Students’ Factors, Nation Development, and Mathematics Achievement by Using Hierarchical Linear Modeling
Traditionally, related studies were based on analysis of single-level variables, which was unable to illustrate the effects of multi-level factors. Hierarchical Linear Modeling (HLM) has been applied in educational research to analyze the influences of various levels of factors on academic achievement. However, those that employed the nation development in HLM were few and far between. This study thus investigated the effects of both the nation-level and the learner-level factors on the learners’ mathematics academic achievement, using HLM. The database used in this study contained data collected in PISA from 363,372 eighth-grade students of 51 nations. The main findings of this study are summarized as follows. First, the differences among nations, important in predicting eighth-grade school students’ mathematics achievement, are not negligible factors. Second, among the nation-level factors, gross national income per capital, nation competitiveness index, and gender inequality index have significant effects on mathematics achievement. Third, among learner-level factors, family cultural capital and family wealth have positive effects on mathematics achievement. Fourth, in terms of the learner-level factors, students’ well-being, mathematics learning motivation, and learning anxiety have positive, positive, and negative effects on mathematics achievement respectively.
|關鍵詞||性別平等指數、國家競爭力指數、數學學習成就、學習動機、學習資源、gender inequality index、nation competitiveness index、mathematics academic achievement、learning motivation、family learning resource|