CHAPTER 2: NON-VIOLENCE, THE HISTORY OF VIOLENCE AND THE ROLE OF THE CHURCH IN ZIMBABWE
5.5 Mixed methods research
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Mixed methodologists working primarily within the pragmatist paradigm and interested in both narrative and numeric data and their analyses.
Table 5.2 Dimensions of contrast among the three methodological communities.
Dimension of contrast Qualitative position Mixed methods position
Quantitative position
Methods Qualitative methods Mixed methods Quantitative methods
Researchers Qualitative
methodologists
Mixed methodologists Quantitative methodologists
Paradigms Constructivism (and
variants)
Pragmatism;
transformative perspective
Post-positivism Positivism
Research questions Qualitative research questions
Mixed methods
research questions (qualitative plus quantitative)
Quantitative research questions; research hypothesis
Form of data Typically narrative Narrative plus numeric Typically numeric Purpose of research (Often) exploratory
plus confirmatory
Confirmatory plus exploratory
(Often) confirmatory plus exploratory Role of theory; logic Grounded theory;
inductive logic
Both inductive and
deductive logic;
inductive-deductive research cycle
Rooted in conceptual framework or theory;
hypothetico-deductive model
Typical studies or designs
Ethnographic research and others (case study)
Mixed methods
designs, such as parallel and sequential
Correlational; survey;
experimental, quasi- experimental
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Sampling Mostly purposive Probability, purposive
and mixed
Mostly probability
Data analysis Thematic strategies:
categorical and
contextualising
Integration of thematic
and statistical
conversion
Statistical analyses:
descriptive and
inferential Validity/trust
worthiness issues
Trustworthiness;
credibility transferability
Inference quality;
inference transferability
Internal validity;
external validity
Source: Tashakkori and Teddlie (2009, p22)
A number of methodological aspects in Table 5.2 will be incorporated in this study. Of particular interest are the forms of data that will be gathered which will borrow from the mixed methods paradigm. Another important aspect is sampling, which will be mostly purposive (qualitative), while data analysis will be based on both the qualitative and mixed methods paradigms.
Typologies of mixed methods designs
Tashakkori and Teddlie (2009, p151) identify typologies of mixed methods research designs which, they advise, are not exhaustive. They argue that unlike in the quantitative tradition where a complete menu of designs is provided and the research selects the preferred one, in mixed methods designs continue to evolve and researchers creatively manipulate options suitable for specific research settings. They identify five ‘families’ of mixed methods designs from which several permutations can be made by researchers.
Parallel mixed designs. In these designs, mixing occurs in a parallel manner, either simultaneously or with some time lapse. Qualitative and quantitative questions, data collection an analysis techniques, are planned and implemented to answer related aspects of the same overarching mixed research question. Conclusions are generated through an integration of the inferences that have been obtained from the results of the qualitative and quantitative phases of the study.
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Sequential mixed designs. These are designs in which at least two phases occur chronologically, from quantitative to qualitative or vice versa. Questions or procedures of one phase emerge from, or depend on the previous phase, and research questions are related to one another and may evolve as the study unfolds. The conclusions based on the first phase lead to the formulation of design components for the next phase. The final inferences are based on the results of both phases of the study.
Conversion mixed designs. In these parallel designs, mixing occurs when one type of data is transformed and analysed both qualitatively and quantitatively by looking at related aspects of the same question. The results of parallel analyses of quantitative and qualitative data sources are integrated into a coherent set of findings and inferences.
Multilevel mixed designs. In these parallel or sequential designs qualitative data are collected at one level of analysis (e.g. the child) and quantitative data are collected at another (e.g. the family) in a parallel or sequential manner. Both types of data are analysed accordingly and the results are used to make multiple types of inferences. The different phases of research are associated with the different levels of analysis.
Fully integrated mixed designs. This is a multi-strand parallel design in which mixing of qualitative and quantitative approaches occurs in an interactive and interdependent manner at all stages of the study. At each stage one approach affects the formulation of the other, and multiple types of implementation processes occur.
Jennifer Greene (2007, p98-104) identifies five purposes of mixing different kinds of methods in one social inquiry study as follows:
Mixing methods for the purpose of triangulation. In a mixed methods study with a triangulation intent, different methods are used to measure the same phenomenon. If the results provide consistent or convergent information, then confidence in inquiry inferences is increased.
Mixing methods for purposes of complementarity. With this purpose, a mixed methods study seeks broader, deeper and more comprehensive social understandings by using methods that tap into different facets or dimensions of the same complex phenomenon.
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Results from the different methods serve to elaborate, enhance, deepen and broaden the overall interpretations and inferences from the study.
Mixing methods for purposes of development. In a mixed methods development study, the results of one method are used to inform the development of the other methods, where development is broadly construed to include sampling and implementation as well as actual instrument construction, thereby capitalising on inherent method strengths.
Mixed methods for the purposes of initiation. With initiation, Greene says, different methods are implemented to assess various facets of the same complex phenomenon, much like complementarity, but the intended result is divergence or dissonance.
Research findings may warrant further investigative analysis which in turn can lead to important insights and new knowledge.
Mixing methods for expansion. Methods can be mixed in social inquiry for the purposes of expanding the scope and range of the study. In the expansion mixed methods study, different methods are used to assess different phenomena. The scope of the study is expanded by extending methods choices to more than one methodological tradition to enable selection of the most appropriate method.
The approach in this study is that of a fully integrated mixed design that evolves from two separate components: the quantitative analysis that will measure the immediate outcomes of AVP training from pre and post-test questionnaires for the experimental and the control groups; and, the qualitative that will involve field observations, interviews, focus group discussions, document analysis and a holistic description of what actually occurred in the community where the research took place. This approach, helped to develop a better understanding of the phenomena of violence being studied.
5.5.2 Strengths and weaknesses of mixed methods research designs
All research approaches have some strengths and weaknesses. According to Tashakkori and Teddlie (2009, p152), the major advantage of mixed methods research is that it “enables
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researchers to simultaneously ask confirmatory and exploratory questions, thus verifying and generating theory in the same study.” This is supported by Hewson (2006), who highlights the potential of mixed methods designs to gain a, richer and more complete understanding of a research question by combining both qualitative and quantitative perspectives. This combination broadens the way issues are viewed, and therefore caters for what may be missed by a one dimensional quantitative or qualitative research perspective. Brewer and Hunter (2006) conclude that a multi-method approach exploits the fortunate circumstance that although all methods are imperfect, their varied strengths provide the opportunity to check and compensate for their faults. Another important strength of mixed methods is triangulation, a concept explained in detail in Section 5.7.
The main disadvantage of mixed methods designs is that they are challenging to conduct due to the complexity of running multiple research methods simultaneously. Considerable expertise is required to examine the same phenomenon using two different approaches. Integration and interpretation of qualitative and quantitative results into a coherent set of findings and inferences can be difficult. Another disadvantage cited by Hewson (2006) is the lengthy data collection and analysis phases required that leads to heavy demands on both time and funding resources.