So sánh phương pháp

	Thiết kế phương pháp hỗn hợp giải thích tuần tự có sự tham gia	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	2000s-2010s	2007 (formalized in Creswell & Plano Clark's mixed methods typology)
Người khởi xướng	Creswell & Plano Clark (explanatory sequential structure); Mertens (transformative/participatory lens)	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 Publications. 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	participatory QUAN-to-QUAL design, community-based explanatory sequential design, transformative explanatory sequential mixed methods, participatory two-phase sequential design	explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design
Liên quan	5	6
Tóm tắt	The participatory explanatory sequential mixed methods design combines the two-phase QUAN-to-QUAL structure of the explanatory sequential design with a participatory or transformative worldview. Community members and stakeholders are involved as collaborators — not merely subjects — across all stages, from formulating research questions to interpreting results. Quantitative data are collected and analyzed first; findings that need deeper explanation then drive a second, qualitative phase conducted with and by the community.	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.