Guide to Advanced Empirical
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- Inspection process
- Reviewed material: How much was inspectedHow is that measureWere the inspected classes more or less complex then average Fig. 3
| Logistical info record name, office, date, time Organization: How long have you worked on project At [company]? Have you work with any of the project members before on other projects? Who on the project team do you interact with most? To whom do you report? To whom are you responsible for your progress on [project]? Inspection process: Who chose the inspectors? How long did it take? Why were those ones chosen in particular? Which inspectors inspected what? Who took care of scheduling? Was it done via email or face-to-face? How much time did it take? What steps were involved inputting together the inspection package? How much time did that take? How are project inspections different from inspections in other company projects you’ve been on? How was this inspection different from other project inspections you’ve been involved with? Reviewed material: How much was inspected? How is that measure? Were the inspected classes more or less complex then average? Fig. 3 An interview guide used in the Inspection Study 48 CB. Seaman qualitative analysis are sometimes boring, often tedious, and always more time-consuming than expected. It is tempting to take shortcuts in the analysis process, but rigorous analysis is necessary for the integrity of the research, and results in more insightful, useful, and valid conclusions. As in quantitative studies, data analysis should be planned upfront, before data collection begins. However, the difference is that qualitative researchers collect and analyse data nearly in parallel, or at least alternate between the two. Qualitative analysis begins as soon as some significant amount of data has been collected. Preliminary analysis results also can modify subsequent data collection. In the next two sections, we present several analysis techniques, roughly divided into two categories, although the line between them is not well delineated. The first set of methods (Sect. 3.1) is used to generate hypotheses that fit the data (or are grounded in the data, normally used in exploratory, or grounded theory studies Glaser and Strauss, 1967). Section 3.2 describes some methods used to buildup the weight of evidence necessary to confirm hypotheses in confirmatory studies. Following, in Sect. 3.3, we discuss the use of visualization of qualitative data, which is useful in conjunction with any analysis approach, and for presenting results. Finally, Sect. 3.4 presents some basic techniques for transforming qualitative data for subsequent quantitative analysis. The methods presented in these sections represent only a small sample of the methods, techniques, and approaches available for analysing qualitative data. Yin (1994) and Miles and Huberman (1994) are excellent sources for other data analysis approaches. Download 1.5 Mb. Share with your friends:
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