So sánh phương pháp

	Tổng quan thiết kế Ma trận Phương pháp Trộn Ưu tiên Định tính	Thiết kế phương pháp hỗn hợp tuần tự khám phá, ưu thế định tính
Lĩnh vực	Thiết kế nghiên cứu	Thiết kế nghiên cứu
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2003–2009	2003–2007
Người khởi xướng	Charles Teddlie & Abbas Tashakkori (matrix framework); qualitative-dominant weighting drawn from Jennifer Greene and David Morgan	Creswell & Plano Clark; Morse (priority notation)
Loại	Mixed methods research design variant	Mixed methods research design
Công trình gốc	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: 978-1483344379
Tên gọi khác	QUAL-dominant MMM, qualitative-priority mixed methods matrix, QUAL-weighted matrix design, qual-dominant typology matrix	QUAL-dominant exploratory sequential design, qual-first exploratory mixed methods, qualitative-priority exploratory sequential MMR, QUAL → quan exploratory design
Liên quan	5	6
Tóm tắt	The qualitative-dominant mixed methods matrix is a design variant in which the researcher selects and positions a specific mixed methods design within a typological matrix — organized by timing (sequential vs. concurrent) and paradigm weighting — while assigning greater priority to the qualitative strand. Quantitative data play a supporting, supplementary role, and the final inferences are grounded primarily in qualitative findings.	This design begins with a substantive qualitative phase (QUAL) that drives the study, followed by a smaller quantitative phase (quan) used to test, refine, or extend qualitative findings to a broader sample. The qualitative strand holds priority in both scope and interpretation; the quantitative strand serves a confirmatory or generalisability function. It is particularly well suited when theory or instrument development must be grounded in participants' own frameworks before statistical testing.