Quant research1/29/2024 ![]() These different standards affect the way researchers handle contradictory empirical findings. Lacking a common methodological background, qualitative and quantitative research methodologies have developed rather distinct standards with regard to the aims and scope of empirical science ( Freeman et al., 2007). Hence, mixed methods methodology does not provide a conceptual unification of the two approaches. However, whilst acknowledging that both strategies have their benefits, this “integration” remains purely pragmatic. These “mixed methods” approaches treat qualitative and quantitative methodologies as complementary, rather than opposing, strategies ( Creswell, 2015). ![]() In recent years, there have been attempts to integrate both strategies. Qualitative and quantitative research strategies have long been treated as opposing paradigms. In this perspective, failed replications are just as informative as successful replications, because they help to explore the scope of our theories. Inductive reasoning forces us to think about the boundary conditions of our theories and provides a framework for generalization beyond statistical testing. We conclude that quantitative research may benefit from a bottom-up generalization strategy as it is employed in most qualitative research programs. Consequently, failed replications do not question the theory per se, but help to shape its boundary conditions. From an inductive perspective, however, replication attempts serve to explore the scope of the theory. Therefore, failed replications imply a faulty theory. In deductive reasoning, replication attempts serve as empirical tests of the underlying theory. Depending on which strategy is employed, the role of replication attempts is very different. Consequently, quantitative researchers mostly adhere to a top-down strategy of generalization, whereas qualitative researchers usually follow a bottom-up strategy of generalization. Using the analytical framework of modal logic, we argue that the modes of reasoning are often not only applied to the context that has been studied empirically, but also on a between-contexts level. We apply this representationalist perspective to the problems of generalization and replication. This syntactic structure implies that sentences about other cases are justifiable by inductive reasoning. In contrast, case-based models are usually stated using context-dependent existential sentences (qualitative statements). ![]() This syntactic structure implies that sentences about individual cases are derived using deductive reasoning. Variable-based models are usually stated in the form of quantified sentences (scientific laws). Whereas quantitative research uses variable-based models that abstract from individual cases, qualitative research favors case-based models that abstract from individual characteristics. In this view, both approaches attempt to construct abstract representations of empirical relational structures. In this paper, we provide a re-interpretation of qualitative and quantitative modeling from a representationalist perspective. Foundations of Education, University of Bamberg, Bamberg, Germany.The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. The cookie is used to store the user consent for the cookies in the category "Performance". This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". The cookie is used to store the user consent for the cookies in the category "Other. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". The cookie is used to store the user consent for the cookies in the category "Analytics". These cookies ensure basic functionalities and security features of the website, anonymously. Necessary cookies are absolutely essential for the website to function properly.
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