Journal of Statistical and Econometric Methods

Statistical analysis and evaluation of Greek students’ background determinants on Science literacy

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• Abstract

   

  Pisa is a program developed by the OECD. The first time it appeared was in 2000. Since then more than 90 countries and about 3,000,000 students worldwide have participated (OECD forum). Students participate every 3 years and are assessed if they can successfully face and solve problems from everyday situations using the basic knowledge they have acquired from the subjects they have been taught at school. The main goal of this paper was to investigate the determinants of student performance. In particular, how students' characteristics, family background, and some school characteristics (type of school, geographic region, curriculum, and class size) affect science performance. We used PISA 2018 data for the case of Greece, as this country requires further research because Greek students perform below the average mean across OECD countries. The sample consisted of 6403 Greek students aged 15-16, who were enrolled in 242 schools. The analysis was carried out with the SPSS statistical program using multiple regression models (OLS) as well as Quantile Regression (QR) method for a more comprehensive study to evaluate whether the above variables affect in the same or different way on low and high-achieving students. Results indicated that family background and student characteristics affect students' performance significantly but to a different degree between high and low-performing students. In contrast, class size was shown to not affect almost the entire performance distribution. Moreover, access to material goods not directly related to education showed a negative effect, instead, the socioeconomic status of the family (ESCS) is a strong positive predictor of scientific literacy. Finally, the Greek education system suffers from several disparities both between different study programs and geographical regions. The above conclusions indicate that educational legislative reforms should be targeted and take into account the variance of student achievement with a focus to reduce the gap between high and low-performing students, which will lead to a robust education system.

  Keywords: PISA 2018, Quantile Regression (QR), OLS, Scientific literacy, Greek students.