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An analysis of a preservice teacher structural equation model under varying assumptions and measurement conditions

机译:在各种假设和测量条件下对职前教师结构方程模型的分析

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摘要

The purposes of this study were to develop a structural equation model of preservice teacher variables and to examine alternative methods of testing this model under different assumptions and measurement conditions. A conceptual model was posited to examine variables related to job expectations, academic ability, pre-student teaching preparation, satisfaction with cooperating teacher, self-rated student teaching performance, and quality of teacher preparation program;From this conceptual model of preservice teacher variables, five empirical models were developed and analyzed. Models I and II utilized single indicators computed as composite means of the respective observed standardized indicators. Model I assumed variables were measured without error. Model II utilized the same indicators as Model I but adjustments were made to allow for measurement error. Models III and IV used a multiple indicator approach with Model III assuming no measurement error, while Model IV adjusted for measurement error. Model V, assuming no measurement error, utilized the multiple indicators from Models III and IV but analyzed them independently. The method of analysis for Models I, III and V was multiple linear regression. Models II and IV were analyzed using the LISREL approach;Results of the analyses lent moderate support for the conceptual model. The results of two single indicator models indicated a satisfactory fit of the models to the data. However, the multiple indicator model adjusting for error did not provide a good fit. In addition to the individual model tests, parameter estimates from the different models were compared and discussed.
机译:这项研究的目的是建立职前教师变量的结构方程模型,并研究在不同的假设和测量条件下测试该模型的替代方法。提出了一个概念模型来研究与工作期望,学业能力,学生的预科教学准备,对合作老师的满意度,学生的自评教学表现和教师准备计划质量有关的变量;从这种职前教师变量的概念模型中,建立并分析了五个经验模型。模型I和模型II利用单个指标作为相应观察到的标准化指标的综合手段进行计算。模型I假设变量的测量没有错误。模型II使用与模型I相同的指标,但进行了调整以允许测量误差。模型III和IV使用多指标方法,其中模型III假设没有测量误差,而模型IV则针对测量误差进行了调整。假设没有测量误差,模型V利用了模型III和IV的多个指标,但对它们进行了独立分析。模型I,模型III和模型V的分析方法是多元线性回归。使用LISREL方法分析了模型II和IV;分析结果为概念模型提供了适度的支持。两个单一指标模型的结果表明模型对数据的满意拟合。但是,针对误差调整的多指标模型并不能很好地拟合。除了单独的模型测试之外,还比较和讨论了来自不同模型的参数估计。

著录项

  • 作者

    Frerichs, Dean K.;

  • 作者单位
  • 年度 1989
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
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