Design-Based Explanatory Sequential Mixed Methods Design
Also known as: DBR explanatory sequential design, design-based explanatory mixed methods, design research explanatory sequential, DBEMM explanatory sequential
This design embeds an explanatory sequential mixed methods structure — quantitative data collection followed by qualitative follow-up — within iterative design-based research (DBR) cycles. The quantitative phase establishes what is happening with a designed intervention or learning environment; the qualitative follow-up explains why. Results then feed directly back into redesign, making the method especially powerful in educational and instructional technology research where both statistical patterns and contextual understanding are needed to refine innovations.
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When to use it
Use this design when you are studying an educational intervention or designed artifact and need both statistical evidence of outcomes and rich explanations of why those outcomes occur, with the explicit aim of refining the design over multiple cycles. It is most appropriate in educational technology, instructional design, curriculum development, and professional learning research. You need sufficient sample size for meaningful quantitative analysis (typically n > 30 for Phase 1) and access to a purposive sub-sample willing to participate in qualitative follow-up. Avoid this design when time or resource constraints prevent iterative cycles, when the intervention is fixed and not open to redesign, or when the research question is purely exploratory and does not start with quantitative measurement.
Strengths & limitations
- Combines statistical breadth with qualitative depth, producing explanations grounded in representative data rather than convenience sampling.
- The iterative design cycle ensures findings are actionable: explanations directly feed redesign rather than stopping at publication.
- Purposive connection between phases increases the credibility of qualitative explanations by anchoring them to documented quantitative patterns.
- Appropriate for real-world educational settings where both accountability (numbers) and improvement (understanding) are required.
- Generates both practical design knowledge and transferable theoretical principles.
- Sequential execution is time-intensive; completing both phases and a redesign cycle within a single academic year is challenging.
- Requires competence in both quantitative analysis and qualitative inquiry — teams or mixed-expertise collaboration are often necessary.
- The sample for the quantitative phase must be large enough for meaningful statistics, which can be difficult when studying novel or niche interventions.
- Iterative cycles depend on sustained access to participants and a design that the host context actually allows to be modified.
Frequently asked
How is this different from a plain explanatory sequential mixed methods design?
The structural sequence — quantitative then qualitative — is the same. The difference lies in purpose and frame: in a design-based variant, the study is embedded in an iterative improvement cycle where the integrated findings directly inform a redesigned intervention. A plain explanatory sequential study typically concludes with explanation; a design-based version continues with redesign and a new evaluation cycle, generating both theoretical and practical knowledge.
How many design cycles are needed?
There is no fixed number. Foundational DBR literature suggests at least two to three cycles are needed to move from initial prototyping to a refined, theory-grounded design. In practice, resource and timeline constraints often produce one or two full cycles within a single study, with later cycles reported as follow-up work. What matters is that each cycle is theory-driven and that interim findings are transparently linked to design changes.
Can I use this design in a dissertation?
Yes, but scope it carefully. A dissertation that attempts three full design cycles within a single enrollment period is rarely feasible. A practical approach is one complete explanatory sequential cycle — quantitative data collection, qualitative follow-up, integration — plus a documented redesign proposal or a limited second cycle. The design-based framing must be genuine: the intervention must actually be modifiable based on your findings.
What sample size do I need for Phase 1?
Enough to detect meaningful group differences or test hypotheses with adequate power — typically at least 30 participants for simple comparisons, and larger for regression or sub-group analyses. A power analysis based on the expected effect size and your statistical tests is the appropriate starting point. Phase 2 (qualitative) usually involves 6–20 purposively selected participants drawn from the Phase 1 sample.
How do I document the connection step?
Create an explicit selection matrix: list the quantitative outcome pattern (e.g., high performers, low performers, outliers), the criteria for selection, and the participants chosen for each category. Report this matrix in the methods section so readers can evaluate whether the qualitative sample genuinely represents the range of quantitative outcomes.
Sources
- Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications. ISBN: 978-1483344379
- McKenney, S., & Reeves, T. C. (2018). Conducting Educational Design Research (2nd ed.). Routledge. ISBN: 978-1138574816
How to cite this page
ScholarGate. (2026, June 3). Design-Based Explanatory Sequential Mixed Methods Design. ScholarGate. https://scholargate.app/en/research-design/design-based-explanatory-sequential-mixed-methods-design
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Concurrent Triangulation Mixed Methods DesignResearch Design↔ compare
- Design-based ResearchField Methods↔ compare
- Embedded Explanatory Sequential Mixed MethodsResearch Design↔ compare
- Explanatory Sequential Mixed Methods DesignResearch Design↔ compare
- Exploratory Sequential Mixed Methods DesignResearch Design↔ compare
- Multiphase Mixed Methods DesignResearch Design↔ compare