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1.
Students' Perceptions of Interpersonal Aspects of the Learning Environment   总被引：1，自引：0，他引：1  
This study examined variables associated with differences in students' perceptions of interpersonal teacher behavior. The perceptions of 3023 students and 74 teachers in 168 classes in seven secondary schools were used in the analyses. Investigating variance at the student, class, teacher and school levels revealed that several variables are significantly related to students' perceptions: student and teacher gender, student and teacher ethnic background, student age and grade, class size, grade level, subject taught and teacher experience. There were interaction effects between some variables, such as student ethnicity and student gender, as well as student and teacher gender. While significant, the amount of variance explained by these was low (around 10%). The outcomes generally confirmed earlier research, although some new effects were found. Perhaps the main result of the study was its verification of the complex and interactive nature of students' perceptions of the learning environment and researchers' understanding of it.  相似文献   

2.
Given multivariate data, many research questions pertain to the covariance structure: whether and how the variables (e.g., personality measures) covary. Exploratory factor analysis (EFA) is often used to look for latent variables that might explain the covariances among variables; for example, the Big Five personality structure. In the case of multilevel data, one might wonder whether or not the same covariance (factor) structure holds for each so-called data block (containing data of 1 higher level unit). For instance, is the Big Five personality structure found in each country or do cross-cultural differences exist? The well-known multigroup EFA framework falls short in answering such questions, especially for numerous groups or blocks. We introduce mixture simultaneous factor analysis (MSFA), performing a mixture model clustering of data blocks, based on their factor structure. A simulation study shows excellent results with respect to parameter recovery and an empirical example is included to illustrate the value of MSFA.  相似文献   

3.
In many applications of multilevel modeling, group-level (L2) variables for assessing group-level effects are generated by aggregating variables from a lower level (L1). However, the observed group mean might not be a reliable measure of the unobserved true group mean. In this article, we propose a Bayesian approach for estimating a multilevel latent contextual model that corrects for measurement error and sampling error (i.e., sampling only a small number of L1 units from a L2 unit) when estimating group-level effects of aggregated L1 variables. Two simulation studies were conducted to compare the Bayesian approach with the maximum likelihood approach implemented in Mplus. The Bayesian approach showed fewer estimation problems (e.g., inadmissible solutions) and more accurate estimates of the group-level effect than the maximum likelihood approach under problematic conditions (i.e., small number of groups, predictor variable with a small intraclass correlation). An application from educational psychology is used to illustrate the different estimation approaches.  相似文献   

4.
ABSTRACT

In the present study the effects of a cooperative leadership team, distributed leadership, participative decision-making, and context variables on teachers’ organizational commitment are investigated. Multilevel analyses on data from 1522 teachers indicated that 9% of the variance in teachers’ organizational commitment is attributable to differences between schools. The analyses revealed that especially the presence of a cooperative leadership team and the amount of leadership support played a significantly positive key role in predicting teachers’ organizational commitment. Also, participative decision-making and distribution of the supportive leadership function had a significant positive impact on teachers’ organizational commitment. In contrast, distribution of the supervisory leadership function and teachers’ job experience had a significant negative impact.  相似文献   

5.
The purpose of this simulation study was to assess the performance of latent variable models that take into account the complex sampling mechanism that often underlies data used in educational, psychological, and other social science research. Analyses were conducted using the multiple indicator multiple cause (MIMIC) model, which is a flexible and effective tool for relating observed and latent variables. The data were simulated in a hierarchical framework (e.g., individuals nested in schools) so that a multilevel modeling approach would be appropriate. Analyses were conducted accounting for and not accounting for the nested data to determine the impact of ignoring such multilevel data structures in full structural equation models. Results highlight the differences in modeling results when the analytic strategy is congruent with the data structure and what occurs when this congruency is absent. Type I error rates and power for the standard and multilevel methods were similar for within-cluster variables and for the multilevel model with between-cluster variables. However, Type I error rates were inflated for the standard approach when modeling between-cluster variables.  相似文献   

