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1.
《Educational Assessment》2013,18(2):105-123
Achievement data from a longitudinally matched student cohort from a large school district in the southwestern United States were analyzed to investigate sample exclusion and student attrition effects on estimates of student, school, and district mathematics performance. Use of 2- and 3-level longitudinal growth models to estimate the growth trajectories of middle school students revealed that mathematics performance differed across 2 sample conditions. Relative to the achievement outcomes associated with a sample that included all students from the longitudinal cohort, district and school achievement were generally higher and student group performance more similar in the smaller, more advantaged student sample used for district accountability reporting. Further investigation of the school performance estimates showed that cross-sample changes in student achievement outcomes were closely related to the proportion of students from special student populations who were excluded from the district accountability sample. The achievement differences and the differential patterns of association demonstrated in this study suggest that conclusions drawn about district and school performance and relationships between student characteristics and student achievement outcomes may depend to some degree on which students are included in an analytic sample. Investigators seeking to take advantage of longitudinal designs in school effectiveness research are cautioned to closely examine their data for nonrandom student attrition and document the impact of sample exclusion and student attrition effects in the research and accountability reports that are produced from longitudinal data sets.  相似文献   

2.
Conventional multilevel modeling works well with purely hierarchical data; however, pure hierarchies rarely exist in real datasets. Applied researchers employ ad hoc procedures to create purely hierarchical data. For example, applied educational researchers either delete mobile participants' data from the analysis or identify the student only with the last school attended while including an explanatory variable indicating whether a student is mobile. This simulation study compared the parameter and standard error estimates of these two ad hoc procedures for handling and assessing the influence of mobility on outcomes with results based on use of the multiple membership random effects model. Substantial bias was found for some parameters when multiple membership data structures were ignored.  相似文献   

3.
That the sample mean and variance are “good” estimates of the corresponding population parameters is easily accepted as “obvious” by students, but the concept of standard error of the mean is often found to be quite a hurdle. That this standard error decreases inversely as the square-root of the sample size, and the mysterious appearance of the Normal distribution, are often taken as magical and incomprehensible effects, and non-mathematical students can often be turned away from further understanding. This article describes a program which provides an experimental framework in which the student can rapidly develop an intuition for the basic properties of sampling.  相似文献   

4.
The present study evaluated the multiple imputation method, a procedure that is similar to the one suggested by Li and Lissitz (2004), and compared the performance of this method with that of the bootstrap method and the delta method in obtaining the standard errors for the estimates of the parameter scale transformation coefficients in item response theory (IRT) equating in the context of the common‐item nonequivalent groups design. Two different estimation procedures for the variance‐covariance matrix of the IRT item parameter estimates, which were used in both the delta method and the multiple imputation method, were considered: empirical cross‐product (XPD) and supplemented expectation maximization (SEM). The results of the analyses with simulated and real data indicate that the multiple imputation method generally produced very similar results to the bootstrap method and the delta method in most of the conditions. The differences between the estimated standard errors obtained by the methods using the XPD matrices and the SEM matrices were very small when the sample size was reasonably large. When the sample size was small, the methods using the XPD matrices appeared to yield slight upward bias for the standard errors of the IRT parameter scale transformation coefficients.  相似文献   

5.
In large-scale assessment programs such as NAEP, TIMSS and PISA, students' achievement data sets provided for secondary analysts contain so-called plausible values. Plausible values are multiple imputations of the unobservable latent achievement for each student. In this article it has been shown how plausible values are used to: (1) address concerns with bias in the estimation of certain population parameters when point estimates of latent achievement are used to estimate those population parameters; (2) allow secondary data analysts to employ standard techniques and tools (e.g., SPSS, SAS procedures) to analyse achievement data that contains substantial measurement error components; and (3) facilitate the computation of standard errors of estimates when the sample design is complex. The advantages of plausible values have been illustrated by comparing the use of maximum likelihood estimates and plausible values (PV) for estimating a range of population statistics.  相似文献   

6.
This study used Monte Carlo methods to investigate the accuracy and utility of estimators of overall error and error due to approximation in structural equation models. The effects of sample size, indicator reliabilities, and degree of misspecification were examined. The rescaled noncentrality parameter (McDonald & Marsh, 1990) was examined as a measure of approximation error, whereas the one‐ and two‐sample cross‐validation indices and a sample estimator of overall error (EFo) proposed by Browne and Cudeck (1989, 1993) were presented as measures of overall error. The rescaled noncentrality parameter and EFo provided extremely accurate estimates of the amounts of approximation and overall error, respectively. However, although models with errors of omission produced larger estimates of approximation and overall error, the presence of errors of inclusion had little or no effect on estimates of either type of error. The cross‐validation indices and sample estimator of overall error reached minimum values for the same model as an empirically derived measure of overall error only for models with large amounts of specification error. Implications for the use of these estimators in choosing among competing models were discussed.  相似文献   

