Abstract
In this paper we introduce the concept of contextual mitigating factors (CMFs) as an analytical tool for interrogating the contextual landscapes that situate one’s research. While we understand that much work has been done on the importance of identifying context in research programs, we continue to stress the importance of developing contextually rich and useful descriptions. The importance of developing contextually rich descriptions that are inclusive of CMFs in the research process to include research designs is underscored in this paper. In using the term context, we are referring to the conglomerate of CMFs that situate, define and occupy complex systems of multiple spaces that create, shape, and continuously modify, contextual landscapes. Complex systems thinking is our basis for understanding that CMFs are a continuous set of socio-historical-political contextual constructs, fluid and dynamic, simultaneously interweaving socially constructed places together. By doing so, we stress that conceptually it is important for a researcher to understand that context is positioned and, as such, all phenomena studied are situated. In order to fully grasp how data presented have been positioned, we underscore the importance of the development of radical doubt (RD) which leads to tactical understanding (TU) by both researchers and consumers of research. Commensurate to the development of RD and TU is understanding how both the researcher and consumer of research have been positioned by their ontological, epistemological and axiological frameworks. Through several examples we demonstrate how CMF analysis as a tool can contribute to researchers abilities to further enhance their analysis of the complexity of socio-educational phenomena such as the science, technology, engineering and mathematics intervention pipelines. Accordingly, we present CMF analysis as a framework with the intent of adding to existing methodologies as opposed to CMF analysis as an exclusive research pathway. We conclude by discussing implications for sponsoring agencies by drawing attention to the potential impact of CMF analysis on evaluating research designs.
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