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The Quality of ‘Good’ Mixed Methods Research: Development and Discussion of an Orientation Framework

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Triangulation und Mixed-Methods

Part of the book series: Studien zur Schul- und Bildungsforschung ((SZSBF,volume 76))

Abstract

Beyond entrenched methodological disputes, Mixed Methods attempt to promote a combination of qualitative and quantitative materialities in a single study, suitable to study the subject of research and aiming at understanding social phenomena in a more comprehensive way than it would be possible with a monomethodological approach. This article focuses on the meaning and relevance of criteria for evaluating the quality of Mixed Methods Research. A complex and ambivalent state of discussion is presented based on current research literature, and the applicability of criteria for research projects is discussed.

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Notes

  1. 1.

    Cf. in this regard Denzin (2012), Gage (1989).

  2. 2.

    However, problems and difficulties are found not only in ontological and epistemological perspectivation and the combination of qualitative and quantitative data, but the integrative aspect of relevance in corresponding studies is also discussed in detail. There are also many challenges linked to the integration concept and its irrefutable centrality in Mixed Methods research. Thus, for example, Uprichard and Dawney (2016) question whether the integration of qualitative and quantitative data is always possible and/or also appropriate, and whether it results from a coherent representation and reconstruction of the subject of research and the social reality/realities. Instead of integration, empirical social research, particularly that used in Mixed Methods, would have to focus far more on breaks and contradictions in the data material and less on an orthodox and enforced combination that is as coherent as possible (cf. Ibid, also Fielding 2012, p. 127).

  3. 3.

    At the same time, the argument against standards is also that they are guidelines issued by scientists or entire communities, who develop such standards, while remaining unclear, however, as to who is judging the quality of these decisions, whereby for Creswell (2015), power issues are also directly involved. It is also critically added that standards certainly have the potential to establish structures and boundaries of what is permissible and/or impermissible, and that this can mean a narrowing of creative potential, which ultimately forces epistemological progress into a pre-specified corset.

  4. 4.

    Here, a differentiation between different facets of quality evaluation is essential, whereby criteria and standards, as well as indicators and their discursive negotiation, are of importance. Criteria are characterised accordingly as features that permit statements regarding the quality of empirical studies on a scientific theory basis, and which are supported in particular by knowledge obtained through empirical studies. Standards are in turn regarded as being normative specifications, “the characterisation of which must be inherent at least to the respective quality indicators, so that it can be assumed that quality […] is poor, adequate or good” (Döring and Bortz 2016, p. 83, translated by author). Indicators permit statements to be made regarding the quality of a scientific study and can be measured and reconstructed (cf. Ibid.).

  5. 5.

    These include (a) using and/or implementing quantitative and qualitative components in accordance with their respective standards, (b) the necessity of transparency in the research process, (c) a reference to the research question with regard to the necessity of using Mixed Methods, (d) presenting the research design and discussing it with regard to the appropriateness in relation to the research questions, (e) a convincing justification for the Mixed Methods use, and (f) the necessity for integrating the qualitative and quantitative data (Bryman 2014).

  6. 6.

    Here, a differentiation is made between: (a) sample integration: this means the benefits gained by integrating qualitative and quantitative materialities with regard to meta-inferences; (b) the inside-outside problem describes the extent to which researchers appropriately and in a differentiated way reflect perspectivations on investigation materialities, such as between description and explanations. (c) Weakness minimisation means a reflection as to the extent to which the weaknesses of one approach are compensated by the strengths of the other; (d) sequential series is the extent to which the potentiality is given for minimising meta-inference through the inversion of the sequence of the quantitative and qualitative phases. (e) Conversion in turn means the extent to which integrative conclusions can be reached accordingly through quantification or qualification. (f) Paradigmatic mixing the extent to which epistemological, ontological, axiological and methodological shared beliefs, which form the basis for the respective methods, have been combined; (g) commensurability means “the extent to which the meta-inferences made reflect a mixed worldview based on the cognitive process of Gestalt switching and integration” (Onwuegbuzi and Johnson 2006, p. 57). (h) Multiple validity means the extent to which the legitimisation of the quantitative and qualitative components result from its extensive elements and the mixing of the results. (i) Finally, Onwuegbuzi and Johnson refer to a political legitimisation dimension: “The extent to which the consumers of Mixed Methods research value the meta-inferences stemming from both the quantitative and qualitative components of a study” (Ibid.).

  7. 7.

    These in turn include different subdimensions, which are of relevance in the evaluation of the quality of Mixed Methods studies.

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Völcker, M. (2019). The Quality of ‘Good’ Mixed Methods Research: Development and Discussion of an Orientation Framework. In: Lüdemann, J., Otto, A. (eds) Triangulation und Mixed-Methods. Studien zur Schul- und Bildungsforschung, vol 76. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-24225-1_4

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