Making Decisions About Your Use Of A Mixed Methods De 618126 ✓ Solved

Making Decisions About Your Use Of A Mixed Methods Design Study De

In making decisions about your use of a mixed methods design study, describe and discuss the following: How you will determine the order in which to implement qualitative and quantitative aspects of the study How you will decide the extent to which each type of data [qualitative and quantitative] will be incorporated into your study How you will decide if the two types of data are to be combined/mixed How you will determine and apply a theory guiding the design of your study Provide at least two scholarly sources to support your responses.

Sample Paper For Above instruction

Introduction

Mixed methods research combines qualitative and quantitative approaches to provide a comprehensive understanding of research questions. When designing such studies, researchers must carefully consider the sequence of data collection, integration strategies, and theoretical frameworks guiding the design. The decisions surrounding the order of qualitative and quantitative components, the extent of their incorporation, and their mixing are critical to the validity and utility of the research outcomes. This paper discusses these decision points in detail, supported by scholarly literature.

Determining the Order of Qualitative and Quantitative Components

One fundamental decision involves the sequence in which qualitative and quantitative data are collected and analyzed. The traditional approaches include sequential explanatory, sequential exploratory, and concurrent designs. In a sequential explanatory design, researchers first collect and analyze quantitative data, then use qualitative data to explain or elaborate on the quantitative results (Creswell & Plano Clark, 2018). This approach is suitable when existing quantitative results need further context. Conversely, a sequential exploratory design begins with qualitative data collection to explore the phenomena, followed by quantitative methods to test or generalize initial findings (Creswell & Creswell, 2018).

The decision often hinges on the research question's nature. If the primary goal is to test hypotheses with numerical data, a sequential explanatory approach is appropriate. When understanding complex processes or perceptions is the focus, a sequential exploratory approach can be more effective. Concurrent designs involve collecting qualitative and quantitative data simultaneously, providing a snapshot of the phenomena and allowing integration at analysis (Tashakkori & Teddlie, 2010). This approach is advantageous when time constraints exist or when the phenomena are best studied holistically.

Deciding the Extent of Data Incorporation

The extent to which qualitative and quantitative data are incorporated depends on the study’s purpose and theoretical framework. A triangulation approach emphasizes equal emphasis on both data types to corroborate findings, enhancing validity (Fetters, Curry, & Creswell, 2013). Alternatively, a dominant status approach may prioritize one method over the other, either as primary or supplementary, depending on the research questions.

In practice, the weight assigned to each data type influences sampling, data collection instruments, and analysis methods. For instance, in a predominantly quantitative study, qualitative data might serve to provide context and depth rather than drive the findings, whereas in qualitative-dominant designs, quantitative data might serve a supportive role. The decision is also influenced by resource availability, expertise, and the specific phenomena under investigation (Plano Clark & Ivankova, 2016).

Deciding if and How to Mix Data

Mixing or integrating qualitative and quantitative data involves strategic decisions on whether and how data will be combined during analysis or interpretation. The literature distinguishes between data merging, connecting, and embedding (Bryman, 2007). Merging entails integrating data during analysis to produce joint interpretations, often using side-by-side comparisons or joint displays. Connecting involves using findings from one phase to inform subsequent phases, such as selecting qualitative samples based on quantitative results. Embedding involves embedding one type of data within a broader design, such as a qualitative component within a mainly quantitative study.

The choice depends on research aims and the degree of integration desired. Fully mixed approaches seek to synthesize data into an integrated interpretation, providing more comprehensive insights. Partial integration may suffice when one data source primarily contextualizes the other. Researchers must also consider analytical complexity and clarity in presenting findings to ensure meaningful integration (Hussein et al., 2015).

Applying a Theoretical Framework

A guiding theory provides essential direction in mixed methods design, influencing research questions, data collection, and interpretation. Theoretical frameworks such as pragmatism are common, emphasizing the practical use of both qualitative and quantitative approaches to solve real-world problems (Creswell & Plano Clark, 2018). Pragmatism supports flexibility in design decisions, encompassing the entire research process, including the sequence of data collection, analysis strategies, and integration.

Other frameworks, such as the dialectical or transformative paradigms, serve to highlight power dynamics or social justice implications, particularly in qualitative components. The selection of a guiding theory should align with the research’s philosophical stance and practical objectives. A well-articulated theoretical framework enhances transparency and coherence across the study phases and provides justification for methodological choices (Mertens, 2014).

Conclusion

Designing a mixed methods study requires thoughtful decisions regarding the sequence of qualitative and quantitative data collection, the extent of their integration, and the theoretical framework guiding these choices. Sequential, concurrent, or embedded designs are selected based on the research questions and context. The degree of emphasis placed on each data type must align with the study’s purpose and resources. Effective integration strategies—merging, connecting, or embedding—depend heavily on research aims and analytical capabilities. Finally, a guiding theoretical framework like pragmatism underpins the entire design, ensuring coherence and purpose. Careful planning at these decision points enhances the robustness and relevance of mixed methods research.

References

• Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches. SAGE Publications.
• Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
• Tashakkori, A., & Teddlie, C. (2010). Mixed methods in social & behavioral research. SAGE Publications.
• Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs— Principles and practices. Health Services Research, 48(6pt2), 2134–2156.
• Plano Clark, V. L., & Ivankova, N. V. (2016). Mixed methods research: A guide to the field. SAGE Publications.
• Bryman, A. (2007). Barriers to integrating qualitative and quantitative research. Journal of Mixed Methods Research, 1(1), 8–22.
• Hussein, J., Suresh, S., & Carter, S. (2015). Designing and conducting mixed methods research. Journal of Clinical Nursing, 24(21-22), 3157–3170.
• Mertens, D. M. (2014). Research and evaluation in Education and Psychology: Integrating diversity with quantitative, qualitative, and mixed methods. SAGE Publications.