Mixed methods research designs integrate and synergize quantitative and qualitative methods of inquiry in a single study. The aim is to provide a complete understanding of research problems compared to the use of a single research approach. This approach has been utilized since the 1970s and has gained increased interest over the last 40 years. The underlying idea is that neither a purely quantitative nor qualitative approach is sufficient to address the complexity of a research problem. Mixed method designs are particularly important for testing theories and improving validity, reliability, and trustworthiness of a research study. Typologies (systematic classification) play a crucial role in mixed designs as they inform and guide researchers on which designs to use. There are four basic types of designs: sequential, concurrent, multiphase, and compound, yielding eight categories. These categories include sequential explanatory design, sequential exploratory design, sequential transformative design, concurrent triangulation design, concurrent embedded design, concurrent transformative design, multiphase mixed design, and composite design. Key factors to consider in choosing the mixed methods design are how the quantitative and the qualitative strands will be mixed, including time and strategy. Mixed methods research follows the traditional scientific systematic approach but places particular emphasis on justifying the use of mixed methods. Researchers should also include details of the theoretical and conceptual framework and provide aids to help readers understand the integration of quantitative and qualitative data. Despite the clear benefits of the mixed methods approach in agricultural research, several obstacles exist, such as inadequate skills and training, significant resource demand, and complexity in implementation and publishing. Additionally, there is the challenge of ongoing paradigm wars between proponents of quantitative and qualitative methodologies who may hold different views regarding validity and application.

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Mixed Methods Research Designs

  • Jayne Njeri Mugwe,
  • Steven Runo

摘要

Mixed methods research designs integrate and synergize quantitative and qualitative methods of inquiry in a single study. The aim is to provide a complete understanding of research problems compared to the use of a single research approach. This approach has been utilized since the 1970s and has gained increased interest over the last 40 years. The underlying idea is that neither a purely quantitative nor qualitative approach is sufficient to address the complexity of a research problem. Mixed method designs are particularly important for testing theories and improving validity, reliability, and trustworthiness of a research study. Typologies (systematic classification) play a crucial role in mixed designs as they inform and guide researchers on which designs to use. There are four basic types of designs: sequential, concurrent, multiphase, and compound, yielding eight categories. These categories include sequential explanatory design, sequential exploratory design, sequential transformative design, concurrent triangulation design, concurrent embedded design, concurrent transformative design, multiphase mixed design, and composite design. Key factors to consider in choosing the mixed methods design are how the quantitative and the qualitative strands will be mixed, including time and strategy. Mixed methods research follows the traditional scientific systematic approach but places particular emphasis on justifying the use of mixed methods. Researchers should also include details of the theoretical and conceptual framework and provide aids to help readers understand the integration of quantitative and qualitative data. Despite the clear benefits of the mixed methods approach in agricultural research, several obstacles exist, such as inadequate skills and training, significant resource demand, and complexity in implementation and publishing. Additionally, there is the challenge of ongoing paradigm wars between proponents of quantitative and qualitative methodologies who may hold different views regarding validity and application.