Comparar métodos

	Diseño Participativo Concurrente Embebido de Métodos Mixtos	Diseño de Métodos Mixtos de Triangulación Concurrente
Campo	Diseño de investigación	Diseño de investigación
Familia	Process / pipeline	Process / pipeline
Año de origen	2000s–2010s	2007 (formally named in Creswell & Plano Clark, 1st ed.)
Autor original	Creswell & Plano Clark (embedded design); Mertens, Tashakkori & Teddlie (participatory frameworks)	John W. Creswell & Vicki L. Plano Clark
Tipo	Mixed methods research design	Mixed methods research design
Fuente seminal	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. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Sage. ISBN: 978-1412975179
Alias	participatory embedded concurrent design, action-research embedded mixed methods, PAR concurrent embedded design, community-based embedded mixed methods	convergent parallel design, triangulation design, QUAN+QUAL concurrent design, simultaneous triangulation
Relacionados	4	5
Resumen	Participatory concurrent embedded mixed methods is a research design that combines a participatory or community-based action research framework with an embedded concurrent data structure — simultaneously collecting dominant and supplementary data strands from community stakeholders who are active co-investigators rather than passive subjects. The embedded strand (typically qualitative) is nested within the dominant strand (typically quantitative) and both are gathered at the same time while community members guide priorities, instruments, and meaning-making throughout.	The concurrent triangulation mixed methods design collects quantitative and qualitative data simultaneously, analyzes each strand independently, and then merges the results to assess whether the two data sources corroborate one another. Often called the convergent parallel design, it is one of the foundational configurations in mixed methods research and is chosen specifically when the researcher wants to cross-validate or triangulate findings from two distinct methodological traditions.