6.
This article examined the role of centering in estimating interaction effects in multilevel structural equation models. Interactions are typically represented by product term of 2 variables that are hypothesized to interact. In multilevel structural equation modeling (MSEM), the product term involving Level 1 variables is decomposed into within-cluster and between-cluster random components. The choice of centering affects the decomposition of the product term, and therefore affects the sample variance and covariance associated with the product term used in the maximum likelihood fitting function. The simulation study showed that for an interaction between a Level 1 variable and a Level 2 variable, the product term of uncentered variables or the product term of grand mean centered variables produced unbiased estimates in both Level 1 and Level 2 models. The product term of cluster mean centered variables produced biased estimates in the Level 1 model. For an interaction between 2 Level 1 variables, the product term of cluster mean centered variables produced unbiased estimates in the Level 1 model, whereas the product term of grand mean centered variables produced unbiased estimates for the Level 1 model. Recommendations for researchers who wish to estimate interactions in MSEM are provided.  相似文献   

7.
Multilevel Structural equation models are most often estimated from a frequentist framework via maximum likelihood. However, as shown in this article, frequentist results are not always accurate. Alternatively, one can apply a Bayesian approach using Markov chain Monte Carlo estimation methods. This simulation study compared estimation quality using Bayesian and frequentist approaches in the context of a multilevel latent covariate model. Continuous and dichotomous variables were examined because it is not yet known how different types of outcomes—most notably categorical—affect parameter recovery in this modeling context. Within the Bayesian estimation framework, the impact of diffuse, weakly informative, and informative prior distributions were compared. Findings indicated that Bayesian estimation may be used to overcome convergence problems and improve parameter estimate bias. Results highlight the differences in estimation quality between dichotomous and continuous variable models and the importance of prior distribution choice for cluster-level random effects.  相似文献   

8.
The present study examined students' attitudes toward science and associated constructs, based on the theories of reasoned action and planned behavior, and explored relationships between individual and school-related variables common to the research literature. Responses from 1,291 students in Grades 5 through 10 were collected using the 30-item Behaviors, Related Attitudes, and Intentions toward Science (BRAINS) Survey along with background information questions. Additional self-report data were collected from teachers (n = 56; 82.4%) in participating schools (n = 68) to obtain information about their education and experience, characteristics and practices, as well as other classroom variables, which could influence students' outlook. Student information, teacher data collected, and other data compiled about participating schools, were used to explore patterns in students' attitudes, beliefs, and intentions. These variables were used to generate multivariate multilevel models through a forward construction process. The final model presented favors individual variables to explain differences in students' responses on all five of the BRAINS subscales, more than group-level variables captured. Of the predictor variables explored, students' perceived science ability and frequency of talk with family were influential on all subscales, and increasing these variables had a positive effect on the estimated mean scores according to the final model presented. Findings from this study also include commonly observed relationships, such as the decline in attitudes over time, but these were found to be less pervasive in this sample. The paper concludes with a discussion about the comparative ineffectiveness of teacher and school-related variables in explaining students' attitudes toward science in this study, in light of design decisions and limitations, to guide future investigations.  相似文献   

9.
Abstract

The aim of this study is to establish to what extent teachers’ knowledge, in association with school socioeconomic level, students’ previous knowledge and level of mathematical knowledge achieved in school contribute to the knowledge that fourth-grade students reach in conceptualizing fractions. Information was obtained from 328 fourth-grade students of nine schools and their respective mathematics teachers. The results show that the 77% of variability observed in the conceptualization of fractions could be attributed to student-level variables, while the remaining 23% would be attributable to school-level variables. On the other hand, 38% of the intra-school variance could be explained by students’ previous knowledge, and virtually all the between-schools variance would be explained by the academic level of the school or, in 32% of cases, by the socioeconomic status of the school. Teacher knowledge, alone or in combination with other factors, accounts for about 10%, with a significance of 10%.  相似文献   

