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Front. Educ. | doi: 10.3389/feduc.2019.00053

Linearity vs. Circularity? On some Common Misconceptions on the Differences in the Research Process in Qualitative and Quantitative Research

  • 1Technische Universität Berlin, Germany

Methodological discussions often oversimplify by distinguishing between ‘the’ quantitative and ‘the’ qualitative paradigm and arguing that quantitative research processes are organized in a linear, deductive way while qualitative research processes are organized in a circular and inductive way. When comparing two selected quantitative traditions (survey research and big data research) with three qualitative research traditions (qualitative content analysis, grounded theory and social-science hermeneutics), a much more complex picture is revealed: The only differentiation that can be upheld is how of ‘objectivity’ and ‘intersubjectivity’ are defined. In contrast, all research traditions agree that partiality is endangering intersubjectivity and objectivity. Countermeasures are self-reflexion and transforming partiality into perspectivity by using social theory. Each research tradition suggests further countermeasures such as falsification, triangulation, parallel coding, theoretical sensitivity and interpretation groups. When looking at the overall organization of the research process, the distinction between qualitative and quantitative research cannot be uphold. Neither is it a continuum between quantitative research, content analysis, grounded theory and social-science hermeneutics. Rather, grounded theory starts inductively and with a general research question at beginning of analysis which is focused during selective coding. The later research process is organized in a linear way, making strong use of theoretical sampling. All other traditions start research deductively and formulate the research question as precisely as possible at the beginning of the analysis and then organize the overall research process in a linear way. In contrast, data analysis is organized in a circular way. One consequence of this paper is that mixing and combining qualitative and quantitative methods becomes both easier (because the distinction is not as grand as it seems at first sight) and more difficult (because some tricky issues of mixing specific to mixing specific type of methods are usually not addressed in mixed methods discourse).

Keywords: Research process, mixed methods, survey research, big data, Qualitative content analysis, Grounded Theory (GT), hermeneutics, sociology of knowledge, Perspectivity, Objectivity, intersubjectivity, induction, deduction, abduction, Social-Science Hermeneutics

Received: 30 Jun 2018; Accepted: 22 May 2019.

Edited by:

Douglas F. Kauffman, Medical University of the Americas – Nevis, United States

Reviewed by:

Barbara Hanfstingl, Alpen-Adria-Universität Klagenfurt, Austria
Jana Uher, University of Greenwich, United Kingdom  

Copyright: © 2019 Baur. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Nina Baur, Technische Universität Berlin, Berlin, Germany, nina.baur@tu-berlin.de