Salīdzināt metodes

	Matrica novērtējumu orientētiem jauktajiem metodiem	Jaukto metožu matrica
Nozare	Pētījuma dizains	Pētījuma dizains
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2000s (Teddlie & Tashakkori 2009; Greene 2007)	2003–2010
Autors	Teddlie & Tashakkori (matrix framework); Greene (evaluation-oriented framing)	Tashakkori & Teddlie; Onwuegbuzie & Teddlie
Tips	Mixed methods design variant	Research design classification and planning tool
Pirmavots	Teddlie, C., & Tashakkori, A. (2009). Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences. Sage. ISBN: 978-0761930129	Onwuegbuzie, A. J., & Teddlie, C. (2003). A framework for analyzing data in mixed methods research. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 351-383). Sage.
Citi nosaukumi	evaluation MMM, mixed methods display matrix for evaluation, evaluation-focused methods matrix, program evaluation mixed methods matrix	MMR matrix, mixed-methods design matrix, research design classification matrix, mixed methods typology matrix
Saistītās	5	6
Kopsavilkums	The evaluation-oriented mixed methods matrix is a structured planning and display tool applied within program evaluation contexts. It maps evaluation questions against data sources, timing, and method types — quantitative and qualitative — in a grid format, making the integration logic explicit and auditable. Rooted in Greene's value-engaged mixed methods tradition and Teddlie and Tashakkori's matrix framework, it serves evaluators who must justify methodological choices to stakeholders while addressing multiple evaluation purposes simultaneously.	The mixed methods matrix is a systematic framework for classifying, planning, and comparing mixed methods research designs along key dimensions such as timing (concurrent vs. sequential), priority (quantitative- vs. qualitative-dominant), and point of integration. It provides researchers with a structured map to make design decisions explicit, communicate choices transparently, and locate a study within the broader mixed methods typology.