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1.
根据研究和访谈结果,编制中学生班级集体效能感初测问卷,对194名中学生进行测试,结果用于探索性分析。对1773名中学生的测试结果用于验证性因素分析。159人完成重测,359人同时完成校标检验。探索性因素分析获得获得四个因素：合作、能力、预期和努力,解释了总变异的52．62％;验证性因素分析显示,四因素模型的各项参数达到可接受的水平;量表的内在一致性α系数和分半信度分别为0．878和0．859,重测信度为0．703,采用高峰强等人的集体效能信念量表作为班级集体效能感测量的效标,结果相关系数为0．541。因此,该量表具有较好的信效度,可应用于中学生群体。  相似文献   

2.
This study was designed to develop an assessment tool to measure high school students’ personal epistemology (PE) in the physics domain by using validation processes. Based on theoretical foundations of PE, the PPEQ was conceptualised on six hypothetical dimensions: structure of knowledge [SK], justification of knowledge and knowing [JK], changeability of knowledge [CK], equations in physics [EQ], quick learning [QL], and source of knowledge [source]. In total, 42-items were developed deductively for these dimensions, and a panel of experts assessed the content validity of the instrument. Subsequently, factor analyses were performed to obtain construct-related evidence. First, exploratory factor analysis (EFA) was performed on the data collected from 362 ninth graders. EFA yielded a six-factor solution which excluded the EQ and divided SK into two dimensions: coherent SK and hierarchical SK. Second, confirmatory factor analysis (CFA) was conducted with the remaining 27-items on data collected from a new sample of 350 ninth graders. The CFA results confirmed that the PPEQ assesses six factors emerged from EFA. Internal consistency of the PPEQ was also found to be very high with Cronbach’s α reliability coefficient of .92, and the coefficients of dimensions ranged from .71 to .83.  相似文献   

3.
A validation study was conducted on the Child Sex Abuse Attitude Scale (CSAAS) using confirmatory factor analysis (CFA) to examine factor structure. The CSAAS was developed based on Festinger's (1957) theory of attitude development resulting in a 4‐factor first‐order structure (cognition, value, affect, and behavior) and a single‐factor 2nd‐order structure (attitude). A sample of 215 school psychologists, members of the National Association of School Psychologists, responded to the CSAAS survey. CFA results supported the hypothesized factor structure of the CSAAS, thus indicating the plausibility of a 4‐factor 1st‐order and a single‐factor higher order structure of the CSAAS.  相似文献   

4.
We examine the factor structure of scores from the CLASS‐S protocol obtained from observations of middle school classroom teaching. Factor analysis has been used to support both interpretations of scores from classroom observation protocols, like CLASS‐S, and the theories about teaching that underlie them. However, classroom observations contain multiple sources of error, most predominantly rater errors. We demonstrate that errors in scores made by two raters on the same lesson have a factor structure that is distinct from the factor structure at the teacher level. Consequently, the “standard” approach of analyzing on teacher‐level average dimension scores can yield incorrect inferences about the factor structure at the teacher level and possibly misleading evidence about the validity of scores and theories of teaching. We consider alternative hierarchical estimation approaches designed to prevent the contamination of estimated teacher‐level factors. These alternative approaches find a teacher‐level factor structure for CLASS‐S that consists of strongly correlated support and classroom management factors. Our results have implications for future studies using factor analysis on classroom observation data to develop validity evidence and test theories of teaching and for practitioners who rely on the results of such studies to support their use and interpretation of the classroom observation scores.  相似文献   

5.
The Approaches and Study Skills Inventory for Students (ASSIST) were administered to 573 under-graduate students in order to analyse a Norwegian version of this inventory. To cross-validate the factor structure, the subjects were divided into two equal samples. Principal axis factor analysis of sample 1 reproduced the three main factors of deep, surface and strategic approaches to learning. However, two of the subscales failed to load appropriately on the 'strategic approach'. When omitting these subscales, the principle of simple structure was better supported by the results. A subsequent CFA with comparison of samples 1 and 2 supported the existence of the expected three-factor model. It is concluded that this Norwegian version of ASSIST is valuable as a research tool for the assessment of approaches to learning among Norwegian students, but that caution should be taken with respect to the interpretation of particular subscales and possible sample effects.  相似文献   

