Grounded Theory (GT) and Content Analysis (CA) are widely known methodologies applied within multiple scientific communities, sharing a close background with social sciences. Each of these approaches has been developed and tested throughout distinct historical pathways, both shaped by different aims, results and theoretical constructions. Whereas GT belongs to what could be described as “inductive science”, CA is tagged under the motto of “deductive sciences”, assuming essentially different epistemological positions (Bernard & Ryan, 2009). They are also contrasted by their qualitative and quantitative data insights. Content Analysis is generally described as a process where data are “quantified”, in which key words and phrases are commonly interpreted into statistical terms, associated as a quantitative focus (Weber, 1990). Grounded Theory on the other side, remains as a predominantly qualitative analysis throughout the overall process. But the reason why I put these differences side by side is to ask simple yet complex questions: Are these distinctions enough to be talking about strictly different approaches? And do these differences mean that both methodologies are essentially incompatible and aim to separate prospects? What comes to my attention, and what I will further present throughout this brief paper, is that, although both methods are defined within separate boundaries, their differences do not constitute an epistemological incompatibility. In fact, their paired use could lead us to alternative means for data exploration and theoretical constructions. Are there any significant commonalities between these methodologies? To what extents could they be used side by side, simultaneously and/or as triangulation source for th... ... middle of paper ... ...ison qualitative data analysis: Using NVivo. School Psychology Quarterly, 26(1), 70. Leech, N. L., & Onwuegbuzie, A. J. (2008). Qualitative data analysis: A compendium of techniques and a framework for selection for school psychology research and beyond. School Psychology Quarterly, 23(4), 587. Maxwell, J. A. (1996). Qualitative research design: An interactive approach (Vol. 41). Sage publications. Tesch, R. (1990). Qualitative research: Analysis types and software tools. London: Routledge Weber, R. P. (1990). Basic content analysis. Second edition. Quantitative applications in the social sciences. (Vol. 49). Sage Publications. Yu, C. H., Jannasch-Pennell, A., & DiGangi, S. (2011). Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability. Qualitative Report, 16(3), 730-744.
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Using two theoretical approaches to social research namely, Positivism and Standpoint theory, I have demonstrated implicit connections in their respective assumptions. The ontological, epistemological and methodical assumptions are all integral facets of the understanding of social research. Once these are understood one can then draw conclusions as to which type or types of methods are appropriate to use.
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Gelo, O., Braakmann, D., & Benetka, G. (2008). Quantitative and Qualitative Research: Beyond the Debate. Integrative Psychological & Behavioral Science, 42(3), 266-290. doi:10.1007/s12124-008-9078-3
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The articles, published after 1996, contain varied methods of research attainment, but share similarities such as being a self-survey, having a small sample size, and being
The author could have employed other methods of qualitative research such as, narrative analysis, grounded theory, discourse analysis, data display and analysis, content analysis and quantifying qualitative data and computer assisted qualitative data analysis software (CAPDAS) (Saunders et al., 2016). Nevertheless, these approaches seem cumbersome sometimes and take a long time to complete (Willig, 1999; Braun and Clarke, 2006 and Smith and Bekker,
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
The research is guided by a theoretical framework called the Grounded Theory Approach. The Grounded Theory Approach (GT), first described by Glaser and Strauss in 1967, is an inductively formatted, general method of research that is aimed towards theory development through the data collection process and constant comparative analysis of that data. Cohen and Crabtree, 2006). The concept relies contingently upon the data the study presents and is characterized by the proposed theory being perfectly depicted by the data accumulated. Cohen and Crabtree, 2006).
A core phenomenon in a substantive study has clear implications for a formal grounded theory (Strauss 1987).
Methods, which provide this type of data, include; interviews, observations as well as focus groups. The advantages of using Qualitative methods such as those listed previously is that they can produce “an extensive base of knowledge” to complex areas of research (Ulin et el. 2005, p.9) such as children’s behavior in school. Another advantage is it will often take place in a natural environment, thus making participants more likely to be more truthful and ther...
Quantitative research uses a deductive reasoning also known as top to bottom or (top down approach) starting with a theory, then the hypothesis, followed by observation and finally confirmation , going from the general to the more specific. Quantitative methods use numbers and statistics to show the results of the research exercise and mainly are concerned with mathematics and statistics. In quantitative research there are levels of measurement being firstly nominal which are names of things followed by ordinal sequence of things, interval where the sequence has equal distance between each item, and ratio where there is a true zero (Alston & Bowles, 2003, p. 7-9).
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