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| Suy luận tổng hợp theo phương pháp hỗn hợp ưu tiên định lượng× | Thiết kế phương pháp hỗn hợp ưu tiên định lượng× | |
|---|---|---|
| Lĩnh vực | Thiết kế nghiên cứu | Thiết kế nghiên cứu |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 2003–2007 | 2003–2009 |
| Người khởi xướng≠ | Tashakkori & Teddlie (meta-inference concept); Creswell & Plano Clark (dominance weighting framework) | Creswell & Plano Clark; Teddlie & Tashakkori |
| Loại≠ | Mixed methods integration procedure | Mixed methods research design |
| Công trình gốc≠ | Tashakkori, A., & Teddlie, C. (Eds.). (2003). Handbook of Mixed Methods in Social and Behavioral Research. Sage. ISBN: 978-0761920731 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Tên gọi khác | QUAN-dominant meta-inference, quantitatively weighted meta-inference, QUAN-priority integration inference, quantitative-weighted mixed inference | QUAN-dominant mixed methods, quantitative-dominant mixed methods, quan-priority design, quantitative-first mixed methods |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | Quantitative-dominant mixed methods meta-inference is an integration procedure in which the researcher draws an overarching conclusion by combining inferences from both quantitative and qualitative strands, while explicitly assigning greater evidential weight to the quantitative results. The qualitative strand serves a supporting, elaborating, or contextualizing role rather than an equal voice in the final interpretation. | Quantitative-priority mixed methods design is a research approach in which quantitative data and analysis carry the primary explanatory weight, while qualitative data play a supplementary or corroborating role. The researcher collects and analyzes quantitative data first (or concurrently with greater emphasis), then uses qualitative findings to elaborate, explain, or contextualize the statistical results. Priority and sequence together define where integration occurs and how each strand informs the other. |
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