I think qualitative research is an area of great complexity and a bit of a love/hate relationship for researchers within the social sciences. There does not seem to be many discernible hard and
fast, black/white rules as with quantitative, much can be seen to be up to interpretation, yet it provides the ‘rich content’ that many researchers are looking to mine in their work. In looking at the essays from the UK data service, which are taken from 16 year olds from the Isle of Sheppey in 1978, I appreciated how difficult coding can be beyond the very general (I did not use software to fit he coding but looking at others blogs this may have been a blessing rather than a curse!) The main ‘take away’ I took from this was that the position of the researcher can play a very important role in in their interpretation of the data. For example, in this activity I felt a great deal of empathy and connection to these voices as I was brought up in a very similar environment (1970’s working class), and questions which other researchers may have had regarding the data (the lack of educational ambition, importance given to home ownership) would not be as pertinent to me as someone of the same age (so aware of the economic climate at the time) and of the same background. Key theme Though there are several key themes (some of them mentioned above), I found the most interesting one to be the longevity of service expected within employment. None of the participants expected to move company or occupation unless it was necessitated by starting a family, moving to a new region or negative impacts such as redundancy or inability to find work. Not only this but there expectation was that staying in a job was seen as the way to ‘get on’ rather than acquiring qualifications. What is an interesting question that researchers might be able to answer using this data? One interesting question which could be answered is the reasons behind the low number of students in the Isle of Sheppey who stayed on at school beyond the age of 16. Though the actual number could be ascertained through quantitive analysis, assessing the students own ambitions would help to understand the reasons why so many left education as soon as possible. If you were conducting a project using this data, what would you want to do next? I think a longitudinal study which also incorporated data from the original participants children and children would be very interesting. Many of the participants obviously envisaged that their children and children would have ‘better’ and ‘easier’ lives then they had and a longitudiunal study would help to establish if this was the case.
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I'm not completely sure if this blog entry really fulfils the objective of this weeks objective of finding a resource which 'lies with statistics' but this is something which I have personal experience of which may be called 'misrepresentation by not communicating all the facts' and it definitely put the cat amongst the pigeons where I work a few years ago! Private hospitality education in Switzerland is a business and competitive advantage is something to strive for. This means that surveys, league tables, etc, are very important marketing tools. Back in 2013 two particular schools used research undertaken by TNS to promote their schools as they had come very high on the league table provided (Source: TNS Global Survey, 2013) The results and indeed the survey itself was met with confusion by many other schools. Firstly, no one within the other schools had been contacted or informed about the survey (though of course in an impartial research project there was no reason to assume that they would be contacted) nor asked to provide any assistance in comprising the data source (in this instance senior management within the hospitality industry). The results themselves were very interesting as schools which had ranked much higher in other, more well established league tables were lower down the pecking order (for example, Cornell which is kind of like the Harvard/Yale of hospitality education in the US).
