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Who Become Low-Achieving Students in Science? A Multilevel Analysis of Chinese Sample From PISA 2015 Data

Thu, April 8, 3:00 to 4:00pm EDT (3:00 to 4:00pm EDT), Division C, Division C - Section 1d: Science Poster Sessions


This study examined the effects of student- and school-level factors on middle school students’ status of science underperformance in China by applying multilevel logistic model to the PISA 2015 data. The student-level factors were gender, SES, achieving motivation, science learning time, and science career aspiration. The school-level factors were school background variables (i.e., school location, school type, and class size), science teaching staff and school science resources. Our findings revealed that a large proportion of the difference between low performers and non-low performers could be explained by school membership. In addition, the results show that most selected student- and school-level factors significantly predicted the status of low-achieving students in science. Implication and directions for future research were discussed.