – Nicholls, Holt and Polman (2005) • Check how the methods section is written • Consider the way that the findings are presented in their ‘themes’ and how data is quoted within this. • Focus on trying to identify the differences between the sociology paper and the psychology paper.
Notes de l'éditeur
- Having looked at some of the qualitative research methods last week, we are going to consider what to do with the data once we have collected it this week. This lecture will include a broad introduction to qualitative data analysis – we will also highlight some difference between carrying out analysis in sports psychology and the sociology of sport. As your task for this week you will be directed towards two research articles – one using qualitative analysis in psychology and one using qualitative analysis in the sociology of sport. Hopefully this will make process of qualitative analysis clearer but also some of the subtle differences in data analysis between the sub-disciplines. There are also differences within the sub-disciplines but we will not go into this here – this will be for you to get to grips with if you choose to research in one of these areas.
- In your introduction to qualitative research we considered the different methods of data collection. We then looked in a little more detail at two of these, documentary analysis and interviews. Obviously you are welcome to and encourage to read and familiarise yourself with other research methods. Please don’t think that because these are the methods of data collection that we covered with you that they are the ‘best’. The method of data collection that you choose of your research will depend on a number of things – especially the research question. There is a paper that you might find interesting in relation to this. It is entitled ‘research is a messy process’. Some of this, at this stage, will not be important to you but you might want to re-visit it if you decide to base your dissertations within the sub-discipline of sociology. For now – the main thing that I would expect you to glean from this paper is the message that there is no one best research method – the main thing is that the method is appropriate for collecting the most useful data in answering your research question.
- Once you have collected all of your data, which is likely to be a time consuming process itself, you will have to deal with your data. If you have carried out face to face interviews you will have had to listen back to what was said and transcribe what was said. If these were video recorded then it likely that you will have had to note the gestures of the participant too. Otherwise, if you conducted some kind of online interview or discussion then this might be in a more usable form already. So, one of the forms that your data will be in will be the transcripts that have been produced. In addition to this you may have made notes while you were collecting your data. This will be the case especially if you were conducting observations but you may also have scribbled some notes down during an interview of anything that you were thinking at the time and want to make sure that those thoughts are considered at the data analysis stage. Something that was emphasised by the participant perhaps or any thoughts about how you might explain your findings. Having large amounts of data to wade through can be quite a daunting task. So we are going to look at how we can approach this systematically.
- The first stage in qualitative data analysis will be reading and organising your transcripts and field notes. You will find that there are some things that can be discarded almost straight away if it is irrelevant, this is sometimes referred to as data reduction. Obviously anything that you do discard does need keeping though for checking towards the end of the analysis. This stage may also involve organising data into broad themes and beginning to annotate any initial thoughts while reading through your data.This will lead you towards the next main stage of your analysis – Identifying emergent themes. This will involve thorough reading, re-reading and coding themes that emerge from the data. So, for example, if you were looking at barriers to sports participation you might code any quotations relating to friends, family or colleagues influencing a person’s participation. Coding can be carried out using numbers, letters or highlighting using different colours. A different theme that might be coded might be any statements that relate to money, income, cost of membership or equipment.You may carry out initial coding of the emerging themes first and then move on to consider the literature and your theoretical framework or you may combine these stages. You might consider the literature in the area to compare your findings to. Also, depending on your approach you may have drawn upon a particular theoretical framework to guide your research. This is likely if you are carrying out a sociological study. In this case you would use the sensitising concepts of the theory to help to code or categorise your data further. This will lead towards your interpretation of the findings. Especially if you are to be explaining your data sociologically. Finally, you would re-visit your themes or categories. You would do this in order to organise your thoughts and confirm your interpretation of your findings. At this stage you may also re-visit the data that you discarded at the beginning to see if you have missed anything having looked in detail at your data. Throughout this stage and all of the earlier stages you would be expected to continually make notes about your data to help guide your discussion and interpretation of the data. Very often as you are reading your data you have some really useful thoughts but these are generally coming thick and fast as you deal with a large amount of data. Therefore it is vital to make a note as I can personally vouch for the fact that you will forget some things that, at the time, you thought were really useful points. The way that you organised data looks at the end of the analysis stage often varies. Many researchers prefer to put this into a table with the themes or categories displayed with the quotations that have been coded into those sections. At the end of this lecture I will get you to look at how data is presented. Broadly speaking you would provide some quotations that are representative of particular themes and the explanations they you are providing. This may be done in separate results and discussion sections or all together within a discussion section.
