運用多層級分析探究影響五個東南亞國家的學生數學成就之因素：以 2012
年國際學生能力評量計畫為例

本研究的目的，是藉由分析2012年的「國際學生能力評量計劃」（PISA）數據庫，探討越南，泰國，新加坡，馬來西亞和印尼，這五個國家學校與學生的層級結構因素，對學生數學成就的影響及其相互作用。以「投入-過程-背景-產出」模式、計劃行為理論、權變理論等三個理論方法為基礎，為使用2012年PISA數據庫的五個國家，選擇預測變項，並進行了階層線性模式（HLM）技術。在HLM的結果中，顯示出這些國家的學生可以藉由以下學生層級的因素，而達到更好的數學能力：（1）學生花更多的時間在家自學或與家庭教師學習; （2）更高的數學自我效能感; （3）更加熟悉數學概念; （4）數學焦慮的程度較低; （5）加強活化認知; （6）在學校應用數學的作業經驗較少; （7）教師以學生為本的行為較少。而在學校層級，只發現了一些影響學生數學表現的因素。在這五個國家中，有助於學生學習數學成功的唯一因素，是學生擁有較高的經濟、社會和文化地位。其他變項，如學校的類型、學校規模、在校女學生比例、生師比、班級規模、教師的參與、與學生相關的因素等，會使這五個國家的結果變項，產生學校的校園風氣顯示不一致的效果。對學生數學表現的影響，因為不同的學生與學校層級因素，所以每間學校都不同。而相關的政策意涵也在此研究中討論。

關鍵字

國際學生能力評量計畫(PISA) ；數學讀寫能力；階層線性模式(HLM) ；東南亞教育

並列摘要

The purpose of the present study is to explore the impact of school- and student-level factors and their interaction on students’ mathematical performance across Vietnam, Thailand, Singapore, Malaysia, and Indonesia by analyzing the Programme for International Student Assessment (PISA) 2012 dataset. Based on three theoretical approaches, the input-process-context-output paradigm, the theory of planned behavior, and the contingency theory, predicting variables were chosen and hierarchical linear modeling (HLM) techniques were conducted for each of the five countries using the PISA 2012 database. The HLM results indicated that students in these countries could make better mathematics achievement thanks to the following factors at the student level: (1) students spending more time learning at home or with a tutor; (2) higher levels of mathematics self-efficacy; (3) higher familiarity with mathematics concept; (4) lower levels of mathematics anxiety; (5) higher cognitive activation; (6) less experience with applied mathematics tasks at school; and (7) less student-oriented behaviors of teachers. As the school level, only a few factors were found to influence students’ mathematical performance. The only factor which contributes to students’ mathematics learning success across the five countries is higher economic, social, and cultural status. Other variables such as school type, school size, proportion of girls at school, student-teacher ratio, class size, teacher participation, and student-related factors affecting school climate show inconsistent effects on the outcome variable in the five countries. The influence on students’ mathematical performance varied from school to school with respect to different student- and school-level factors. Policy implications have also been discussed in the study.

並列關鍵字

Programme for International Student Assessment (PISA) ； Mathematical literacy ； Hierarchical Linear Modeling (HLM) ； Southeast Asian education

參考文獻

Adeyemo, D. A., & Adetona, M. O. (2005). A path analytic study of the personality factors affecting students’ learning outcomes in mathematics. European Journal of scientific research, 18(1), 118-133.

Google Scholar

Ajzcn, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.

Google Scholar

Ajzcn, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 34(2), 665-683.