Multiphase research
Multiphase mixed methods research design
Given that mixed methods research encompasses multiple phases, its underlying assumptions can vary depending on the specific design employed. Generally, Creswell and Plano Clark (2011) suggest that researchers often adopt pragmatism as an overarching philosophical foundation when strands are conducted concurrently.
Divide the overarching objective into distinct, manageable studies or phases. Each phase should target a specific aspect of the broader research objective. Carefully select the type of study for each phase based on the kind of data required and the objectives of that phase.
Develop research questions for each phase. Each phase should have its own set of focused research questions that align with its objectives. These questions should be designed to build upon the findings of previous phases and contribute to the larger program.
Sequential designs, where one study informs the next, are useful when earlier findings guide the direction of later phases. Concurrent designs, where multiple studies run simultaneously, are beneficial when time constraints or complementary methods allow parallel work.
Collect and analyze data for each phase. Conduct data collection in accordance with the planned methods, ensuring consistency and accuracy. Analyze the data using techniques appropriate for the phase, whether qualitative (e.g., thematic analysis) or quantitative (e.g., statistical modelling).
Integrate findings across phases. Once data from each phase is analyzed, integrate the findings to create a comprehensive understanding of the research problem. Use integration methods, such as triangulation, to merge qualitative and quantitative data, ensuring that the insights from different phases are synthesized effectively.
Iteratively refine the design. As each phase unfolds, be prepared to adapt the research design based on new insights. Refine research questions, methods, or procedures to better align with the evolving objectives of the program. For example, initial findings might reveal the need to include a new variable or address an overlooked subgroup in subsequent phases. Iterative refinement allows your research to remain flexible and responsive, ensuring that the design evolves effectively to meet the program’s goals.
Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Multi-phase Mixed Design
It is a research design that takes on collecting and analyzing data using both qualitative and quantitative methods in multiple phases. Its goal is to provide a more complete and accurate understanding of the research question by collecting and analyzing data from both qualitative and quantitative sources in multiple phases. It is to address a set of incremental research questions that all advance one programmatic research object (Creswell & Clark, 2011)
Creswell, J. W., & Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). Los Angeles: Sage Publications.
No matter how the research questions are generated, scholars writing about mixed methods research uniformly agree that the questions of interest play a central role in the process of designing any mixed methods study.
The importance of the research problem and questions is a key principle of mixed methods research design. This perspective stems from the pragmatic foundations for conducting mixed methods research where the notion of “what works” applies well to selecting the methods that “work” best to address a study’s problem and questions.
Development seeks to use the results from one method to help develop or inform the other method, where development is broadly construed to include sampling and implementation, as well as measurement decisions.
Bryan, 2006
These decisions address the different ways that the quantitative and qualitative strands of the study relate to each other. A strand is a component of a study that encompasses the basic process of conducting quantitative or qualitative research: posing a question, collecting data, analyzing data, and interpreting results based on that data (Teddlie & Tashakkori, 2009). Mixed methods studies meeting our definition of mixed methods research include at least one quantitative strand and one qualitative strand
There are four key decisions involved in choosing an appropriate mixed methods design to use in a study. The decisions are (1) the level of interaction between the strands, (2) the relative priority of the strands, (3) the timing of the strands, and (4) the procedures for mixing the strands. We examine each of these decisions along with the available options.
An important decision in mixed methods research is the level of interaction between the quantitative and qualitative strands in the study. The level of interaction is the extent to which the two strands are kept independent or interact with each other. Greene (2007) argued that this decision is the “most salient and critical” (p. 120) for designing a mixed methods study, and she noted two general options for a relationship: independent and interactive.
Priority: The study may utilize a qualitative priority where a greater emphasis is placed on the qualitative methods and the quantitative methods are used in a secondary role.
• Sequential timing occurs when the researcher implements the strands in two distinct phases, with the collection and analysis of one type of data occurring after the collection and analysis of the other type. A researcher using sequential timing may choose to start by either collecting and analyzing quantitative data first or collecting and analyzing qualitative data first.
• Multiphase combination timing occurs when the researcher implements multiple phases that include sequential and/or concurrent timing over a program of study. Examples of multiphase combination timing include studies conducted over three or more phases as well as those that combine both concurrent and sequential elements within one mixed methods program.
The four basic mixed methods designs are the convergent parallel design, the explanatory sequential design, the exploratory sequential design, and the embedded design. In addition, our list of major designs includes two examples of designs that bring multiple design elements together: the transformative design and the multiphase design.
The multiphase design. As shown in Figure 3.1f, the multiphase design combines both sequential and concurrent strands over a period of time that the researcher implements within a program of study addressing an overall pro objective. This approach is often used in program evaluation where quan and qualitative approaches are used over time to support the development, adaptation, and evaluation of specific programs. For example, a research team may want to help lower smoking rates for adolescents living in a particular Native American community. The researchers might first start by con a qualitative needs assessment study to understand the meaning of smoking and health from the perspective of adolescents in this community.
Using these results, the researchers might develop an instrument and assess the prevalence of different attitudes across the community. In a third phase, the researchers might develop an intervention based on what they have learned and then examine both the process and outcomes of this intervention program.