- Different disciplines in sport studies and sport science tend to use different philosophic positions and these tend to result in the use of different methods of analysis associated with those particular positions. In sport psychology there are a number of possible stances that could be taken depending on the research question you are considering. Each of the methods illustrated use different methods of theming the data for analysis. For example, if you are interested in comparing individual’s experiences of a particular phenomena, you might chose to use IPA analysis. This would involve initially reading through transcripts and making notes on your initial feelings and how you make sense of what is reflected in the participant’s responses. Then you would produce themes and organise these into clusters. These might then be used to compare and contrast the experiences you are interested in. If you intend to use a particular approach you should familiarise yourself with the particular method as there are differences in how themes are produced and considered.
- There are some relatively new computer analysis programmes and software packages emerging. In a similar way to your method of data collection, the way that you analyse your data will be chosen depending on your research question and theoretical approach. As with everything else there are pros and cons to the range of computer analysis options. They can be very useful in dealing with large amounts of data. You will also be sure that you have not missed anything that you have intended to code. However, if you are looking at transcripts of conversations or behaviours you have to be sure that you have coded every possible term that could be related to a particular theme. For example, if we wanted to know about pain and injury – just like a thorough google search, we would have to ask the programme to code pain, painful, hurt, sore, ache, tight, sprain, break, broken and so on and we would have to make sure that we had covered all of the possible terms that could have been used by respondents. Whereas if we were to be coding out data manually we would recognise anything relating to this theme as we read. As with most things there is always the possibility of combining computer analysis with the more human process to confirm data sets. There is certainly a place for this in large research projects and it is something to keep an eye on for future use.
- One final thing to consider is the confidence with which you can discuss your data. We have to be aware of certain researcher biases or ideological assumptions. Some sociologists talk about involvement-detachment and the need to ‘take a step back’ from their ideologies or opinions or preferences in order to analyse things in a more adequate way, although there are no clear procedures for becoming more detached. The trustworthiness of your analysis should also be taken into consideration. Consider whether you have any assumptions about your research and whether you have coded the data in ways that confirm your thoughts rather than genuinely coding the data as it really is. Qualitative analysis is thought to be more open to this sort of bias than quantitative analysis, even though we know that statistical analysis is still a social process.There are some tools for ensuring the trustworthiness of your data discussed in research methods text books – as we have stressed throughout – check your sub-discipline and read accordingly. Member validation is one of the most common methods used for validation the interpretations. Those being investigated as asked to judge the adequacy of the analysis. As you can imagine, this has its problems connection to the ideological views of individual participants and peer reviewing is often used as an alternative.Considering alternative explanations is another useful process, this requires the researcher to search for data that contradicts their explanations in order to ensure that they have not simply tried to confirm their own biases or assumptions. Keeping an audit train can help to ensure the reliability of qualitative research. This is linked to peer reviewing, if there is an audit train then the research process and decision making can be judged.Critical reflection by the researcher regarding their role in the whole research process can help to identify any ways in which they may have influenced the research.
- By now you should have some understanding of qualitative data analysis. We have pointed you towards some differences between the sub-disciplines in the study of sport. The best way for you to get more of a handle on this is to look at publications in the area.So your task for this week is to read the papers uploaded. One is written by sociologists of sport, the other by sports psychologists. You can focus your reading on the methods and findings.Check how the methods sections are written. You can then move on to consider the way that the findings are presented in their ‘themes’ and how data is quoted within this. The main things to gain an understanding of through this task are some of the differences between the sociological and psychological approach. So, focus on identifying the differences between the papers. These only provide you with one example – just to confuse you even further there are differences within sub-disciplines so when you do eventually choose your dissertation topics be sure to get to grips with the sub-discipline within which you choose to study.Good luck with your reading and keep us up to date with how you are getting on and anything that you are unsure on.