Looking beyond the website marketing and to the research paper itself, there were some glaringly obvious causes for concern of the validity of the research but also a lot of 'vagueness'. The first 'mmm' was the fact that the research itself had been funded by the education group who run the two schools which found themselves above Cornell. To the researchers credit this was made very clear to anyone who made the effort to find the research paper itself. However, there was no indication of the methodology used in sampling their participants. How were they chosen? What criteria was used? This is not made clear and therefore left the research open to interpretations and assumptions (being that the majority of participants had been provided by the funding body). I think this was the main area where if the researchers had been more transparent the research could have been improved and in fact supported their findings more thoroughly. Thought I would slightly not follow the rules by doing the second activity this week (analysing the paper by Kan and Laurie) on my blog. If I am totally honest this was probably the first time I have ever read a quantitative paper properly, as in actually trying to understand the tables of statistics and numbers. Normally I just skip through that bit and go straight to the results and discussion part of the paper. By trying to actually understand the ‘numbers’ bit I now realise two things:
Data Source Kan and Laurie used secondary analysis of an existing large dataset (The UK Household Longitudinal Study). One of the main advantages of using such a service (as well as saving time and resources on collating primary data) is the scale of the sample. As the study covers over 40,000 households the amount of data available to there researchers was vast though the amount of information based on ethnicity is quite smaller (1000). Both the large number of participants and the longitudinal nature of the data validates the research in terms of its scope. However, one of the main disadvantages is the lack of control the researchers have over the survey design. Basically with secondary analysis researchers ‘get what they are given’ and have to deal with it accordingly. For example, a limitation the researchers mention several times is there is no way to determine how the participants determine ‘housework’ which could have had an important effect on the responses. Intersectionality Previous research in this area has primarily focused on differences between gender in domestic division of labour which though useful does not reflect differences in relation to ethnic group and gender. Issues such as inequality within the genders and between the genders based on ethnicity are not reflected but, as this research attempts to show, can indicate wide and unexpected differences. Understanding (or not) of statistical terms In actually trying to understand the methodology used rather than just skipping to the summary of results I realised there are many, many terms that are currently beyond my comprehension - in doing some quick reading on some of the concepts (OLS regression, for example) it really made me appreciate the complexity of quantitive methods. There were however other terms I found much easier to get to grips with (perhaps because the language seems a lot more ‘generic’ and not specific to ‘statistical vocabulary’. One of these was cross sectional analysis. Cross-sectional analysis is often contrasted with longitudinal studies (for example here). Cross-sectional can be seen as analysis which happens ‘in one point in time’ rather than across time. In this instance this means that analysis was taken within the The UK Household Longitudinal Study data and not across the different waves of the study. Though the research uses data from two waves of the study, these are ‘pooled’ together rather than analysis with would look at similarities and differences between the two waves. Findings The researchers make a compelling argument for the importance in their research in extending the range of previous research beyond merely gender to incorporate differences between ethnic groups and gender attitudes, especially in light of other contributing factors such as inequality of opportunity (educational attainment, employment status, etc). By using intersectionality to analyse these different areas the reseachers make an attempt to ‘pull apart’ the data to indicate the relationships between the different elements in creating a more detailed picture of the Household Survey that incorporates more than merely male v female comparisons. One result which was very interesting was based on the assumption that the ‘White. . .’ ethnic groups would have the most equal results which was not the case with the Black Caribbean group identified as having the most equal share in housework. However, I also think that this also reflects one to the weaknesses of this research - there seems to have been some ethnic centred assumptions made regarding the expected results. Furthermore, as other students on the course have highlighted, there seems to be a generic relation made between some ethnic groups and religion which seems unfounded.
This week I have been looking at surveys which I thought would be pretty straight forward but got more complex as the week went on! I am going to save my reflections on surveys until next weeks blog, but this is my attempt at the second activity which was to create a small survey regarding the use of a social media by a specific group.
I decided to choose a group I work with quite a lot here in Switzerland which is students from mainland China who are experiencing studying outside of their home country for the first time and their use of facebook - the majority do not have Facebook accounts when they arrive as most are experienced users of a platform called Wechat, but this puts them in the minority compared to all other nationalities where Facebook is the main social media platform used prior to starting their studies. I started to put together a mindmap and survey but the more I thought about it the more convoluted it got and I am now veering towards the impression that a survey would not work very well with this research question and that perhaps interviews or focus groups would be more effective way of going forwards with this research. However, I have persevered though I am sure there are some BIG holes in my questions, so all feedback is appreciated! One important note is that I think before this survey there would be a need for a provisional survey or auditing so that the students who would take this survey would already be determined as those who created a Facebook account after starting their studies. Below you will find my initial mindmap on the research question and the survey itself. Well, last week I was mildly confused, this week I feel like I have totally fallen into the rabbit hole as I have grappled (unsuccessfully I think) with discourse analysis. As I am interested in areas of socio-materiality I thought this would be a good method to look at and possibly use in the future.
