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| Presečni relaciono istraživanje× | Relacioni upitnik× | |
|---|---|---|
| Oblast | Dizajn istraživanja | Dizajn istraživanja |
| Porodica | Process / pipeline | Process / pipeline |
| Godina nastanka≠ | Mid-20th century onward | Mid-20th century onward (systematised ~1960s–1990s) |
| Tvorac≠ | Rooted in survey methodology traditions; codified by Fraenkel, Wallen, and Creswell among others | Established in educational and social science research methodology; systematised by Fraenkel & Wallen and others |
| Tip≠ | Non-experimental quantitative design | Quantitative non-experimental survey design |
| Temeljni izvor≠ | 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 | Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2009). How to Design and Evaluate Research in Education (8th ed.). McGraw-Hill. ISBN: 978-0073525748 |
| Drugi nazivi | cross-sectional correlational survey, one-time relational survey, cross-sectional associational survey, single-occasion relational survey | correlational survey, associational survey, relationship survey design, relational descriptive survey |
| Srodne | 4 | 4 |
| Sažetak≠ | 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. | Relational survey research is a quantitative, non-experimental design that gathers structured self-report data from a sample and examines the statistical associations among two or more variables. Unlike purely descriptive surveys, which only characterise distributions, relational surveys ask whether and how strongly variables co-vary — providing evidence of relationships without manipulating conditions or establishing causation. |
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