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| 비교 탐색적 양적 연구× | 탐색적 양적 연구× | |
|---|---|---|
| 분야 | 연구설계 | 연구설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | Mid-to-late 20th century | Mid-20th century (codified in social research methods texts c. 1950s–1970s) |
| 창시자≠ | No single originator; codified in quantitative research methodology traditions (20th century) | Earl Babbie; John Creswell (systematic codification in social science methods) |
| 유형≠ | Quantitative research design | Non-experimental quantitative research design |
| 원전≠ | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage Publications. ISBN: 978-1452226101 | Babbie, E. (2021). The Practice of Social Research (15th ed.). Cengage Learning. ISBN: 978-0357360767 |
| 별칭 | exploratory comparative quantitative design, comparative exploratory survey research, quantitative comparative exploration, CEQR design | quantitative exploratory design, exploratory survey research, initial quantitative investigation, preliminary quantitative study |
| 관련≠ | 3 | 4 |
| 요약≠ | Comparative exploratory quantitative research is a design that uses structured numerical data collection to discover patterns, differences, and relationships across two or more distinct groups or conditions — without a fully specified hypothesis in advance. It sits at the intersection of exploratory intent and comparative structure: the researcher does not enter the field with a predetermined answer but organises the inquiry around a comparison that will generate quantitative insights. The design is common in social, educational, and behavioural sciences when a phenomenon is insufficiently understood to permit confirmatory testing but structured group comparison is still feasible and informative. | Exploratory quantitative research is a non-experimental design used when a phenomenon is insufficiently understood to support formal hypothesis testing. The researcher collects numerical data — typically through surveys, structured observation, or existing records — to describe distributions, detect patterns, and generate hypotheses that more targeted confirmatory studies can subsequently test. It occupies the first stage of a cumulative quantitative research programme. |
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