6.
This study is a methodological-substantive synergy, demonstrating the power and flexibility of exploratory structural equation modeling (ESEM) methods that integrate confirmatory and exploratory factor analyses (CFA and EFA), as applied to substantively important questions based on multidimentional students' evaluations of university teaching (SETs). For these data, there is a well established ESEM structure but typical CFA models do not fit the data and substantially inflate correlations among the nine SET factors (median rs = .34 for ESEM, .72 for CFA) in a way that undermines discriminant validity and usefulness as diagnostic feedback. A 13-model taxonomy of ESEM measurement invariance is proposed, showing complete invariance (factor loadings, factor correlations, item uniquenesses, item intercepts, latent means) over multiple groups based on the SETs collected in the first and second halves of a 13-year period. Fully latent ESEM growth models that unconfounded measurement error from communality showed almost no linear or quadratic effects over this 13-year period. Latent multiple indicators multiple causes models showed that relations with background variables (workload/difficulty, class size, prior subject interest, expected grades) were small in size and varied systematically for different ESEM SET factors, supporting their discriminant validity and a construct validity interpretation of the relations. A new approach to higher order ESEM was demonstrated, but was not fully appropriate for these data. Based on ESEM methodology, substantively important questions were addressed that could not be appropriately addressed with a traditional CFA approach.  相似文献   

7.
The purpose of this study was to develop a valid and reliable scale for assessing high school students’ self-directed learning skills. Based on a literature review and data obtained from similar instruments, all skills related to self-directed learning were identified. Next, an item pool was prepared and administered to 255 students from various high schools. To test the suitability of the gathered data, exploratory factor analysis was performed. The results revealed that there were correlations between the items, factor analysis could be conducted and nine factors were obtained. A confirmatory factor analysis (CFA) was performed concerning the quality of the factor structure. The results of the CFA confirmed the nine-factor solution. The final version of the scale has a nine-factor structure and includes a total of 40 items. This instrument uses a five-point Likert-type scale and was termed the Self-Directed Learning Skills Scale (SDLSS).  相似文献   

8.
The purpose of this study was twofold. First, the study aimed to validate the scale of the Virtual Team Competency Inventory in distance education, which had initially been designed for a corporate setting. Second, the methodological advantages of Exploratory Structural Equation Modeling (ESEM) framework over Confirmatory Factor Analysis (CFA) framework were empirically compared and discussed. A total of 1,355 distance education students participated in the survey designed to elicit their perceptions of their own competencies for working on virtual teams. The study validated the results from prior research that an eleven-factor structure solution for the competency construct achieved the most satisfactory fit. Methodologically, it also demonstrated that ESEM yielded a clearer factor structure and optimal model-fitting indices than CFA in a construct validation study.  相似文献   

9.
Many scholars agree on the general theoretical structure of metacognition, which is what informed the development of the Metacognitive Awareness Inventory (MAI). Although self-report instruments such as the MAI suffer many threats to validity, they continue to be used in research and practice because of their convenience. With the MAI, studies have varied in the way they calculate scores and in their adherence to the intended theory. In this study, we address these shortcomings and propose modifications in calculating MAI scores. Using confirmatory factor analysis (CFA) and multidimensional random coefficients multinomial logit (MRCML) item-response modeling, we examined how well the intended functioning of the MAI matched the data from 622 undergraduate students. The results support scoring the MAI as two dimensions, knowledge and regulation of cognition, but indicate that the 52-item instrument has poor fit. Using iterative CFA and MRCML models, we tested subsets of items that represent the theory and had good fit. We followed up with tests of between-group and time invariance. The results support the use of a 19-item subset for between-group comparisons, with provisional evidence for its use in longitudinal studies.  相似文献   

10.
Confirmatory factor analysis (CFA) is often used in the social sciences to estimate a measurement model in which multiple measurement items are hypothesized to assess a particular latent construct. This article presents the utility of multilevel CFA (MCFA; Muthén, 1991, 1994) and hierarchical linear modeling (HLM; Raudenbush, Rowan, & Kang, 1991) methods in testing measurement models in which the underlying attribute may vary as a function of various levels of observation. An illustrative example using a real dataset is provided in which an unconditional model specification and parameter estimates from the MCFA and HLM are shown. The article demonstrates the comparability of the two methods in estimating measurement parameters of interest (i.e., true variance at levels the measures are used and measurement errors).  相似文献   

