學生因素、國家發展與數學成就之多層次研究   免費試閱

Students’ Factors, Nation Development, and Mathematics Achievement by Using Hierarchical Linear Modeling

傳統上，以單層面分析學生學習成就，無法掌握不同層面的因素對學習表現的影響。近年來，多層次模型應用在不同層次因素對學習成就的影響有增加趨勢。然而，將國家發展指標納入分析者相當少。本研究透過2015年參加PISA資料，51個國家363,372名學生納入分析，研究中分為國家層及學生層因素，透過多層次模型分析獲得結論如下：一、國家發展的差異在解釋數學學習成就的效應不可忽略；二、國民所得、國家競爭力及性別平等對數學學習成就有顯著預測力；三、學生的家庭學習資源與家庭設備對數學學習成就有正向顯著影響；四、學生的幸福感、學習動機及學習焦慮對數學學習成就有明顯影響。

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.