I really should have known, if I am honest, that I was going to struggle with this - in my undergraduate days I remember struggling terribly as someone who will openly confess to have an ‘enlightenment’ type of thinking, with post-modern and post-structuralist theory - even the sniff of the name ‘Foucault’ should have had me running in the opposite direction. But I was very intrigued about discourse analysis - what makes it different from the analysis of interviews, or grounded theory with its codification? Outside of linguistics, what is the role of discourses analysis? I am not sure I have yet reached a conclusion. . . In the videos and texts I have read, there seems to be more a consensus of what it is not rather than what it is (for example, Antaki et al, 2003) - it is not summarising or using selective quotations to confirm or refute a particular concept. It is something which adds to the understanding of a discourse or text - two of the most understandable resources I found was the video (Wiggins, 2017) describing the different ‘schools’ of discourse analysis as belonging on a spectrum of lenses from the ‘wide angled’ to the ‘zoom’, from analysing at a wider societal level of Foucauldian analysis with its focus on relations of power and knowledge to the zoom lens of conversational analyses which pulls apart the verbal dynamics of an individual discourse. The other was the chapter from Gee (2006) where he defines the work of discourse analysts as the ‘. . . study of how speakers and writers use clues or cues (namely, syntax and discourse) to shape the interpretations and actions of listeners and readers.’ (p20). Though I think a lot of discourse analysts would refute this as far too general to really define what they do, I have found this as a workable starting point for a method which I have in turn found very appealing and incredibly difficult to understand at exactly the same time. One of my research interests is in the way the implementation of a specific device into my organisation may (or may not) have changed the way our students work with, relate to and use that device as part to their study life and if the fact they have been ‘made’ to use this device has in some way affected their relationship to it ( I can remember the difference between being ‘made’ to read Lord of the Flies at school and then reading it by choice when I was much older and the difference in my feelings towards the novel and relationship to it). It may well be that discourse analysis will indeed allow me to analyse the ‘clues and cues’ which are part of discourse but I do feel currently that my research question is too broad and that for this research method to be really useful I really need to decide on which lens I would like to use. Or maybe I just need to find another rabbit hole. . . . . References: Antaki, C., Billig, M., Edwards, D. and Potter, J. (2003) Discourse analysis means doing analysis: A critique of six analytic shortcomings, Discourse Analysis Online, 1(1), 1-22 Gee, J.P. (2011) An introduction to discourse analysis: theory and method, Abingdon, Routledge. Wiggins, S. (2017) An introduction to discourse analysis [Video], London. Sage. What kind of topics are you interested in researching?
I am primarily interested in the way that technology can change or effect student behaviour and practices. This includes anonymity and participation, and developments in socio-materiality. As you can see I have some really fuzzy ideas at the moment! What initial research questions might be starting to emerge for you? Does anonymity lead to higher levels of participation, especially within an international student community? How do student practices change in regard to technology when the technology is imposed on them? • What are you interested in researching? In all honesty, its probably a bit of everything. My research topic is very focused on my own institution (well, they have paid for most of it after all!), though I feel that if I had to really pin it down I would say people and groups (relating to anonymity) and documents and images (relating to socio-materiality) Do you have an initial ideas for the kinds of methods that might help you to gather useful knowledge in your area of interest? The quiz on the MOOC suggested qualitative methods, discourse analysis and ethnography. I feel my topics definitely fall into the general area of qualitative rather than quantitative though I must admit I find what could be termed the more ‘scientific’ nature of quantitative rather comforting. • What initial questions do you have about those methods? These methods I understand in general but I don’t have much experience of using them myself and feel I would really need some practical examples to be able to either apply them myself or to evaluate them. Do you perceive any potential challenges in your initial ideas? My impression is that both discourse analysis and ethnography are quite labour intensive methods of collecting data, though I believe will provide much ‘richer’ information than surveys and questionnaires. Though I cannot envisage any issues with gaining access to a research group, I am concerned that as a member of staff students may not feel able to be completely honest in their answers, which makes me think that some sort of ethnographic research would be more beneficial. On a conceptual level, I am not quite sure that any findings could be objectively classified as either ‘truth’ or ‘facts’ as they are both principally focused on a very specific situation (international school community, for example). |
AuthorLisa Peel - MSc student, Librarian and permanently exhausted ArchivesCategories |