Methoden vergleichen

	Design-basiertes Multilevel Mixed Methods	Design-basierte Interventions-Mixed-Methods
Fachgebiet	Forschungsdesign	Forschungsdesign
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	2000s–2010s	2003–2010s (convergence of DBR and mixed methods traditions)
Urheber	Synthesized from Design-Based Research Collective (2003) and Creswell & Plano Clark multilevel mixed methods typology	Design-Based Research Collective; Creswell & Plano Clark (mixed methods framework)
Typ	Mixed methods research design	Mixed methods research design variant
Wegweisende Quelle	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications. ISBN: 978-1483344379	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage Publications. ISBN: 978-1483344452
Aliasnamen	DB-MLMM, multilevel design-based mixed methods, design-based multilevel research, DBR multilevel mixed design	DBR intervention mixed methods, design-based intervention study, design experiment with mixed methods, intervention design-based mixed methods
Verwandt	3	6
Zusammenfassung	Design-based multilevel mixed methods combines the iterative, context-sensitive logic of design-based research (DBR) with the analytical power of multilevel data structures and the explanatory depth of mixed methods research. It is used predominantly in educational and organizational research where participants are nested within settings (e.g., students within classrooms within schools) and where a designed intervention must be tested, refined, and understood at multiple organizational levels simultaneously.	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.