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Sunday, August 25, 2019


Mixed Methods Research
Mixed methods research is a a growing area of methodological choice for many academics and researchers from across a variety of discipline areas. With the development and perceived the legitimacy of both quantitative and qualitative research in the social and human sciences, mixed methods research, employing the combination of both quantitative and qualitative research has gained popularity. This popularity is because research methodology continues to evolve and develop and mixed methods research is another step forward, utilizing the strengths of both qualitative and quantitative methods.
Mixed methods research is basically defined as the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts or language into a single study. Philosophically, it is the “third wave” or third research movement, a movement that moves past the paradigm wars by offering a logical and practical alternative. It is an expansive and creative form of research, not a limiting form of research. It is inclusive, pluralistic and complementary. Mixed methods research focuses on collecting, analyzing and mixing both quantitative and qualitative data in a single study or series of studies. Its central premise is that the use of quantitative and qualitative approaches in combination provides a better understanding of research problems than either approach alone. This better understanding results because mixed methods offer strengths that offset the weaknesses of separately applied quantitative and qualitative research methods. It also encourages the collection of more comprehensive evidence for study problems; helps answer questions that quantitative or qualitative methods alone cannot answer. Mixed methods research is important today because of the complexity of problems that need to be addressed, the rise of interest in qualitative research and the practical need to gather multiple forms of data for diverse audiences.
Johnson, Onwuegbuzie, and Turner define mixed methods research “is the type of research in which a researcher or a team of researchers combines elements of quantitative and qualitative approaches (e.g. use of qualitative and quantitative viewpoints, data collection, analysis, and inference techniques) for the purpose of breadth and depth of understanding and corroboration”. Also, the Journal of Mixed Methods, in its call for paper, mixed-methods defined mixed methods research as “research in which investigator collects, analyses, mixes and draws inferences from both qualitative and quantitative data in a single study or a program of inquiry”.
Qualitative and Quantitative Data
As per the definition, mixed methods research involves both collecting and analyzing quantitative and qualitative data. Quantitative data includes closed-ended information such as that found on attitude, behavior, or performance instruments. Sometimes quantitative information is found in documents such as census records or attendance records. The analysis consists of statistically analyzing scores collected on instruments, checklists or public documents to answer research questions or to test hypotheses.
In contrast, qualitative data consists of open-ended information that the researcher gathers through interviews with participants. The general, open-ended questions asked during these interviews allow the participants to supply answers in their own words. Also, qualitative data may be collected by observing participants or sites of research, gathering documents from a private or public source, etc. The analysis of the qualitative data (word or text or images) typically follows the path of aggregating the words or images into categories of information and presenting the diversity of ideas gathered during data collection.
Mixing of Data
The mixing of data is a unique aspect of the definition of the mixed methods research. By mixing the datasets, the researcher provides a better understanding of the problem than if either data set had been used alone. There are three ways in which the mixing occurs: merging or converging the two data sets by actually bringing them together, connecting the two datasets by having built on the other, or embedding one dataset within the other so that one type of data provides a supportive role for the other dataset. In short, it is not enough to simply collect and analyze qualitative and quantitative data; they need to be mixed in some way so that together they form a more complete picture then they do when standing alone.
Table 1 Characteristics of Quantitative, Mixed and Qualitative methods
Characteristics
Quantitative Methods
Mixed Methods
Qualitative Methods
Degree Of Predetermined Nature
Predetermined
Both Predetermined And Emerging Methods
Emerging Methods
Questions
Instrument Based
Both Open- And Closed -Ended
Open-Ended
Data Types
Performance, Attitude, Observational, And Census
Multiple Forms Of Data Drawing On All Possibilities
Interview, Observation, Document,
And Audiovisual
Analysis
Statistical Analysis
Statistical And Text Analysis
Text And Image Analysis
Interpretation
Statistical Interpretation
Across Databases Interpretation
Themes, Patterns Interpretation
May Employ These Strategies Of Inquiry
Surveys, Experiments
Sequential, Convergent, And Embedded
Phenomenology, Grounded Theory, Ethnography, Ease Studies, Narrative
Basic Characteristics
  • Design can be based on either or both perspectives.
  • Research problems can become research questions and/or hypotheses based on prior literature, knowledge, experience, or the research process.
  • Sample sizes vary based on methods used.
  • Data collection can involve any technique available to researchers.
  • Interpretation is continual and can influence stages in the research process(‘Mixed Methods Research Designs | Research Rundowns’, n.d.).
Mixed Methods Research Process Model
The mixed methods research process model comprises eight distinct steps:
  • Interpretation of data;
  • Analysis of data;
  • Collection of data;
  • Selection of mixed-method or mixed-model research design;
  • Determining the research question;
  • Determining whether a mixed the research procedure is appropriate;
  • Legitimization of data; and
  • Drawing conclusions and writing the final report(kudrat, 2015).
Figure1. Mixed Methods Research Design


