مقایسهٔ روش‌ها

	روش‌های ترکیبی مداخله مبتنی بر طراحی	طرح روش‌های ترکیبی اکتشافی متوالی
حوزه	طراحی پژوهش	طراحی پژوهش
خانواده	Process / pipeline	Process / pipeline
سال پیدایش	2003–2010s (convergence of DBR and mixed methods traditions)	1990s–2000s (codified by ~2007)
پدیدآور	Design-Based Research Collective; Creswell & Plano Clark (mixed methods framework)	John W. Creswell & Vicki L. Plano Clark
نوع	Mixed methods research design variant	Mixed methods research design
منبع بنیادین	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage Publications. ISBN: 978-1483344452	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379
نام‌های دیگر	DBR intervention mixed methods, design-based intervention study, design experiment with mixed methods, intervention design-based mixed methods	QUAL → QUAN design, exploratory sequential design, instrument-development design, theory-building mixed methods
مرتبط	6	6
خلاصه	Design-based intervention mixed methods is a research design that embeds both quantitative and qualitative data collection within iterative intervention cycles drawn from design-based research (DBR). The approach systematically tests and refines a practical intervention — typically an educational program, curriculum, or organizational solution — while using qualitative data to explain why and how the intervention works, and quantitative data to assess its measurable impact. Iteration between design, testing, and revision is the hallmark of this approach.	The exploratory sequential mixed methods design is a two-phase research framework in which a qualitative phase is conducted first to explore a poorly understood phenomenon, and the findings then inform a subsequent quantitative phase — typically to develop and test a survey instrument, measure a theory, or generalize qualitative insights to a larger population. The qualitative strand guides what is measured; the quantitative strand tests or extends those findings at scale.