Examining the Performance Standards for In-Service Teachers: A Confirmatory Factor Analysis of the Assessment of Teachers' NETS-T Expertise

The survey Performance Standards for In-service Teachers is widely used to help describe teacher skills relating to instructional technology for assessment or planning of professional development. It is based on the six constructs of the National Educational Technology Standards for Teachers, and though used broadly in a variety of contexts, it does not appear to have undergone significant independent evaluation of its psychometric properties. Our analysis found that all six subscales possessed strong internal consistency (all α > 0.93). A subsequent confirmatory factor analysis supported both its current six-factor structure as well as a more parsimonious one-factor model.     

Measurement Bias Detection Through Factor Analysis

Assessing the correctness of a structural equation model is essential to avoid drawing incorrect conclusions from empirical research. In the past, the chi-square test was recommended for assessing the correctness of the model but this test has been criticized because of its sensitivity to sample size. As a reaction, an abundance of fit indexes have been developed. The result of these developments is that structural equation modeling packages are now producing a large list of fit measures. One would think that this progression has led to a clear understanding of evaluating models with respect to model misspecifications. In this article we question the validity of approaches for model evaluation based on overall goodness-of-fit indexes. The argument against such usage is that they do not provide an adequate indication of the “size” of the model's misspecification. That is, they vary dramatically with the values of incidental parameters that are unrelated with the misspecification in the model. This is illustrated using simple but fundamental models. As an alternative method of model evaluation, we suggest using the expected parameter change in combination with the modification index (MI) and the power of the MI test.     

Exploratory and Confirmatory Factor Analysis of the School Level Environment Questionnaire (SLEQ)

The purpose of the present study was to validate an existing school environment instrument, the School Level Environment Questionnaire (SLEQ). The SLEQ consists of 56 items, with seven items in each of eight scales. One thousand, one hundred and six (1106) teachers in 59 elementary schools in a southwestern USA public school district completed the instrument. An exploratory factor analysis was undertaken for a random sample of half of the completed surveys. Using principal axis factoring with oblique rotation, this analysis suggested that 13 items should be dropped and that the remaining 43 items could best be represented by seven rather than eight factors. A confirmatory factor analysis was run with the other half of the original sample using structural equation modeling. Examination of the fit indices indicated that the model came close to fitting the data, with goodness-of-fit (GOF) coefficients just below recommended levels. A second model was then run with two of the seven factors, with their associated items removed. That left five factors with 35 items. Model fit was improved. A third model was tried, using the same five factors with 35 items but with correlated residuals between some of the items within a factor. This model seemed to fit the data well, with GOF coefficients in recommended ranges. These results led to a refined, more parsimonious version of the SLEQ that was then used in a larger study. Future research is needed to see if this model would fit other samples in different elementary schools and in secondary schools both in the USA and in other countries. This revised version was published online in July 2006 with corrections to the Cover Date.     

A Test for Cluster Bias: Detecting Violations of Measurement Invariance Across Clusters in Multilevel Data

We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings are equal to the between-level factor loadings, and whether the between-level residual variances are zero. The test is illustrated with an example from school research. In a simulation study, we show that the cluster bias test has sufficient power, and the proportions of false positives are close to the chosen levels of significance.     

高校教师教学效果的多因素模型的验证性分析

通过贵州省文科、理科和农科专业的二、三、四年级大学生填写的《大学生评价教师教学效果问卷》（学生用）,即SEEQ问卷,运用协方差结构模型验证了贵州地区大学生评价教师教学效果的七、九因素模型的适合性。结果表明：1．Marsh的一阶九因素结构比较稳定;2．七因素完整模型也比较稳定,比九因素结构模型更好;3．教学热情／组织、群体互动、人际和谐、知识宽度、考试／作业与阅读材料这五个维度影响学习／价值感;4．项目T1（教师讲课能在智力上激发学生,富有启发和激励性）可归为教学热情／组织性这个维度。     

The Construct Validity of Student Engagement: A Confirmatory Factor Analysis Approach

As institutions seek to promote student engagement on campus, the National Survey of Student Engagement (NSSE) is increasingly being used to chart progress and compare results using the Five Benchmark Scores. While recent research has begun to decompose the five benchmarks in a variety of ways; few research studies have sought to explore the underlying structure of these five benchmarks, their interdependence, and the extent to which the items do reflect those five dimensions. This study begins to address the instrument’s construct validity by submitting a single, first-time freshman cohort’s NSSE responses to a confirmatory factor analysis, and proposes as an alternative, eight “dimensions” of student engagement that fit this set of data slightly better and in a more useful way. Results have practical implications for institutions utilizing NSSE, but also contain conceptual implications pertaining to the application of these benchmarks.     

影响学生网络化语言测试适应度的因素研究

文章通过文献回顾提出了影响学生网络化语言测试适应度的因素构想,并通过现场观察、问卷调查、访谈对此构想进行了验证。研究发现影响学生网络化语言测试适应度的四个因素包括:测试环境、测试规程、网考输入和回答方式。最后文章就此提出了减少负面影响的途径。     

基于因子分析的我国制造业各行业R&D投入绩效评价研究

运用因子分析模型,构建出制造业各行业RD投入绩效评价指标体系,运用2004年全国第一次经济普查工业科技活动情况相关数据,对我国制造业29个具体行业RD投入绩效水平及差异进行综合评价与分析。     

基于因子分析法的绿色照明概念上市公司绩效评价

运用 SPSS17.0软件和因子分析法对我国绿色照明概念中的20家上市公司在2013年度的经营绩效进行了实证分析,构建了一套科学合理的上市公司经营绩效综合评价指标体系,对上市公司的盈利能力、营运能力、偿债能力的指标数据进行建模分析,使企业管理者认识到公司的优势与劣势,为提升我国绿色照明概念上市公司的效益提供有益借鉴,同时也给证券市场投资者提供全面参考,有较大的研究价值和现实意义.     

