Social capital modelling in mathematical literacy

L. Kor
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引用次数: 1

Abstract

This study proposed a social capital (SC) model to examine the relational bonds between SC and the mathematical literacy (ML). A random sample of 1021 15-year old secondary school students responded to the SC Questionnaire measured in Likert scales rated from 1 (strongly disagree) to 10 (strongly agreed) and answered selected released 2006 PISA items on ML. Structural Equation Modeling was employed to test the measurement model and the structural model in a two-stage approach. The factor loadings of the SC items were all above 0.6 with Goodness-of-Fit Index (GFI) = 0.934, Adjusted Goodness-of-Fit Index (AGFI) = 0.904, Comparative Fit Index (CFI) = 0.934, Normed Fit Index (NFI) = 0.903 and Root Mean Square Error Approximation (RMSEA) = 0.070. Results of hypothesis testing indicated that the Internet and home economic capital have positive and significant effect on ML. Teacher exerts a negative significant effect on the ML. This study concluded that the Internet, social economic status and teacher contribute to the development of ML. It strongly supports the inclusion of the Internet as an additional SC factor in view of the global educational excellence in this information age.
数学素养中的社会资本模型
本研究提出社会资本模型来检视社会资本与数学素养之间的关系。随机抽取1021名15岁中学生参与SC问卷调查,问卷采用李克特量表(Likert scale),从1(强烈不同意)到10(强烈同意)进行测量,并回答了2006年国际学生评估项目中关于ML的部分题目。采用结构方程模型对测量模型和结构模型进行了两阶段的检验。各量表的因子负荷均在0.6以上,拟合优度指数(GFI) = 0.934,调整拟合优度指数(AGFI) = 0.904,比较拟合指数(CFI) = 0.934,归一化拟合指数(NFI) = 0.903,均方根误差近似(RMSEA) = 0.070。假设检验的结果表明,互联网和家庭经济资本对机器学习有显著的正向影响,教师对机器学习有显著的负向影响。本研究认为,互联网、社会经济地位和教师对机器学习的发展有促进作用,这有力地支持了在信息时代全球教育卓越的背景下,将互联网作为一个额外的SC因素纳入其中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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