10.
When modeling latent variables at multiple levels, it is important to consider the meaning of the latent variables at the different levels. If a higher-level common factor represents the aggregated version of a lower-level factor, the associated factor loadings will be equal across levels. However, many researchers do not consider cross-level invariance constraints in their research. Not applying these constraints when in fact they are appropriate leads to overparameterized models, and associated convergence and estimation problems. This simulation study used a two-level mediation model on common factors to show that when factor loadings are equal in the population, not applying cross-level invariance constraints leads to more estimation problems and smaller true positive rates. Some directions for future research on cross-level invariance in MLSEM are discussed.  相似文献   

11.
This is the first study to test whether the stages of change of the transtheoretical model are qualitatively different through exploring discontinuity patterns in theory of planned behavior (TPB) variables using latent multigroup structural equation modeling (MSEM) with AMOS. Discontinuity patterns in terms of latent means and prediction patterns for the different stage groups were examined. Adults (n = 3,462) were assessed on their physical activity stages of change and TPB variables. The TPB was separately examined within the five stage groups. The TPB measurement model fit was acceptable. Latent mean analyses with post-hoc contrast and MSEM indicated discontinuity patterns. Results underscore the qualitative differences between the stages that may guide further research and the design of interventions integrating the approaches.  相似文献   

12.
While there is an increased interest in describing attitudes of teachers, parents and peers towards students with special educational needs in regular education, there is a lack of knowledge about various variables relating to the attitudes of these three groups. The aims of this study are: (1) to examine which variables relate to the attitudes of teachers (N?=?44), parents (N?=?508) and peers (N?=?1113) towards students with Attention Deficit/Hyperactivity Disorder, Autistic Spectrum Syndrome or a cognitive disability in regular primary education and (2) to examine whether teachers and parents’ attitudes affect the attitudes of peers. An attitude survey was used to assess attitudes and data were analysed by means of multilevel analyses. The variables found in this study relating to attitudes can be used as a foundation to develop interventions to change attitudes.  相似文献   

13.
Enjoyment of reading, diversity of reading and metacognitive awareness of reading strategies are cognitive and affective variables pertaining to three facets of reading engagement for students to read happily, widely and skilfully. These have been found to be related to effectiveness in reading instruction. They together form a focus for this study to examine the underlying student- and across-level mechanisms to explain gender differences in reading performance of Macao students. Drawing data from Programme for International Student Assessment (PISA) 2009 Study, the mediation effects of gender and the school’s gender composition on reading performance are analysed. Two findings are of both theoretical and pedagogical interests. Firstly, the three facets of reading engagement from the nurture perspective explain substantially the within-school gender gap. Secondly, in coeducation context where students read happily and skilfully, there are gender-specific peer influences across-level onto student reading performance. Implications for gender-inclusive reading instruction programmes are discussed.  相似文献   

14.
Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture modeling, as well as the application to complex multilevel sampling designs. The goal of this study was to investigate—through a Monte Carlo simulation study—the performance of several methods for parameterizing multilevel latent class analysis. Of particular interest was the comparison of several such models to adequately fit Level 1 (individual) data, given a correct specification of the number of latent classes at both levels (Level 1 and Level 2). Results include the parameter estimation accuracy as well as the quality of classification at Level 1.  相似文献   

15.
The major aim of educational effectiveness research is to examine and explain school, class, and teacher differences with respect to relevant educational criteria. Until now, in the large majority of studies, language and mathematics scores were used as a criterion. In the present study, the educational track students choose at the start of secondary education (at the age of 12) and their success in the chosen curriculum are examined in relation to primary school and classes (Grades 1 to 6). Two-level models show that students had higher aims in secondary education if they had attended primary Catholic schools and/or primary schools with high average curriculum advice. The latter schools were also highly effective with respect to achievement, and their students had a high socioeconomic status and background. Multilevel models with a cross-classified structure showed no direct long-term effects of primary schools and classes.  相似文献   

