Validating quantitative data triangulation model
Keywords: Mixed Method Design, Philosophical Premises, Generating Research Questions, Data Collection and Analysis, Ethical Issues, Quality of inference and Teaching Mixed Methodology Copyright © 2016 Science and Education Publishing. The Educational researchers are still in dilemma to choose a particular methodological stand point to approach a research problem.They often find difficulties to choose possible alternative methods to carry out their research work. On the one hand, this definition puts forth the main points of what qualitative research is about, but it also demonstrates how it is positioned or tries to position itself in contrast to quantitative research.NEUMAN (1997) goes even further by stating that there are basically two categories of data collection techniques: quantitative and qualitative (p.30).
Some see triangulation as a method for corroborating findings and as a test for validity. This assumes that a weakness in one method will be compensated for by another method, and that it is always possible to make sense between different accounts. Rather than seeing triangulation as a method for validation or verification, qualitative researchers generally use this technique to ensure that an account is rich, robust, comprehensive and well-developed.
This problem isn’t restricted to UX and Ix D of course, our marketing brethren might do likewise, referring only to Roy Morgan for insight, for example.
Each of these techniques can be incredibly useful for giving insight into a particular aspect of what you’re studying, but relying solely on one is a big mistake.
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It could be something as simple as a run away script or learning how to better use E-utilities, for more efficient work such that your work does not impact the ability of other researchers to also use our site.
This article highlights on the growing interest of educational researchers on sequential mixed method design in order to collect and analyze data for legitimize knowledge claim.