Fisher | Qualitative Computing: Using Software for Qualitative Data Analysis | Buch | 978-1-85972-561-0 | www.sack.de

Buch, Englisch, 146 Seiten, Format (B × H): 153 mm x 219 mm, Gewicht: 359 g

Reihe: Cardiff Papers in Qualitative Research

Fisher

Qualitative Computing: Using Software for Qualitative Data Analysis


1. Auflage 1997
ISBN: 978-1-85972-561-0
Verlag: Routledge

Buch, Englisch, 146 Seiten, Format (B × H): 153 mm x 219 mm, Gewicht: 359 g

Reihe: Cardiff Papers in Qualitative Research

ISBN: 978-1-85972-561-0
Verlag: Routledge


As qualitative researchers incorporate computer assistance into their analytic approaches, important questions arise about the adoption of new technology. Is it worth learning computer-assisted methods? Will the pay-off be sufficient to justify the investment? Which programs are worth learning? What are the effects on the analysis process? This book complements the existing literature by giving a detailed account of the use of four major programs in analyzing the same data. Priority is given to the tasks of qualitative analysis rather than to program capability and the programs are treated as tools rather than as a discipline to be acquired. The key is not what the programs allow researcher to do, but whether the tasks that researchers need to undertake are facilitated by the software. Thus the study develops a user-centred approach to the adoption of computer-assisted qualitative data analysis. The author emphasises qualitative analysis as a creative craft, but one which must increasingly be subject to rigorous methodological scrutiny. The adoption of computer-aided methods offers opportunities, but also dangers and ultimately this book is about the scientific qualitative research. Written in a distinctive and succinct style, this book will be valuable to social science researchers and students interested in qualitative research and in the potential for computer-assisted analysis.

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Contents: Getting into. and getting on with qualitative computing; Approaches to qualitative computing; Text searching and data exploration; Category building and finding meaning; Theory building; Conclusion; References.




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