7.
Robust maximum likelihood (ML) and categorical diagonally weighted least squares (cat-DWLS) estimation have both been proposed for use with categorized and nonnormally distributed data. This study compares results from the 2 methods in terms of parameter estimate and standard error bias, power, and Type I error control, with unadjusted ML and WLS estimation methods included for purposes of comparison. Conditions manipulated include model misspecification, level of asymmetry, level and categorization, sample size, and type and size of the model. Results indicate that cat-DWLS estimation method results in the least parameter estimate and standard error bias under the majority of conditions studied. Cat-DWLS parameter estimates and standard errors were generally the least affected by model misspecification of the estimation methods studied. Robust ML also performed well, yielding relatively unbiased parameter estimates and standard errors. However, both cat-DWLS and robust ML resulted in low power under conditions of high data asymmetry, small sample sizes, and mild model misspecification. For more optimal conditions, power for these estimators was adequate.  相似文献   

8.
The focus of this investigation was on relationships between teaching behaviors and student engagement in 13 middle school science classes. The results indicated that seven managerial variables and four instructional variables were significantly related to student engagement rates. Also the types of tasks allocated by teachers in science lessons were significantly related to the types of tasks undertaken by students. A canonical correlation analysis indicated significant relationships between three allocated task dimensions and three student engagement dimensions. Although teachers allocated adequate time for students to engage in investigation planning, data collecting, and data processing, the results indicated that overt engagement was prevalent only when data were collected. Attending was the predominant type of student engagement when investigations were planned and data were processed. The percentage of student time on task was approximately 63%. Rates of student off task behavior tended to be consistently high across all types of allocated tasks.  相似文献   

9.
A Monte Carlo approach was used to examine bias in the estimation of indirect effects and their associated standard errors. In the simulation design, (a) sample size, (b) the level of nonnormality characterizing the data, (c) the population values of the model parameters, and (d) the type of estimator were systematically varied. Estimates of model parameters were generally unaffected by either nonnormality or small sample size. Under severely nonnormal conditions, normal theory maximum likelihood estimates of the standard error of the mediated effect exhibited less bias (approximately 10% to 20% too small) compared to the standard errors of the structural regression coefficients (20% to 45% too small). Asymptotically distribution free standard errors of both the mediated effect and the structural parameters were substantially affected by sample size, but not nonnormality. Robust standard errors consistently yielded the most accurate estimates of sampling variability.  相似文献   

10.
大学学生评教的实证分析   总被引：13，自引：0，他引：13  
结合大学学生对课堂教学评价的实证分析，分析了影响学生评教指标体系设计的因素，同时论述了学生评教结果与班级大小，课程性质，教师职称，课程学时之间的关系。  相似文献   

11.
Prior studies that have investigated the relationship between school size and student academic achievement have produced conflicting results. For example, some studies found a positive relationship between school size and student achievement; other studies found that the relationship is negative. Typically, however, these past studies have not accounted for the influence of student ability in their analysis of the impact of school size on student achievement. The purpose of this paper is to examine the effect of school size on student achievement while accounting for student ability, among other variables. The results reported in this paper suggest that school size has a nonlinear relationship with respect to student achievement. Thus, there is an optimal school size with respect to the maximization of student achievement.  相似文献   

12.
目前高校学生工作标准化还没有引起足够重视。高校学生工作标准化是保证学生工作质量、提升学生工作水平的重要基础,其标准化活动主要包括制定、发布、实施相关标准的过程。高校学生工作标准体系应坚持以学生需求为中心、遵循党和国家的教育方针及相关的法律法规、关注学生工作重要岗位人员、关注关键和复杂过程。其标准体系主要包括管理职责标准、各岗位工作标准、过程控制标准、合格评定标准、分析改进标准。高校应编制标准体系表,总结学生工作的基本规律和成功经验,充分考虑相关方需求,制定各项标准,建立学生工作标准体系,并动态适应学校内外部环境。在标准体系的运行中,应注意标准体系的实施、监督检查和持续改进等环节,保持体系的有效性和效率。  相似文献   

13.
This research study investigates co-ordination strategies within schools, their relationships to both teacher and student commitment to school, and the relationship between student commitment and student achievement in Switzerland. Two different kinds of co-ordination strategies, structural and cultural, can be distinguished. Structural co-ordination strategies have to do with formal, lasting arrangements that allow an organisation to operate. These include roles, rules, procedures, and authority relations. Cultural co-ordination strategies are related to the nature of communications and the consensus on organisational goals in the school. Cultural mechanisms shape what teachers want to do. Drawn from TIMSS, the sample for the present analyses included principals, teachers and students in 178 classes at the lower secondary level in three Swiss cantons: Bale-Country, Berne and Zurich. Multiple regression analyses carried out with different indicators of teacher and student commitment to school showed that school coordination strategies can make a difference, although the effects were rather small. A further analysis that included student commitment indicators as predictors of mathematics achievement suggests that the affective/social and the cognitive domains are relatively independent at class level.  相似文献   

