dc.contributor.author |
Smit, Brigitte
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dc.date.accessioned |
2008-04-02T12:05:54Z |
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dc.date.available |
2008-04-02T12:05:54Z |
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dc.date.issued |
2002-09 |
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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. |
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dc.format.extent |
158516 bytes |
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dc.format.mimetype |
application/pdf |
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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] |
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dc.identifier.issn |
0081-2463 |
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dc.identifier.uri |
http://hdl.handle.net/2263/4813 |
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dc.language.iso |
en |
en |
dc.publisher |
Faculty of Education, University of Pretoria |
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dc.rights |
Faculty of Education, University of Pretoria |
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dc.subject |
Atlas.ti |
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dc.subject |
Qualitative data analysis |
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dc.subject |
Educational research |
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dc.subject |
CAQDAS |
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dc.subject |
Computer-aided qualitative data analysis |
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dc.title |
Atlas.ti for qualitative data analysis |
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dc.type |
Article |
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