A Two-Level Hierarchical Linear Model Analysis of the Effect of Teacher Factors, Student Factors, and Facility Conditions on Students’ Cognitive Scores in Rural China

Xiaoyan Wang and Anquan Wang
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Xiaoyan Wang: School of Education, Ningxia University, Yinchuan 750021, China
Anquan Wang: School of Education, Ningxia University, Yinchuan 750021, China

Sustainability, 2022, vol. 14, issue 13, 1-17

Abstract: Based on the data from the China Education Panel Survey 2013–2014, this study uses a two-level hierarchical linear model to explore the impact of student factors, teacher factors, and facility conditions on students’ cognitive scores and the model’s heterogeneity. Additionally, under the Owen value method, the contribution of teacher and student factors to students’ cognitive scores is much greater than that of facility conditions, and teacher-related factors contribute more to scores than student-related ones. Therefore, teacher and student resources should be given priority in allocating resources to rural education systems, and high-quality teachers, who can have positive impacts on students’ cognitive scores, should be prioritized.

Keywords: input of rural educational resources; China Education Panel Survey Data (CEPS data); Hierarchical Linear Model (HLM); Shapley value method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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