14.
ABSTRACT

Using a “naïve” specification, this paper estimates the relationship between 36 high school characteristics and 24 student outcomes controlling for students' pre-high school characteristics. The goal of this exploration is not to generate casual estimates, but rather to: (a) compare the size of the relationships to determine which inputs seem most promising and to identify which student outcomes appear most susceptible to being affected; (b) obtain likely upper-bound effect sizes that are useful information for power analyses used to establish minimum sample sizes for more robust designs capable of revealing causal impacts; and (c) illustrate how small effects over many outcomes (which are cumulatively important) can be easily missed. I find that most of the 36 inputs appear to have affected more outcomes than one would expect by chance, but that the apparent effects were generally small. Further, I find a higher frequency of large and significant apparent effects on educational achievement and attainment outcomes than labor market and other outcomes for young adults.  相似文献   

15.
Computerized adaptive testing (CAT) is a testing procedure that adapts an examination to an examinee's ability by administering only items of appropriate difficulty for the examinee. In this study, the authors compared Lord's flexilevel testing procedure (flexilevel CAT) with an item response theory-based CAT using Bayesian estimation of ability (Bayesian CAT). Three flexilevel CATs, which differed in test length (36, 18, and 11 items), and three Bayesian CATs were simulated; the Bayesian CATs differed from one another in the standard error of estimate (SEE) used for terminating the test (0.25, 0.10, and 0.05). Results showed that the flexilevel 36- and 18-item CATs produced ability estimates that may be considered as accurate as those of the Bayesian CAT with SEE = 0.10 and comparable to the Bayesian CAT with SEE = 0.05. The authors discuss the implications for classroom testing and for item response theory-based CAT.  相似文献   

16.
This study compares the impact of timing of registration on the student learning outcomes of students taking courses at three rural community colleges in the southeastern U.S. during the school years 2001–2003. Findings from this study indicate that early registration has a positive influence on students' grades and course completion rates. Also contributing to differences in student outcomes were student race, Pell Grant status, gender, program of study, and age.  相似文献   

17.
Most of the empirical frameworks and theories concerned with the development of citizenship today are quite complex and only provide some guidance for what citizenship education should attend to; they do not provide insight into the actual citizenship of students. We constructed a typology of student citizenship, on the basis of data collected from students. Patterns of scores for the citizenship orientations and citizenship knowledge of students were examined, and four clearly interpretable profiles could be identified (committed citizenship, indifferent citizenship, ordinary citizenship and self-assured citizenship). A sample of 7,768 students from grades 5 to 9 (aged 11–16 years) from 38 primary and secondary education schools participated in this research. The typology was then cross-validated on a separate sample of 15,940 students from Dutch primary and secondary education schools. The types of the citizenship differed depending on the individual demographic characteristics of the students and their level of education. Implications of the typology for citizenship education and future research are discussed.  相似文献   

18.
Abstract

A functional analysis involving interviews and direct observation was used to analyze the multiple disruptive behaviors of a kindergarten student. Following this analysis, an intervention that combined reinforcement and teacher-cued self-monitoring procedures was implemented using an A-B-A-B withdrawal design. The procedures produced a significant decrease in his disruptive behavior and changes in the functions of disruptions across experimental phases.  相似文献   

19.
Abstract

One major aim of international large-scale assessments (ILSAs) is to monitor changes in student performance over time. To accomplish this task, a set of common items is repeatedly administered in each assessment and linking methods are used to align the results from the different assessments on a common scale. The present article introduces a framework for discussing linking errors in ILSAs, in which different components of linking errors are distinguished (country-by-item interaction, assessment-by-item interaction and country-by-assessment-by-item interaction). Furthermore, the different components of linking errors are used to analytically derive standard errors for national trend estimates. In a simulation study, the proposed standard error formula outperforms the method that is used in PISA. In addition, the PISA 2006 and 2009 reading data are used to illustrate how the interpretation of national trend estimates can change when different procedures are applied to calculate standard errors.  相似文献   

20.
The purpose of this study is to investigate the effects of missing data techniques in longitudinal studies under diverse conditions. A Monte Carlo simulation examined the performance of 3 missing data methods in latent growth modeling: listwise deletion (LD), maximum likelihood estimation using the expectation and maximization algorithm with a nonnormality correction (robust ML), and the pairwise asymptotically distribution-free method (pairwise ADF). The effects of 3 independent variables (sample size, missing data mechanism, and distribution shape) were investigated on convergence rate, parameter and standard error estimation, and model fit. The results favored robust ML over LD and pairwise ADF in almost all respects. The exceptions included convergence rates under the most severe nonnormality in the missing not at random (MNAR) condition and recovery of standard error estimates across sample sizes. The results also indicate that nonnormality, small sample size, MNAR, and multicollinearity might adversely affect convergence rate and the validity of statistical inferences concerning parameter estimates and model fit statistics.  相似文献   

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