Although knowledge is created and disseminated every day; there is relatively little consideration given to how that knowledge exists and how it was created in the first place. This essay explores how knowledge is created through research as logic of enquiry, mainly focusing on the differences between method and methodology, the debate between qualitative and quantitative research, and ultimately, the conclusion that research must be a synthesis of all relevant competing methodologies in a mixed methods approach. By utilizing such a holistic strategy, researchers are able to uncover their problem more accurately and effectively.
Although knowledge is created and disseminated every day; there is relatively little consideration given to how that knowledge exists and how it was created in the first place. This essay explores how knowledge is created through research as a logic of enquiry, mainly focusing on the differences between method and methodology, the debate between qualitative and quantitative research, and ultimately, the conclusion that research must be a synthesis of all relevant competing methodologies in a mixed methods approach. By utilizing such a holistic strategy, researchers are able to uncover their problem more accurately and effectively.
Most all research starts with a question, problem, or hypothesis that needsexploring, describing, explaining, understanding, predicting, changing, evaluation, or assessment (Blaikie, 2010, pp.69-70). Upon identifying, defining, and refining the research question(s), researchers are able to design their research and implement a strategy regarding the ontology, logic, concepts, and related theory in order to best solve the main problem (Blaikie, 2010, pp.81-82). In such strategy formulation, it is important to not only recognize but also account for the researcher’sgiven context or paradigm which is the overarching “set of theoretical ideas and ontological and epistemological assumptions” that may influence the study (Blaikie, 2010, p.19). Respective paradigms, therefore, frame the researcher’s way of thinking and their general ontological and epistemological beliefs.
Ontology can begenerally understood as the philosophical study of existence and reality. Blaikie (2010) affirms that social ontological assumptions such as the various facets of realism and idealism establish exactly “what kinds of social phenomena do or can exist, the conditions of their existence, and the ways in which they are related” (pp.92-93). Epistemology, on the other hand, is the science of knowledge and how we as humans know what we know. In general, those of us with a critical theoretical epistemology are attracted to methodologies such as ethnography, impact assessment, and/or phenomenology while those among us with a positivist mindset may be drawn to different approaches (experimental, correlational, and/or causational, for example) (Layder, 1993, pp.44-45; Blaikie, 2010, pp.39-40, pp.212-216).
Blaikie (2010) argues that researchers cannot avoid adopting a certain epistemological and ontological assumptions so these must be made explicit (p.2). Although knowledge and discussion of techniques of data collection are important, all choices made regarding these techniques have to do with broader methodological considerations (p.2). Selection of techniques occurs late in the process of designing research whereas “a number of fundamental decisions have to be made before methods of investigation can be considered. To focus attention on methods is to ignore the serious thinking and planning that needs to occur beforehand” in the methodology phase (Blaikie, 2010, p.9).
The next step is to actually generate knowledge whether it is theorizing in a library (formal propositions), conducting a quantitative study in the streets (factual propositions), or a “logico-empirical” mix of both (Harris, 1979, pp.26-27). There are many ways to go about producing knowledge including different time dimensions (cross-sectional, latitudinal, historical), various data collection methods (questionnaires, interviews, content analysis, etc.), and several different ways to reduce and analyze the collected data such as coding reduction and regression analysis respectively (Blaikie, 2010, pp.
[...]
-
-
-
-
Upload your own papers! Earn money and win an iPhone X. -
-
Upload your own papers! Earn money and win an iPhone X. -
-
Upload your own papers! Earn money and win an iPhone X. -
-
Upload your own papers! Earn money and win an iPhone X. -
-
Upload your own papers! Earn money and win an iPhone X.