3 Thesis Data Gathering

3 Thesis Data Gathering-22
A simple bulleted list of the steps you plan to conduct will suffice for this step.

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The draft should be succinct, clear, and comprehensive.

Once you have completed the narrative, you can compare it to the outline to make sure everything is addressed.

Most, Craddick, Crawford, Redican, Rhodes, Rukenbrod, and Laws (2003) describe ‘quality assurance’ and ‘quality control’ as two approaches that can preserve data integrity and ensure the scientific validity of study results.

Each approach is implemented at different points in the research timeline (Whitney, Lind, Wahl, 1998): Since quality assurance precedes data collection, its main focus is 'prevention' (i.e., forestalling problems with data collection).

Regardless of the field of study or preference for defining data (quantitative, qualitative), accurate data collection is essential to maintaining the integrity of research.

Both the selection of appropriate data collection instruments (existing, modified, or newly developed) and clearly delineated instructions for their correct use reduce the likelihood of errors occurring.

This phenomenon, known as ‘drift’, should be corrected with additional training, a provision that should be specified in the procedures manual.

Given the range of qualitative research strategies (non-participant/ participant observation, interview, archival, field study, ethnography, content analysis, oral history, biography, unobtrusive research) it is difficult to make generalized statements about how one should establish a research protocol in order to facilitate quality assurance.

Poorly written manuals increase the risk of failing to identify problems and errors early in the research endeavor.

These failures may be demonstrated in a number of ways: An important component of quality assurance is developing a rigorous and detailed recruitment and training plan.


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