Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Сравнителен интерпретативен феноменологичен анализ× | Сравнително казусно изследване× | |
|---|---|---|
| Област | Качествени методи | Качествени методи |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1996 (IPA); comparative applications prominent from 2000s onward | 1984 (Yin); 1995 (Stake) |
| Създател≠ | Jonathan A. Smith (IPA); comparative extension by IPA research community | Robert K. Yin; Robert E. Stake |
| Тип≠ | Qualitative research design | Qualitative / mixed research design |
| Основополагащ източник≠ | Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretative Phenomenological Analysis: Theory, Method and Research. Sage. ISBN: 978-1412908344 | Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage. ISBN: 978-1506336169 |
| Други названия | Comparative IPA, cross-group IPA, IPA comparative design, multi-group interpretative phenomenological analysis | cross-case study, multi-site case study, multiple case study design, comparative case analysis |
| Свързани≠ | 5 | 4 |
| Резюме≠ | Comparative Interpretative Phenomenological Analysis (Comparative IPA) applies the IPA framework — developed by Jonathan A. Smith — to examine and contrast the lived experiences of two or more distinct groups or individuals. Rather than producing a single composite description, it preserves within-group detail and then performs a principled cross-group comparison, revealing how the same phenomenon is experienced differently depending on context, identity, or circumstance. | 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 от данни ↗ |
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