基于因子分析法的河南省上市公司经营绩效评价

选择2010年12月31日之前上市的河南省49家上市公司作为研究对象,利用其2011至2015年的财务数据,分别从偿债能力、盈利能力、营运能力、发展能力等4个方面选取了13项财务指标,构建经营绩效评价指标体系,运用因子分析法研究样本公司经营绩效。实证结果显示:样本公司综合得分普遍偏低,综合绩效得分大于0的公司有19家,综合绩效得分小于0的公司有30家,河南省上市公司整体经营业绩仍有待提高。河南省上市公司应该通过全面协调发展、注重产品创新、提高资金的使用效率、扩大销售收入、控制经营成本、强化公司内部治理等路径,提高其经营绩效。     

基于因子分析法的中小板上市公司经营绩效评价及其影响因素分析

以我国中小板上市公司为样本,运用因子分析法对上市公司绩效进行综合评价,为公司绩效评价方法提供有益的借鉴。采用多元回归分析方法,考察公司经营绩效的影响因素。研究发现：中小板上市公司的董事会结构与绩效之间不存在显著的相关关系;股权结构指标与绩效之间呈现出较为显著的相关性;公司总资产规模和负债程度和对公司的绩效也产生了很大的影响。     

Web项目性能测试实例设计与分析

性能测试是一种性能评测,它对响应时间、事务处理速率和其他与时间相关的需求进行评测和评估,是验证软件系统是否能够达到用户提出的性能指标的一种手段。以“项目月报管理系统”为例,使用Loadrunner负载测试工具对测试过程进行了设计与分析。从测试结果数据看,系统性能表现较好,从而得出：Web项目性能测试成功的关键在于有效的性能测试分析方法和实践。     

构建科学的重庆基层政府绩效评估体系

科学的基层政府绩效评估体系对转变基层政府职能和优化政府工作流程有着重要的导向作用。构建科学的基层政府绩效评估体系应包括基层政府绩效评估指标体系、基层政府绩效评估方法体系和基层政府绩效评估运行保障体系三大方面。根据重庆的实际情况,本文尝试构建科学、完善的重庆基层政府绩效评估体系。     

美国地方政府绩效考评:实践与经验--以弗吉尼亚州费尔法克斯县为例

美国弗吉尼亚州费尔法克斯县的绩效考评实践,具有代表性。从中国学者立场观察,其实践经验可以概括为五点:(1)目标明确,动力十足;(2)组织合理,制度严格;(3)程序规范,方法科学;(4)指标简明,切合实际;(5)措施得力,实施有效。美国地方政府绩效考评经验,只可借鉴,不可照搬。     

湖南上市公司业绩的因子分析

用因子分析法来评价公司的业绩是一种常见的方法。借助因子分析法,利用湖南省上市公司公布的数据,从这些公司的14个财务指标中提取了5个因子。每个因子都有特定的名称和含义,根据因子得分的情况对这些公司的业绩进行排序,从而得出这些公司财务状况和综合业绩的总体印象。     

SPSS软件在试卷分析中的应用探析

试卷分析是反馈教学效果不可或缺的渠道,但分析过程又是繁冗复杂的。本文通过举例介绍SPSS软件在试卷分析中的应用,重点演示包括数据的录入、分析成绩分布,试卷难度、区分度、信度及效度等内容,旨在令没有系统学过教育统计学和相关软件的外语教师同样能够借助该软件轻松自如对考试试卷进行必要分析,有助于提高教师编制试卷、独立分析试卷的能力,从而科学指导教学,提高教学质量和效率。     

基于CFA视角的高考数学试卷结构的多维度研究

本文利用验证性因素分析(CFA)对一份高考数学试卷预设能力维度模型与实测数据进行拟合,给出了试题与其所反映的潜在能力维度之间的关系。分析结果表明,试题所反映的能力维度基本符合预设的目标,但试题所考核的能力目标并不十分明显,试题质量还需要进一步提升。分析也表明,验证性因素分析是一种有效的试卷能力维度分析方法。     

基于CORPS模式因子分析的国家示范性高职院校绩效评价研究

以2008年立项的23所国家示范高职院校为例,建立基于CORPS模式的高职院校绩效评价体系,研究这些院校在深化教育教学改革、创新人才培养模式、提高社会服务能力和创建办学特色等方面所取得的成绩.结果显示,高职院校在各因素的发展水平不均衡,各高职院校的总体发展水平也不均衡;总体来看,各高职院校普遍对服务对象、业务运作和师资力量等方面较为重视.     

心理统计学考试成绩的影响因素及教学启示

采用自编问卷考察《心理统计学》考试成绩影响因素的结构、特点及影响途径。结果发现,影响考试成绩的个体内部因素是学习态度、学习信心、学习方法,外部因素是课堂教学质量、教材与课时安排、复习资料;学习态度、学习信心的性别差异显著;学习态度、学习信心、复习资料对考试成绩有直接正向预测性,课堂教学质量、教材与课时安排通过学习态度或学习信心起间接正向预测作用,据此提出了相应的教学措施。