Why Use Mixed Methods?
The simple answer is to overcome the limitations of a single design. A detailed answer involves:
·         To explain and interpret.
·         To explore a phenomenon.
·         To develop and test a new instrument.
·         To serve a theoretical perspective.
·         To complement the strengths of a single design.
·         To overcome the weaknesses of a single design.
·         To address a question at different levels.
·         To address a theoretical perspective at different levels.
What are some strengths?
  • Can be easy to describe and to report.
  • Can be useful when unexpected results arise from a prior study.
  • Can help generalize, to a degree, qualitative data.
  • Helpful in designing and validating an instrument.
  • Can position research in a transformative framework.
What are some weaknesses?
  • Time required.
  • Resolving discrepancies between different types of data.
  • Some designs generate unequally evidence.
  • Can be difficult to decide when to proceed in sequential designs.
  • Little guidance on transformative methods.
TYPES
Sequential explanatory design. This design involves the collection and analysis of quantitative data followed by the collection and analysis of qualitative data. The priority is given to the quantitative data, and the findings are integrated during the interpretation phase of the study.
Example: The researcher collects data about people’s risk and benefit perceptions of red meat using a survey and follows up with interviews with a few individuals who participated in the survey to learn in more detail about their survey responses (e.g., to understand the thought process of people with low-risk perceptions (‘Mixed methods research’, n.d.).
sequential exploratory design. In this design, qualitative data collection and analysis are followed by quantitative data collection and analysis. The priority is given to the qualitative aspect of the study, and the findings are integrated during the interpretation phase of the study
ExampleThe researcher explores people's beliefs and knowledge regarding nutritional information by starting with in-store interviews and then uses an analysis of the information to develop a survey instrument that is administered later to a sample from a population.
Concurrent triangulation. In this design only one data collection phase is used, during which quantitative and qualitative data collection and analysis are conducted separately yet concurrently. The findings are integrated during the interpretation phase of the study. Usually, equal priority is given to both types of research.
Example:The  researcher uses a survey to assess people’s self-reported food safety practices and also observes those practices in their natural environment. By comparing the two types of data, the researcher can see if there is a match between what people think they are doing and what they are actually doing in terms of food safety practices.

Concurrent nested. In this design only one data collection phase is used, during which a predominant method (quantitative or qualitative) nests or embeds the other less priority method (qualitative or quantitative, respectively). This nesting may mean that the embedded method addresses a different question than the dominant method or seeks information from different levels. The data collected from the two methods are mixed during the analysis phase of the project.
Example:The researcher collects data to assess people’s knowledge and risk perceptions about genetically modified food by using a survey instrument that mixes qualitative (open-ended) and quantitative (closed-ended) questions, and both forms of data are integrated and analyzed.


Conclusion
Mixed methods research actually has a long history in research practice. It is now time that all researchers and research methodologists formally recognize the third research paradigm and begin systematically writing about it and using it. Generally, contingency theory is recommended for research approach selection, which accepts that quantitative, qualitative and mixed research are all superior under different circumstances and it is the researcher’s task to examine the specific contingencies and make the decision about which research approach or combination of approaches, should be used in a specific study. As noted by Sechrest and Sidana, growth in the mixed method movements has the potential to reduce some of the problems associated with singular methods. By narrowing the divide between quantitative and qualitative researches, mixed-method research has a great potential to promote shared responsibility in the quest for attaining accountability for educational quality. The time has come for mixed methods research.


Reference
·         kudrat. (2015, February 14). Mixed Methods Research. Retrieved 25 August 2019, from Academike website: https://www.lawctopus.com/academike/mixed-methods-research/
·         Mixed methods research. (n.d.). Retrieved 25 August 2019, from http://resourcecentre.foodrisc.org/mixed-methods-research_185.html
·         Mixed Methods Research Designs | Research Rundowns. (n.d.). Retrieved 25 August 2019, from https://researchrundowns.com/mixed/mixed-methods-research-designs/

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