Creswell 1998 phenomenology

M

The material in this document comes from the HASOP manual Qualitative Research Approaches in Psychology.

Data Analysis Data analysis in ethnography: Thematic analysis and exemplary life histories Ethnography shares with the other four approaches a core method of data analysis, namely thematic analysis. The other approaches may use different terms or specify slightly different procedures, but the core analytic method is quite similar. We describe it briefly here in its ethnographic form, and we’ll describe it briefly in its other forms when outlining the other approaches. Learners are advised to master the general method regardless of the approach they select. Once the data are collected by observations, interviews (audio taped and transcribed), field notes, or any other sources, patterns of experience (recurring words, phrases, descriptions, etc.) are identified and listed. These patterns are derived from direct quotes and paraphrases of recurring ideas emerging from the data. These patterns form the first level of thematic analysis. Next, the researcher identifies data that correspond to the identified patterns. If, in a study of the culture of a corporation, a pattern is noted such as “males defer to hierarchically superior males, but not to hierarchically superior females,” examples that confirm this – that show it is both recurring and an accurate description of events - are located in the data (transcripts, notes, etc.) and annotated with the listed pattern (as quotes along with citation of their source). Now, the researcher combines and catalogues related patterns into themes. Themes are defined as descriptive meaning units derived from the patterns. For example, if along with the earlier example this pattern emerged: “males repeatedly initiate flirting behavior with females regardless of the females’ rank and the females return the flirtation, even when they dislike it,” two themes or meaning units might be constructed as follows: “Males impose rank-dominance on subordinate males” and “males impose sexual-dominance on all females.” Finally, at the highest level of abstraction, themes that emerge from the patterns (which emerged from the original data) are synthesized together to form a comprehensive representation of the element of the culture that is being investigated. The above meaning units or themes might constellate with other descriptive themes of the male and female interactions in the organization into a rich and textured description of the rules, customs, attitudes, and practices around gender in that organization. This distillation of the practice of thematic analysis is adapted from Taylor and Bodgan (1984) and Aronson (1994). In writing ethnographic reports, one common – though by no means required - presentation practice is to construct “life stories” of representative or exemplary participants in the culture, group, or organization. Perhaps a more accurate term would be “culture stories” or “organization stories.” The objective is not to single out the individuals for study, but to use their experiences to exemplify key themes found in the data. These representative life stories are not standard biographies or life histories as might be found in biographical research. These life or organizational stories are created in a process not unlike thematic analysis. Here, however, the stories of the participants’ experience in the culture, group, society, or organization are culled for the initial patterns of recurring experiences, behaviors, etc. These in turn are organized into themes or meaning units which in a robust way exemplify important aspects of the larger culture, society, group, or organization. Finally, as in thematic analysis, the meaning units are woven into a richly evocative description of the meaning of the persons experience in this culture which stands for

Data Analysis

2 Capella Proprietary and Confidential ShortDoc_Internal.doc Last updated: 11/29/2006 3:05 PM

many others’ similar experiences. In effect, the life story (or the organization story, if you will) of the exemplar “stands for” the essence of the ethnographic description of what it means to be a member of this culture, group, or organization. References

Aronson, J. (1994). A Pragmatic View of Thematic Analysis. The Qualitative Report, 2, Number 1. Retrieved January 20,2003, from http://www.nova.edu/ssss/QR/index.html

Taylor, S, J. & Bogdan, R. (1984). Introduction to qualitative research methods: The search for meaning. 2nd edition. New York: John Wiley.

Data analysis in case studies Two types of data analysis for a case study are sometimes referred to (for example, Patton, 2005): holistic analysis, in which the information about the entire case is analyzed; and embedded analysis, in which information about a specific but limited aspect of the case is analyzed. For example, in a case study of learners’ experiences with online education, if all aspects of the experience are studied – the nature of the online platform, the IT support structure, the type of educational company providing the online learning, the quality and training of the teachers, the nature of the curriculum, the demographics of the learners, the costs and benefits perceived by the learners, the work load of the faculty, and so on and so forth – the analysis is said to be holistic. However, if out of that mass of data only one aspect is analyzed and reported – for example, the learners perceptions of the learning platform and of the instructors’ competence – this would be an embedded analysis. A case study dissertation would most likely be a holistic analysis of a case or set of cases. There is no consensus format for case study data analysis, but a common series of steps can be found in many sources. The following description is adapted from Creswell (1998) and Stake (1995).

• The opening step of data analysis – sometimes referred to as description – involves creating a

detailed description of the case as a whole and of its setting(s) and contexts. The objective is both clarity and detail, creating a rich and textured picture of the case and its settings.

• The case study researcher looks at single instances in the described data and draws meaning from each without (yet) looking for multiple instances. This process pulls the described data apart and puts them back together in more meaningful ways. This may be called direct interpretation.