مقایسهٔ روش‌ها

	ماتریس روش‌های ترکیبیِ ناظر بر ارزیابی	طراحی چندمرحله‌ای روش‌های ترکیبی
حوزه	طراحی پژوهش	طراحی پژوهش
خانواده	Process / pipeline	Process / pipeline
سال پیدایش	2000s (Teddlie & Tashakkori 2009; Greene 2007)	2007 (first edition of Designing and Conducting Mixed Methods Research)
پدیدآور	Teddlie & Tashakkori (matrix framework); Greene (evaluation-oriented framing)	John W. Creswell & Vicki L. Plano Clark
نوع	Mixed methods design variant	Mixed methods research design
منبع بنیادین	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	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483substitute
نام‌های دیگر	evaluation MMM, mixed methods display matrix for evaluation, evaluation-focused methods matrix, program evaluation mixed methods matrix	multiphase design, multiproject mixed methods, programmatic mixed methods, multistage mixed methods
مرتبط	5	6
خلاصه	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 multiphase mixed methods design is a sustained research program in which quantitative and qualitative strands are combined across three or more sequential phases — or across multiple related projects — to address a central program objective. Each phase builds on the prior phase's findings, making the design well-suited to long-term evaluation, intervention development, and large-scale program assessment where a single data-collection cycle cannot fully address the complexity of the research problem.