16.
ABSTRACT

A multilevel framework was applied to investigate the effects of teacher characteristics, school environment, and district level HRM practices on teacher commitment. Drawing on the results from a public school teacher survey conducted in the Emirate of Abu Dhabi in 2014, four forms of teacher commitment (commitment to school, to students, to teaching, and to community) were tested, which provided empirical evidence to further the development of teacher commitment as a multi-foci construct. The results of the three-level model revealed differentiating effects of some individual and organisational variables on different forms of teacher commitment and highlighted that nationality, multiple interpersonal support, and collegial relationships were the most consistent and strong variables to predict teacher commitment. This study suggested that the social and interpersonal environment of school played a significant role in influencing teacher commitment. Results were discussed in relation to improving the commitment of teachers in the empirical context of Abu Dhabi public schools.  相似文献   

17.
This study evaluated rater accuracy with rater-monitoring data from high stakes examinations in England. Rater accuracy was estimated with cross-classified multilevel modelling. The data included face-to-face training and monitoring of 567 raters in 110 teams, across 22 examinations, giving a total of 5500 data points. Two rater-monitoring systems (Expert consensus scores and Supervisor judgement of correct scores) were utilised for all raters. Results showed significant group training (table leader) effects upon rater accuracy and these were greater in the expert consensus score monitoring system. When supervisor judgement methods of monitoring were used, differences between training teams (table leader effects) were underestimated. Supervisor-based judgements of raters’ accuracies were more widely dispersed than in the Expert consensus monitoring system. Supervisors not only influenced their teams’ scoring accuracies, they overestimated differences between raters’ accuracies, compared with the Expert consensus system. Systems using supervisor judgements of correct scores and face-to-face rater training are, therefore, likely to underestimate table leader effects and overestimate rater effects.  相似文献   

18.
ABSTRACT

Previous studies have indicated that, although some teachers have substantial expectation effects on student outcomes, the effects for most teachers are only small. Furthermore, teacher expectations are associated with key pedagogical differences related to teacher beliefs about providing instruction and support for learning. The aim of this study was to explore (a) teacher-level differences in the level and differentiation of expectations, (b) associations between teacher differences in expectations and teacher background and beliefs, and (c) relationships with subsequent student performance. Secondary analyses were performed on data for 42 teachers and their students in New Zealand. The results were supportive of the notion that some teachers were differentiating more between students in their expectations than others. Teachers who differentiated more perceived students generally as more competent, but felt less related to the school team, and perceived more classroom stress. Differentiation in expectations was negatively related to end-of-year mathematics scores.  相似文献   

19.
To what extent can teacher–student dyadic interactions modify the hierarchy of student performances within a single class? To answer this insufficiently researched question, the authors conducted two parallel studies involving 33 Grade 5 classes in France (759 students) and 15 Grade 5 classes in Luxembourg (243 students). Interactions were observed during whole-class lessons. Posttest scores were analyzed using multilevel models controlling for five level-1 variables and two level-2 variables. The authors did not find any effect of dyadic interactions on relative student performance in mathematics or in language (French or German), in France or in Luxembourg. This result is interpreted in terms of both the public character of dyadic interactions in whole-class settings and the class management functions of these interactions.  相似文献   

20.
The authors compared the effects of using the true Multilevel Latent Growth Curve Model (MLGCM) with single-level regular and design-based Latent Growth Curve Models (LGCM) with or without the higher-level predictor on various criterion variables for multilevel longitudinal data. They found that random effect estimates were biased when the higher-level predictor was not included and that standard errors of the regression coefficients from the higher-level were underestimated when a regular LGCM was used. Nevertheless, random effect estimates, regression coefficients, and standard error estimates were consistent with those from the true MLGCM when the design-based LGCM included the higher-level predictor. They discussed implication for the study with empirical data illustration.  相似文献   

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