Term Paper: Concise Analysis of Assignment 2 Application

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[. . .] A qualitative researcher is concerned with a different focus. The researcher is interested in uncovering how and when they use emotional labor, with the aim of identifying or establishing the role emotional labor plays in their work. Data analysis would be an ongoing process for the duration of the study (Maxwell, 2008). The researchers will use observation and in-depth interviews. Therefore, they should be able to transcribe the interviews immediately and identify patterns and themes. The study will make use of different criterions to establish the quality of the study. It would not be possible to employ the same criteria as the ones used in qualitative research. It is vital to establish the consistency of the data collected. Different researchers can conduct the same study using the same employees, and they can rest assured that they will get the same results.

Qualitative data analysis takes into account trailing the correlation between categories and themes pursuant to enhance the understanding of the phenomenon. Bearing this in mind, the researcher is necessitated to be prepared, flexible and positively interact with data collected. Taking into consideration that the data gathered in this research study is text-based, the foundation of analyzing these data is the coding process. In delineation codes are labels for apportioning units of meaning to the inferential information gathered in the course of a study. In this process, coding takes into account searching for related phrases and wording that will be mentioned by the interviews during the interview process and recorded in the transcripts. Subsequently, these phrases are put together so as to understand the correlation and relationship between them. Imperatively, this study will employ Nvivo for data analysis. This is a qualitative data analysis computer software package that will facilitate the quality of research and will provide more time to discover inclination, ascertain themes and derive conclusions (Hilal and Alabri, 2013).

The main advantage of using Nvivo in this particular study is that it will undertake five significant tasks that will ease analysis of the qualitative data. First, the software package will manage data that will include interview transcripts. Secondly, it will facilitate management of ideas so as to comprehend the theoretical and issues that come about during the study. The third task is querying of data through posing numerous questions of the data and employing the software in answering these queries. Fourth, Nvivo will generate graphs that will illustrate the correlations between conceptual and theoretical data and lastly report information by employing the data gathered and the outcomes found to formulate reports about the study conducted (Hilal and Alabri, 2013). However, it is imperative to point out that Nvivo and the coding process will have its own difficulties. In accordance to Welsh (2002), Nvivo is less beneficial in terms taking into consideration issues of validity and reliability in the thematic notions that come about in the course of the data analysis process and this is as a result of the unsolidified and creative manner in which these themes emanate. In addition, it is imperative to note that Nvivo similar to statistical packages have shortcomings in the sense that they do not necessarily analyze data but rather facilitate the analysis process itself.

References

Creswell, J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousand Oaks, CA: Sage.

Eysenbach, G., & Kohler, C. (2002). How do consumers search for and appraise health information on the world wide web? Qualitative study using focus groups, usability tests, and in-depth interviews. Bmj, 324(7337), 573-577.

Hilal, A. H., & Alabri, S. S. (2013). Using NVIVO for data analysis in qualitative research. International Interdisciplinary Journal of Education, 2(2), 181-186.

Maxwell, J. A. (2008). Designing a qualitative study. The SAGE handbook of applied social research methods, 2, 214-253.

Welsh, E. (2002, May).… [END OF PREVIEW]

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