Methoden vergleichen
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| Deskriptive Forschung× | Trendforschung× | |
|---|---|---|
| Fachgebiet | Forschungsdesign | Forschungsdesign |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | Late 19th century; formalized in social/behavioral sciences ~1960s–1980s | Mid-20th century (formalised in social science methodology ~1950s–1960s) |
| Urheber≠ | Francis Galton, Karl Pearson (early empirical tradition); formalized in social science by Fred Kerlinger | Earl Babbie and survey research tradition |
| Typ≠ | Non-experimental quantitative research design | Quantitative longitudinal research design |
| Wegweisende Quelle | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage. ISBN: 978-1452226101 | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage. ISBN: 978-1452226101 |
| Aliasnamen | descriptive study, descriptive survey design, observational descriptive research, non-experimental descriptive research | trend study, trend survey, longitudinal trend study, time-series survey |
| Verwandt≠ | 3 | 4 |
| Zusammenfassung≠ | Descriptive research is a non-experimental quantitative design that systematically documents the characteristics, frequencies, or distributions of variables in a defined population at a given point in time. It answers 'what is' questions — who, what, when, where, and how much — without manipulating variables or drawing causal conclusions. It is one of the most widely used research designs across the social, behavioral, health, and education sciences. | Trend research is a longitudinal quantitative design that tracks changes in a characteristic of a general population over time by surveying different, independently drawn samples at two or more time points. Unlike panel studies, the same individuals are not followed; rather, each wave draws a fresh sample from the same population, allowing researchers to detect population-level shifts in attitudes, behaviours, or conditions while avoiding the attrition and panel conditioning problems of repeated-measures designs. |
| ScholarGateDatensatz ↗ |
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