Atlas.ti for qualitative data analysis

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dc.contributor.author Smit, Brigitte
dc.date.accessioned 2008-04-02T12:05:54Z
dc.date.available 2008-04-02T12:05:54Z
dc.date.issued 2002-09
dc.description.abstract In this article I discuss a variety of theoretical and conceptual dimensions of Atlas.ti (Muhr, 1994, 1997a, 1997b). I draw on my own Atlas.ti experiences (Smit, 001), and discuss advantages and disadvantages of using computer-aided qualitative data analysis software (CAQDAS) (Lee & Fielding, 1995). How can the quality of a research project be enhanced and how will the end product be affected? These are some questions I intend to answer. Firstly, I introduce qualitative data analysis in general. Secondly, I discuss the relevance of computer-aided qualitative data analysis software in qualitative research and how Atlas.ti, focuses on coding procedures, (cf. Miles & Huberman, 1994; Dey, 1993) which supports a grounded theory approach for data analysis. Thirdly, I illustrate some facets of my Atlas.ti project and explain some technical aspects, such as the VISE principles, visualisation, integration, serendipity and exploration as the main strategic modes of operation that may enhance the quality in the data analysis. en
dc.format.extent 158516 bytes
dc.format.mimetype application/pdf
dc.identifier.citation Smit, B 2002, 'Atlas.ti for qualitative data analysis', Perspectives in Education, vol. 20, no. 3, pp. 65-75, [http://journals.sabinet.co.za/ej/ejour_persed.html] en
dc.identifier.issn 0081-2463
dc.identifier.uri http://hdl.handle.net/2263/4813
dc.language.iso en en
dc.publisher Faculty of Education, University of Pretoria en
dc.rights Faculty of Education, University of Pretoria en
dc.subject Atlas.ti en
dc.subject Qualitative data analysis en
dc.subject Educational research en
dc.subject CAQDAS en
dc.subject Computer-aided qualitative data analysis en
dc.title Atlas.ti for qualitative data analysis en
dc.type Article en


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