Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Множественный визуальный анализ на основе кейсов× | Сравнительное исследование случая× | |
|---|---|---|
| Область | Качественные методы | Качественные методы |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2000s–2010s (convergence of case study and visual research traditions) | 1984 (Yin); 1995 (Stake) |
| Автор метода≠ | Synthesised from Robert E. Stake (multiple case design) and Gillian Rose / visual methodologies scholars | Robert K. Yin; Robert E. Stake |
| Тип≠ | Qualitative comparative research design | Qualitative / mixed research design |
| Основополагающий источник≠ | Stake, R. E. (2006). Multiple Case Study Analysis. Guilford Press. ISBN: 978-1593852481 | Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage. ISBN: 978-1506336169 |
| Другие названия | multi-case visual analysis, comparative visual case study, cross-case image analysis, MCVA | cross-case study, multi-site case study, multiple case study design, comparative case analysis |
| Связанные≠ | 5 | 4 |
| Сводка≠ | Multiple case-based visual analysis is a qualitative design that systematically examines visual materials — photographs, drawings, maps, video stills, or image-rich documents — across two or more purposefully selected cases. By combining Robert Stake's multiple case study logic with visual analysis frameworks, it enables researchers to identify both case-specific visual meanings and cross-case patterns, producing richer comparative insights than either method yields alone. | Comparative case study is a qualitative research design in which two or more bounded cases are studied in depth and then systematically compared to identify similarities, differences, and patterns across contexts. Rooted in Yin's replication logic and Stake's multiple case framework, it is particularly suited to questions that ask how or why a phenomenon unfolds differently — or similarly — across distinct settings, populations, or time periods. |
| ScholarGateНабор данных ↗ |
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