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Social capital modelling in mathematical literacy

机译:数学素养中的社会资本建模

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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.
机译:这项研究提出了一种社会资本(SC)模型,以检验SC与数学素养(ML)之间的关系。随机抽取1021名15岁的中学生对用李克特量表(从1(强烈不同意)到10(强烈同意)评分的SC问卷)进行了回答,并回答了选定的2006年发布的ML上的PISA项目。使用结构方程建模以两阶段方法测试测量模型和结构模型。 SC项目的因子负载均在0.6以上,拟合优度指数(GFI)= 0.934,调整后的拟合优度指数(AGFI)= 0.904,比较拟合指数(CFI)= 0.934,标准拟合指数( NFI)= 0.903,均方根误差近似值(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具有积极而显着的影响。教师对ML产生负面影响。这项研究得出的结论是,互联网,社会经济地位和教师对机器学习的发展做出了贡献。考虑到这个信息时代的全球卓越教育,它强烈支持将互联网作为附加的SC因素。

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