So sánh phương pháp

	Thiết kế phương pháp hỗn hợp giải thích tuần tự nhúng	Thiết kế phương pháp hỗn hợp giải thích tuần tự
Lĩnh vực	Thiết kế nghiên cứu	Thiết kế nghiên cứu
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2007–2011	2007 (formalized in Creswell & Plano Clark's mixed methods typology)
Người khởi xướng	John W. Creswell & Vicki L. Plano Clark	John W. Creswell & Vicki L. Plano Clark
Loại	Mixed methods research design	Mixed methods research design
Công trình gốc	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379
Tên gọi khác	embedded QUAN→QUAL design, nested explanatory sequential design, embedded mixed methods with explanatory sequence, QUAN(qual) explanatory embedded design	explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design
Liên quan	5	6
Tóm tắt	The embedded explanatory sequential mixed methods design combines two structural logics: the explanatory sequential framework (a dominant quantitative phase followed by a qualitative follow-up) and the embedded design principle (one method nested within the other to serve a supporting role). Quantitative data are collected and analyzed first to identify patterns or outcomes; qualitative data are then gathered — embedded within or alongside the QUAN phase — to explain, interpret, or contextualize those findings. The result is a study in which numerical results drive the inquiry and qualitative voices provide the explanatory depth.	The explanatory sequential mixed methods design is a two-phase research approach in which a quantitative study is conducted first, and qualitative data are then collected specifically to help explain or elaborate the initial quantitative results. The quantitative phase carries greater priority; the qualitative phase is purposefully built around the findings — such as surprising results, outliers, or statistically significant relationships — that need deeper interpretation.