Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Enquête relationnelle transversale× | Recherche Descriptive× | |
|---|---|---|
| Domaine | Conception de la recherche | Conception de la recherche |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | Mid-20th century onward | Late 19th century; formalized in social/behavioral sciences ~1960s–1980s |
| Auteur d'origine≠ | Rooted in survey methodology traditions; codified by Fraenkel, Wallen, and Creswell among others | Francis Galton, Karl Pearson (early empirical tradition); formalized in social science by Fred Kerlinger |
| Type≠ | Non-experimental quantitative design | Non-experimental quantitative research design |
| Source fondatrice≠ | Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to Design and Evaluate Research in Education (8th ed.). McGraw-Hill. ISBN: 978-0078097706 | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage. ISBN: 978-1452226101 |
| Alias | cross-sectional correlational survey, one-time relational survey, cross-sectional associational survey, single-occasion relational survey | descriptive study, descriptive survey design, observational descriptive research, non-experimental descriptive research |
| Apparentées≠ | 4 | 3 |
| Résumé≠ | A cross-sectional relational survey collects data from a representative sample at a single point in time and examines the statistical relationships (correlations, associations, predictions) among two or more variables. It combines the temporal efficiency of cross-sectional design with the relational focus of correlational survey research, making it one of the most widely used quantitative designs in education, social science, and health research when a quick, population-level picture of variable relationships is needed. | 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. |
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