Data for the paper titled "Cross-country predictors of academic achievement: An applied inquiry with data from 41 countries"

The main purpose of this study is to examine potential predictors of academic achievement using OECD’s original PISA 2018 dataset that has recently been released. Our sample covers 41 countries and data used in our analysis are collected from 282,461 students distributed in 9,317 schools worldwide. Multiple linear regressions are developed and analyzed using stepwise estimation techniques. The results indicate that (i) a strong correlation exists between high test scores and student characteristics & learning climate, i.e. students’ sense of belonging at school, disciplinary climate and students’ fear of failure, (ii) there is a negative relationship between academic performance and teacher enthusiasm & support, (iii) student success is negatively correlated with income level and political and economic freedoms but positively associated with economic competitiveness of a country, (iv) the students in overcrowded classes perform worse than those in lightly populated ones and inadequate or poor educational material deteriorates educational outcomes, and (v) availability of internet connection at home and student’s possession of enjoyable pastime activity have positive impacts on student’s success.

本研究旨在借助经济合作与发展组织（Organisation for Economic Co-operation and Development, OECD）新近发布的原版国际学生评估项目（Programme for International Student Assessment, PISA）2018数据集，探究学业成就的潜在预测因子。本研究样本覆盖41个国家，分析所用数据取自全球9317所学校的282461名学生。本研究采用逐步估计法构建并分析多元线性回归模型，结果显示：（1）高分表现与学生特征及学习氛围存在显著关联，具体包括学生在校归属感、校园纪律氛围以及学生的失败恐惧心理；（2）学业表现与教师教学热情及支持力度呈负相关关系；（3）学生学业成功与国家收入水平、政治经济自由度呈负相关，而与一国经济竞争力呈正相关；（4）大班额班级的学生学业表现逊于小班学生，且教育资源不足或质量欠佳会削弱教育产出效果；（5）家庭互联网接入条件以及学生拥有愉悦的课余休闲活动，对学生学业成功具有正向促进作用。