Factors associated with academic resilience in disadvantaged students: An analysis based on the PISA 2015 B-S-J-G (China) sample - Jin, Songli; Fang, Guangbao; Cheung, Kwok Cheung; Sit, Pou Seong (Frontiers in Psychology, 2022)
Some students, referred to as Disadvantaged Resilient Students, live in disadvantaged home environments but strive to achieve as much as possible. However, other students, referred to as Disadvantaged Non-resilient Students with similar home backgrounds, cannot perform at levels beyond what is predicted by their socio-economic status. The percentage of Disadvantaged Resilient Students in four affluent cities/provinces of China (i.e., Beijing, Shanghai, Jiangsu, and Guangdong) within the Programme for International Student Assessment in 2015, ranked eighth amongst the 68 participating countries/economies. This study examines the learning, schooling, and parental factors, which predict the adolescent classification of Disadvantaged Resilient Students and Disadvantaged Non-resilient Students from Beijing, Shanghai, Jiangsu, and Guangdong in China with reference to the assessment of their scientific literacy. The Classification and Regression Tree and Multilevel Logistic Regression Modeling have been deployed to identify differentiating factors and the scale of outcomes. These findings inform governments, educational practitioners, and parents as to how to help students, classified as DNS, perform at a level in scientific literacy beyond that predicted by their home socio-economic status.