Multiphase (in 35066_Chapter3_CHOOSING A MixedMethodsDesign)
https://us.sagepub.com/sites/default/files/upm-binaries/35066_Chapter3.pdf
The multiphase design is an example of a mixed methods design that goes beyond the basic designs (convergent, explanatory, exploratory, and embed). Multiphase designs occur when an individual researcher or team of investigators examines a problem or topic through an iteration of connected quantitative and qualitative studies that are sequentially aligned, with each new approach building on what was learned previously to address a central program objective.
Today, multiphase designs combine sequential and concurrent aspects and are most common in large funded studies that have numerous questions being investigated to advance one programmatic objective. The purpose of the multiphase design. The purpose of this design is to address a set of incremental research questions that all advance one pro research objective. It provides an overarching methodological framework to a multiyear project that calls for multiple phases to develop an overall program of research, or evaluation. For example, in the context of program evaluation, these multiple phases may be tied to phases for needs assessment, program development, and program evaluation testing.
As a general framework, we suggest that the researcher use pragmatism as an umbrella foundation if strands are implemented concurrently and use constructivism for the qualitative compo and postpositivism for the quantitative component if the strands are sequential.
In addition to the importance of philosophical assumptions, multiphase designs also benefit from a strong theoretical perspective that provides a guiding framework for thinking about the substantive aspects of the study across the multiple phases.
The multi design allows for each individual study to address a specific set of research questions that evolve to address a larger program objective. These procedures within a given study phase, or sequence of studies, often mirror the procedures for implementing one or more of the basic mixed methods designs. In addition, researchers utilizing a multiphase design also have to care state the research questions for each phase, which both contribute to the overall program of inquiry and build upon what has been learned in previous phases, and design procedures that build on the earlier findings and results.
Strengths of the multiphase design. This design has a number of strengths:
• The multiphase design incorporates the flexibility needed to utilize the mixed methods design elements required to address a set of inter research questions.
• Researchers can publish the results from individual studies while at the same time still contributing to the overall evaluation or research program.
• The design fits the typical program evaluation and development approach well.
• The researcher can use this design to provide an overall framework for conducting multiple iterative studies over multiple years.
Challenges in using the multiphase design. While the multifaceted nature and flexibility of the multiphase design are its main strengths, they also rep the primary challenges:
• The researcher must anticipate the challenges generally associated with individual concurrent and sequential approaches within individ or subsequent phases
Like quantitative and qualitative research approaches, mixed methods research encompasses several different designs. The designs provide sound frameworks for collecting, analyzing, mixing, interpreting, and reporting quantitative and qualitative data to best address specific types of research purposes.
Researchers must match the design to their research problem and questions. Finally, researchers should articulate at least one reason why they are mixing methods.
Creswell and Plano Clark: Designing and Conducting Mixed Methods Research
A typology-based approach to mixed methods design emphasizes the classification of useful mixed methods designs and the selection and adaptation of a particular design to a study’s purpose and questions (Creswell and Plano Clark, 2010; p.55).
Using educational design research
multiphase mixed methods research design
From an educational design research perspective, Reeves (2006) focuses on a specific iterative cycle: problem analysis; solution development; iterative refinement; and reflection to produce design principles (McKenney and Reeves, 2012, p.74).
(Reeves in Akker book P.52)
Reeves, T. C. (2006) Design research from a technology perspective. In J. van den Akker, K. Gravemeijer, S. McKenney & N. Nieveen(Eds), Educational Design Research (pp.52-66). London: Routledge.
More from CGPT
Critique of the Use of Multiphase Sequential Mixed Methods Design in Design-Based Research
Introduction
Design-Based Research (DBR) has emerged as a robust methodological framework in education and learning sciences, characterized by iterative cycles of design, enactment, analysis, and redesign (Design-Based Research Collective, 2003). Its core aim is to develop both theoretical understanding and practical innovations situated in real-world settings. The integration of multiphase or multipart sequential mixed methods research designs into DBR can, on the surface, appear synergistic. However, this integration requires careful epistemological and methodological alignment to avoid compromising either the integrity of the DBR or the coherence of the mixed methods paradigm.
Compatibility of Paradigms
Multiphase or multipart sequential mixed methods research (MMR) involves conducting multiple studies—both quantitative and qualitative—either in sequence or in distinct but interconnected phases (Creswell & Plano Clark, 2018). The rationale behind this approach is to allow each method to inform subsequent stages, offering richer insights than single-method studies. This aligns well with DBR’s iterative nature, as each cycle can correspond to a methodologically distinct phase of the research (Anderson & Shattuck, 2012).
However, a critical issue emerges in the epistemological integration of the two frameworks. DBR is grounded in pragmatism and constructivism, with a strong focus on contextually-bound intervention development (Barab & Squire, 2004). MMR, although often positioned within a pragmatic paradigm, can lean toward positivist tendencies when dominated by large-scale quantitative elements (Teddlie & Tashakkori, 2009). Thus, while compatible in theory, in practice researchers must remain vigilant against epistemological drift, where the dominance of one method (often quantitative) undermines the situated, context-sensitive goals of DBR (Maxwell, 2013).
