Table_1_Factors influencing secondary school students’ reading literacy: An analysis based on XGBoost and SHAP methods.docx

This paper constructs a predictive model of student reading literacy based on data from students who participated in the Program for International Student Assessment (PISA 2018) from four provinces/municipalities of China, i.e., Beijing, Shanghai, Jiangsu and Zhejiang. We calculated the contribution of influencing factors in the model by using eXtreme Gradient Boosting (XGBoost) algorithm and sHapley additive exPlanations (SHAP) values, and get the following findings: (1) Factors that have the greatest impact on students’ reading literacy are from individual and family levels, with school-level factors taking a relative back seat. (2) The most important influencing factors at individual level are reading metacognition and reading interest. (3) The most important factors at family level are ESCS (index of economic, social and cultural status) and language environment, and dialect is negative for reading literacy, whereas proficiency in both a dialect and Mandarin plays a positive role. (4) At the school level, the most important factors are time dedicated to learning and class discipline, and we found that there is an optimal value for learning time, which suggests that reasonable learning time is beneficial, but overextended learning time may make academic performance worse instead of improving it.

本研究基于中国北京、上海、江苏、浙江四省市参与2018年国际学生评估项目（Program for International Student Assessment，PISA 2018）的学生数据，构建了学生阅读素养预测模型。本研究采用极限梯度提升（eXtreme Gradient Boosting，XGBoost）算法与夏普利可加解释值（SHapley additive exPlanations，SHAP）计算模型中各影响因素的贡献度，得到如下研究发现：（1）对学生阅读素养影响最大的因素来自个体与家庭层面，学校层面因素相对居于次要地位；（2）个体层面最核心的影响因素为阅读元认知与阅读兴趣；（3）家庭层面最重要的影响因素为经济、社会和文化地位指数（Economic, Social and Cultural Status，ESCS）与语言环境，方言对学生阅读素养具有负向影响，而同时掌握方言与普通话则能发挥正向作用；（4）学校层面最关键的影响因素为学习投入时长与课堂纪律，研究发现学习时长存在最优值，即合理的学习时长有益于提升学业表现，但过长的学习时长反而可能降低学业成绩。