Literaturnachweis - Detailanzeige
| Autor/inn/en | Ay, Sule; Sahin, Seyma; Okmen, Burcu; Incirci, Ayhan |
|---|---|
| Titel | Content Analysis of the Papers in 2015 High-Impact A-Class SSCI Journals |
| Quelle | In: Journal of Education and Practice, 7 (2016) 34, S.34-45 (12 Seiten)
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 2222-1735 |
| Schlagwörter | Content Analysis; Journal Articles; Educational Research; Predictor Variables; Cohort Analysis; Research Methodology; Research Design; Data Collection; Data Analysis; Bibliometrics; Foreign Countries; Turkey |
| Abstract | It was aimed in this study to reveal the general tendency of studies in the field of education by examining the papers in the high-impact A-class SSCI journals, to which qualified papers are accepted from all around the world, in terms of their dependent-independent variables, sample or study groups, research designs, data collection instruments, and data analysis techniques. The descriptive survey model was used in the research. The population of the research was all the journals surveyed in the field of educational sciences by SSCI. The journals and papers examined were selected with the purposive sampling method. 169 papers from six journals were subjected to examination within the scope of the research. Descriptive analysis and content analysis methods were used for analyzing the data. It was consequently seen that the papers used dependent variable of "student" the most which was followed by "teacher." The most studied variable along with "student" was "academic performance." It was found that a quite large number of dependent variables were used in the papers examined. It can be understood that studies on students among all study groups occupied the largest place, which was followed by teachers. It was seen that quantitative data analyses and experimental research studies was addressed more in the papers. Several documents and tests were mostly preferred as data collection instruments. It was noticed that the most used data analysis method was the regression analysis. Finally, some recommendations were developed in accordance with the research results. (As Provided). |
| Anmerkungen | IISTE. No 1 Central, Hong Kong Island, Hong Kong SAR. Tel: +852-39485948; e-mail: JEP@iiste.org; Web site: http://iiste.org/Journals/index.php/JEP |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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