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❶Choosing Qualitative Data Analysis Software:

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One person found this helpful. Most helpful customer reviews on Amazon. IMO, this is most appropriate for researchers with some experience, rather than beginning doctoral students.

Kirk and Miller seek to resolve some of the problems of reliability and validity faced by researchers using qualitative methodology. It is emphasized in the series introduction in the preface of the book that the distinction between qualitative and quantitative research is often misleading and false. The authors elaborate on that observation in their opening comments by noting, "Technically, a 'qualitative observation' identifies the presence or absence of something, in contrast to 'qualitative observation,' which involves measuring the degree to which some feature is present.

They acknowledge that individuals' meanings must be taken into account in the process of reporting the findings. The meat of their argument is addressed in the next section as they cite various well known researchers and discuss their contributions. They talk about issues of reliability in these studies and the role of interpreting results.

This book helps you to see the challenges of ethnographic research. Kirk and Miller's methodology explanation and historical examples help researchers of social problemas to conduct their works in a really focused scientific direction. Short and clear, without compromising the message, it's a really worth reading text. Feedback If you need help or have a question for Customer Service, contact us. Would you like to report poor quality or formatting in this book? Click here Would you like to report this content as inappropriate?

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Clearly, in this situation it makes more sense to use dedicated software. The extent to which the software is exploited beyond this basic use is related to the expertise of the analyst.

For example, writing memos within the software rather than manually by, perhaps, writing in a notebook and linking different pieces of data together through electronic memos can be useful when building up themes across the data. In order to make sense of these memos though, it is useful to return to "manual" methods.

This involves going through coded text as well as memos and making notes on how all of these link together. At this point it is useful to think of the qualitative research project as a rich tapestry. The software is the loom that facilitates the knitting together of the tapestry, but the loom cannot determine the final picture on the tapestry.

It can though, through its advanced technology, speed up the process of producing the tapestry and it may also limit the weaver's errors, but for the weaver to succeed in making the tapestry she or he needs to have an overview of what she or he is trying to produce. It is very possible, and quite legitimate, that different researchers would weave different tapestries from the same available material depending on the questions asked of the data.

However, they would have to agree on the material they have to begin with. Software programs can be used to explore systematically this basic material creating broad agreement amongst researchers about what is being dealt with. Hence, the quality, rigour and trustworthiness of the research is enhanced. In order to understand how the different themes knit together to form a whole, it is first necessary to analyse individual themes. Using Nvivo to do this is difficult.

Whilst it can be helpful in terms of counting "who said what" within a theme, in order to relate the theme to other ideas it is necessary to consider, for example, the memos written during the analysis process.

The model explorer tool in Nvivo is useful at this point for mapping out diagrammatically how the themes relate to each other. However, because it is difficult to show the whole model on screen at once it is easier to do this on, for example, a very large piece of card so that the researcher can view the whole picture and the inter-relationships of the codes at a glance.

When considering the memos and coded data together in order to pull out themes across the data I found it useful simply to write a short summary on each node. These summaries included details such as how many women from a particular political party appeared within text coded at each node, for example, how many women from the Conservative party self-identified as feminist? This information was placed alongside relevant memos and using this information, notes were made of possible themes within the nodes.

For example, when considering the motivations of the councillors the relevant text from all interviews was coded at "motivations" and a coding report 7 was made of this node. The theme of "credibility" which was related to the councillors' search for a professional identity was identified from this node coding report and thus initial ideas were formulated for a discussion in the research of a "political investor" identity among councillors.

The temptation, as mentioned above, when using software in the data analysis process to extend the coding—because it is relatively easy to do so—beyond any real benefit for understanding the data is a difficult issue. For example, once data have been gathered together under descriptive codes and thematic ideas have emerged from this process with the data connected together through memos, it is possible to begin coding again, with only thematic codes being applied.

The purpose of this stage of analysis is to ensure that the theoretical ideas which have emerged in the first round of coding can be systematically evidenced in the data, thus addressing the validity of the research results and this may be "easier" to see if all data relevant to, for example, "professional identity" are coded electronically together rather than manually highlighted on paper.

This would, in turn, make it possible to search this "professional identity" code to find out, for example, how many councillors from a particular political party fell into this category.

However, the decision to code data at this stage, once it has been identified manually on paper, will be influenced by the size of the data set. In this research project into women local politicians, it was possible to see these codes easily on paper without electronically re-coding them simply because there were so few women in any one category. Thus, once again we see manual and electronic methods being combined whilst also taking account of the research reality of available time.

The searching tools in NVivo allow the researcher to interrogate her or his data at a particular level. This can, in turn, improve the rigour of the analysis process by validating or not some of the researcher's own impressions of the data. However, the software is less useful in terms of addressing issues of validity and reliability in the thematic ideas that emerge during the data analysis process and this is due to the fluid and creative way in which these themes emerge.

Of course, details can be checked on the content of particular nodes and this could affect the inter-relationships of the thematic ideas, but in terms of searching through the thematic ideas themselves in order to gain a deep understanding of the data, NVivo is less useful simply because of the type of searching it is capable of doing.

It is important that researchers recognise the value of both manual and electronic tools in qualitative data analysis and management and do not reify one over the other but instead remain open to, and make use of, the advantages of each. Its full title is NUD. In this paper where NVivo is referred to it is to the first version of the software. The researcher can create attributes for any documents in NVivo.

Choosing Qualitative Data Analysis Software: Sociological Research Online, 3 3. Computers and QDA—can they help it? A report on a qualitative data analysis programme. Sociological Review, 38 1 , Making Sense of Qualitative Data. How we ensured rigour in a multi-site, multi-discipline, multi-researcher study. Qualitative Inquiry and Research Design: Choosing Among Five Traditions. Software for qualitative research: Some thought on "aiding" analysis.

Environment and Planning A, 29, Theory, Methods and Practice pp. Sociological Research Online, 2 2. Reliability and Validity in Qualitative Research. Reflections on a Voice-centred Relational Method: Public Knowledge and Private Lives pp. An Expanded Sourcebook 2nd edition. Exploration of First Time Motherhood: University of Warwick, UK. The role of computer software in the analysis of qualitative data: Journal of Advanced Nursing, 28 1 , The Transformation of Qualitative Method: Computational Paradigms and Research Processes.

From filing cabinet to computer. The Quality of Qualitative Research. Methods for Analysing Talk, Text and Interaction.

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Like reliability and validity as used in quantitative research are providing springboard to examine what these two terms mean in the qualitative research paradigm, triangulation as used in quantitative research to test the reliability and validity can also illuminate some ways to test or maximize the validity and reliability of a qualitative study.

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Some contributions to issues and ever present debates on the reliability and validity of qualitative research approaches. However some concerns on the currency of the arguments given the references.

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Kirk and Miller seek to resolve some of the problems of reliability and validity faced by researchers using qualitative methodology. It is emphasized in the series introduction in the preface of the book that the distinction between qualitative and quantitative research is often misleading and false/5(3). Reliability and Validity in Qualitative Research / Edition 1 Kirk and Miller define what is -- and what is not -- qualitative research. They suggest that the use of numbers in the process of recording and analyzing observations is less important than that the research should involve sustained interaction with the people being studied, in their Price: $

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Following a chapter on objectivity, the authors discuss the role of reliability and validity and the problems that arise when these issues are neglected. They present a paradigm for the qualitative research process that makes it possible to pursue validity without neglecting reliability. Reliability and Validity in Qualitative Research - Ebook written by Jerome Kirk, Marc L. Miller. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Reliability and Validity in Qualitative Research.