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    Analysis of Factors Predicting Students' Mathematics Achievement According to 2018 PISA Data
    (2024) Barun, Merve Nur; Sülkü, Seher Nur
    This study aims to determine the factors affecting students’ success in mathematics with PISA 2018 Data-Turkey covering 4473 students out of 6890. The factor analysis is applied to a wide range of 52 variables, including the number of weekly lessons in language, mathematics, and science courses to satisfaction with life, 14 factors are identified. After that, the multiple regression model is derived to find out the determinants of students’ success in mathematics. Besides these 14 factors, the gender of the students and the educational status of the parents are considered explanatory variables. Firstly, it is found that males and those whose fathers have higher levels of education have higher performance in mathematics. Among the factors, the wealth of family, use of information and communication technologies both outside and at the school, time spent to learn mathematics and science, perception of reading comprehension, and perception of cooperation at school are significantly positively associated with a student’s success. Furthermore, facing discrimination and bullying decreases student success in mathematics. The family's socioeconomic status and access to information-communication technologies are the most important determinants of student success. Finally, it is recommended that reasonable support should be given to disadvantaged students for providing equal opportunity.
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    Öğe
    Explanation of mortality rates with socio-economic indicators
    (Altınbaş Üniversitesi, 2022) Barun, Merve Nur; Korkmaz, İlayda
    This study aims to examine the relationship between death rates and socioeconomic variables and to develop policy recommendations to reduce mortality rates. Therefore, the variables of maternal mortality rate, crude mortality rate, and infant mortality rate are explained with real health expenditures per capita, number of nurse midwives, total health expenditures, number of physicians, and number of hospitals. The most recent data available between 2002 and 2019 are used in the article. Data are taken from health statistics annually. While three different mortality rates are considered as dependent variables in the study, five different variables indicating socioeconomic status are used as independent variables. Since more than one dependent and independent variable is used, canonical correlation analysis is preferred as the method. In the results of the analysis, it has been revealed that there is a high relationship between maternal mortality rate, infant mortality rate, crude death rate, and the number of hospitals, the number of nurses-midwives, the number of physicians, total health expenditures and per capita health expenditures. According to this, it is important to increase health awareness, increase the quality of health services in society, and facilitate access to health services. In addition, it is recommended to increase the number of health workers, improve health literacy in society and increase investments in the field of health.