Strengths of Integration
One of the primary strengths of integrating a multiphase sequential design within DBR lies in the iterative validation of interventions. For instance, an initial qualitative phase might explore user needs and inform the design of a prototype (Cobb et al., 2003), followed by a quantitative phase to test the effectiveness of that prototype in a broader population. A subsequent qualitative phase could then explore user experiences and explain quantitative outcomes (Ivankova & Plano Clark, 2016).
This cyclical, phased structure allows for recursive learning, where data from each phase refines the intervention and the underlying theory. Importantly, such designs facilitate both formative evaluation during development and summative evaluation of outcomes—key goals of DBR (Reeves, Herrington, & Oliver, 2005).
Furthermore, multiphase designs offer a scaffolding for scaling innovations from micro (classroom) to meso (school) to macro (policy) levels, aligning with the goals of DBR to generate scalable, yet contextually meaningful, knowledge (McKenney & Reeves, 2018).
Challenges and Critiques
Despite these strengths, several challenges undermine the effectiveness of this methodological synergy:
Design Coherence and Analytical Complexity: A major challenge is maintaining methodological coherenceacross phases. Sequential designs risk becoming disjointed if the findings from one phase are not sufficiently integrated into the next (Fetters, Curry, & Creswell, 2013). In DBR, where each iteration should build cumulatively toward both theory and practice, such disjunction can fragment the research narrative.
Temporal Demands and Resource Intensity: Both DBR and multiphase MMR are time- and resource-intensive. The combination can lead to research projects spanning years, increasing vulnerability to attrition, contextual changes, and shifting stakeholder interests (Kelly, Lesh, & Baek, 2008).
Data Integration and Theorization: Effective mixed methods designs require genuine integration of qualitative and quantitative data (Greene, 2007). In DBR, integration is further complicated by the need to theorize from design enactments, not merely test pre-existing theory. A superficial application of MMR risks reducing DBR to a series of methodologically disparate episodes rather than a coherent design inquiry (Brown, 1992).
Validity and Trustworthiness: While MMR attends to internal and external validity, DBR prioritizes ecological validity and design relevance. Balancing these validity claims is non-trivial. For example, rigorous quantitative assessment may require experimental controls that conflict with DBR’s naturalistic and iterative interventions (Wang & Hannafin, 2005).
Recommendations for Practice
To mitigate these challenges, researchers should:
Adopt methodologically integrated designs from the outset, using mixed methods not as add-ons but as embedded components of DBR cycles (Johnson, Onwuegbuzie, & Turner, 2007).
Use joint displays and meta-inferences to synthesize data across phases, ensuring cumulative insight and coherence (Guetterman, Fetters, & Creswell, 2015).
Develop flexible protocols that allow iterative refinement of both the intervention and the methods used, in line with the emergent nature of DBR.
Engage in critical reflection on the ontological and epistemological assumptions of both MMR and DBR to avoid methodological tokenism.
Conclusion
The use of multiphase or multipart sequential mixed methods designs within Design-Based Research holds considerable promise for addressing complex educational challenges. When carefully aligned, such integration allows researchers to capitalize on the strengths of both traditions: the iterative, situated, and theory-building focus of DBR, and the methodological pluralism and depth of MMR. However, this synergy is not automatic. Without thoughtful integration, coherence, and reflexivity, the combined design may obscure rather than clarify the learning processes under investigation.
References
Anderson, T., & Shattuck, J. (2012). Design-based research: A decade of progress in education research? Educational Researcher, 41(1), 16–25.
Barab, S., & Squire, K. (2004). Design-based research: Putting a stake in the ground. Journal of the Learning Sciences, 13(1), 1–14.
Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. The Journal of the Learning Sciences, 2(2), 141–178.
Cobb, P., Confrey, J., diSessa, A., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9–13.
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage.
Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5–8.
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.
Greene, J. C. (2007). Mixed methods in social inquiry. Jossey-Bass.
Guetterman, T. C., Fetters, M. D., & Creswell, J. W. (2015). Integrating quantitative and qualitative results in health science mixed methods research through joint displays. Annals of Family Medicine, 13(6), 554–561.
Ivankova, N. V., & Plano Clark, V. L. (2016). Mixed methods research. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation.
Johnson, R. B., Onwuegbuzie, A. J., & Turner, L. A. (2007). Toward a definition of mixed methods research. Journal of Mixed Methods Research, 1(2), 112–133.
Kelly, A. E., Lesh, R. A., & Baek, J. Y. (Eds.). (2008). Handbook of design research methods in education: Innovations in science, technology, engineering, and mathematics learning and teaching. Routledge.
Maxwell, J. A. (2013). Qualitative research design: An interactive approach (3rd ed.). Sage.
McKenney, S., & Reeves, T. C. (2018). Conducting educational design research (2nd ed.). Routledge.
Reeves, T. C., Herrington, J., & Oliver, R. (2005). Design research: A socially responsible approach to instructional technology research in higher education. Journal of Computing in Higher Education, 16(2), 96–115.
Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Sage.
Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development, 53(4), 5–23.
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