Abstract: An Examination of School Influences on the Academic Achievement of Left behind Children in China (Society for Social Work and Research 23rd Annual Conference - Ending Gender Based, Family and Community Violence)

An Examination of School Influences on the Academic Achievement of Left behind Children in China

Schedule:
Saturday, January 19, 2019: 8:30 AM
Golden Gate 5, Lobby Level (Hilton San Francisco)
* noted as presenting author
Susan Stone, PhD, Catherine Mary and Eileen Clare Hutto Professor of Social Services in Public Education, University of California, Berkeley, Berkeley, CA
Qiaobing Wu, PhD, Associate Professor, The Hong Kong Polytechnic University
Marla Stuart, PhD, ​Fellow, Guizhou Berkeley Big Data Innovation Research Center (GBIC) Moore/Sloan Data Science Fellow, Berkeley Institute for Data Science (BIDS), University of California, Berkeley, CA
Cheng Ren, MSSA, Graduate Student Researcher, University of California, Berkeley, CA
Background and purpose: In China, 29 million children are affected by family migration—either as migrators themselves, or as those “left behind” by one or more parents. Existing research suggests that left behind children lag behind their peers in areas of emotional, social, and academic functioning, but these differences in functioning may be relatively small in magnitude. Although scholars contend that schools likely play important roles in supporting the functioning of left behind children, their potential roles have, to date, not been deeply empirically assessed. This study aims to provide preliminary evidence of the extent to which school characteristics relate to academic performance for left behind children.

Methods: To develop a profile of children and their schools, this study merges data from three government bureaus in a southern district of China: Education, Civil Affairs, and Health, covering a broad range of indicators on child, family, and school attributes. The data obtained are a cross section of 60,099 primary and middle school students who started school and took mathematics, Chinese, and English exams in Fall, 2016. Analytic methods include descriptive, spatial, and multi-level regressions.

Results: We find that 2% of primary and middle school students are identified as left behind. Compared to their non-migratory peers, they are more likely to be from a minority ethnicity (76% vs 43%) and low income (16% vs 6%). Our estimates suggest that left-behind children are less likely than their peers to pass all their exams, although the difference is small (OR=.97). Crucially, estimates demonstrate substantial across-school variation in student examination performance (ICCs range from .31-.47). Only after the addition of school-level characteristics over and beyond student and family characteristics is the ICC substantially reduced, indicating that the type of school (Provincial or Municipal), school level (middle school, or both primary and middle) and the overall passing rate for the school account for most of the variation in individual student examination performance. Interestingly, the estimated range of academic performance effect sizes for left behind children are about half the size of those that appear in published literature, suggesting that these children, while still behind their local peers, are performing better than expected. 

Conclusions and Implications: Characteristics of schools play a stronger role in examination scores than individual and family characteristics. A crucial next step is to better understand why school type is associated with better examination performance. Programmatically, these results suggest that efforts to support the academic achievement of left behind children be substantively coupled with local school-level educational reform efforts and that such efforts should target the student body as a whole.