השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| מחקר מקרה השתתפותי× | מבנה חקירת מקרי-מבחן מרובים× | |
|---|---|---|
| תחום | איכותני | איכותני |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 1980s–1990s (as an integrated approach) | 1980s–1990s (Yin's first edition 1984; Stake's collective case study concept 1995) |
| הוגה השיטה≠ | Synthesised from Robert K. Yin (case study) and Peter Reason / William Foote Whyte (participatory research) | Robert K. Yin (systematic replication logic); Robert E. Stake (naturalistic/collective case tradition) |
| סוג≠ | Qualitative research design | Qualitative research method |
| מקור מכונן≠ | Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage Publications. ISBN: 978-1506336169 | Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage. ISBN: 978-1506336169 |
| כינויים | collaborative case study, participatory case research, co-constructed case study, PCS | comparative case study, multi-site case study, collective case study, cross-case analysis |
| קשורות≠ | 5 | 6 |
| תקציר≠ | Participatory Case Study is a qualitative design that embeds participatory principles within a bounded case study framework. Participants are not merely research subjects but active collaborators who co-define the research questions, co-generate data, contribute to analysis, and validate the findings. The approach is appropriate when deep understanding of a specific, bounded context is needed and when the community or group under study has both the capacity and the right to shape the knowledge produced about their own situation. | Multiple-case study design investigates two or more bounded real-world cases using the same research protocol, then compares findings across cases to identify patterns, contrasts, and explanatory insights that a single case could not produce. Developed primarily through Robert Yin's replication logic and Robert Stake's collective case tradition, the approach is particularly powerful when a researcher needs to determine whether a phenomenon occurs under varied conditions or to test an emerging theoretical explanation against rival contexts. |
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