Atlas.ti for qualitative data analysis

dc.contributor.authorSmit, Brigitte
dc.date.accessioned2008-04-02T12:05:54Z
dc.date.available2008-04-02T12:05:54Z
dc.date.issued2002-09
dc.description.abstractIn 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.extent158516 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.citationSmit, 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.issn0081-2463
dc.identifier.urihttp://hdl.handle.net/2263/4813
dc.language.isoenen
dc.publisherFaculty of Education, University of Pretoriaen
dc.rightsFaculty of Education, University of Pretoriaen
dc.subjectAtlas.tien
dc.subjectQualitative data analysisen
dc.subjectEducational researchen
dc.subjectCAQDASen
dc.subjectComputer-aided qualitative data analysisen
dc.titleAtlas.ti for qualitative data analysisen
dc.typeArticleen

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