11.
The authors created a psychometrically sound instrument that could be used to examine K-12 teachers’ perceptions of arts integration. Ten content experts reviewed the initial survey items for construct-fit and readability. Scores from 354 K-12 teachers were examined for the survey’s initial factor structure through exploratory factor analysis (EFA). Then, scores from 1,072 K-12 teachers were analyzed to complete a confirmatory factor analysis (CFA) of the Putting the Arts and the Classroom Together (PACT) data. EFA results indicated a three-factor structure (i.e., value, willingness, and barriers), and CFA results produced model indices showing good fit of the three-factor model. For purposes of examining teachers’ practices in integrating the arts, establishing teacher receptiveness to arts integrated curriculum is important in designing and implementing any professional development program. This survey could be used to establish baseline participant perceptions for staging targeted professional development to support educators in creating appropriate arts integrated curricula.  相似文献   

12.
This simulation study assesses the statistical performance of two mathematically equivalent parameterizations for multitrait–multimethod data with interchangeable raters—a multilevel confirmatory factor analysis (CFA) and a classical CFA parameterization. The sample sizes of targets and raters, the factorial structure of the trait factors, and rater missingness are varied. The classical CFA approach yields a high proportion of improper solutions under conditions with small sample sizes and indicator-specific trait factors. In general, trait factor related parameters are more sensitive to bias than other types of parameters. For multilevel CFAs, there is a drastic bias in fit statistics under conditions with unidimensional trait factors on the between level, where root mean square error of approximation (RMSEA) and χ2 distributions reveal a downward bias, whereas the between standardized root mean square residual is biased upwards. In contrast, RMSEA and χ2 for classical CFA models are severely upwardly biased in conditions with a high number of raters and a small number of targets.  相似文献   

13.
The purposes of this study were to (a) test the hypothesized factor structure of the Student-Teacher Relationship Scale (STRS; Pianta, 2001) for 308 African American (AA) and European American (EA) children using confirmatory factor analysis (CFA) and (b) examine the measurement invariance of the factor structure across AA and EA children. CFA of the hypothesized three-factor model with correlated latent factors did not yield an optimal model fit. Parameter estimates obtained from CFA identified items with low factor loadings and R2 values, suggesting that content revision is required for those items on the STRS. Deletion of two items from the scale yielded a good model fit, suggesting that the remaining 26 items reliably and validly measure the constructs for the whole sample. Tests for configural invariance, however, revealed that the underlying constructs may differ for AA and EA groups. Subsequent exploratory factor analyses (EFAs) for AA and EA children were carried out to investigate the comparability of the measurement model of the STRS across the groups. The results of EFAs provided evidence suggesting differential factor models of the STRS across AA and EA groups. This study provides implications for construct validity research and substantive research using the STRS given that the STRS is extensively used in intervention and research in early childhood education.  相似文献   

14.
Social‐emotional health influences youth developmental trajectories and there is growing interest among educators to measure the social‐emotional health of the students they serve. This study replicated the psychometric characteristics of the Social Emotional Health Survey (SEHS) with a diverse sample of high school students (Grades 9–12; N = 14,171), and determined whether the factor structure was invariant across sociocultural and gender groups. A confirmatory factor analysis (CFA) tested the fit of the previously known factor structure, and then structural equation modeling was used to test invariance across sociocultural and gender groups through multigroup CFAs. Results supported the SEHS measurement model, with full invariance of the SEHS higher‐order structure for all five sociocultural groups. There were no moderate effect size or higher group differences on the overall index for sociocultural or gender groups, which lends support to the eventual development of common norms and universal interpretation guidelines.  相似文献   

15.
In 1959, Campbell and Fiske introduced the use of multitrait–multimethod (MTMM) matrices in psychology, and for the past 4 decades confirmatory factor analysis (CFA) has commonly been used to analyze MTMM data. However, researchers do not always fit CFA models when MTMM data are available; when CFA modeling is used, multiple models are available that have attendant strengths and weaknesses. In this article, we used a Monte Carlo simulation to investigate the drawbacks of either using CFA models that fail to match the data-generating model or completely ignore the MTMM structure of data when the research goal is to uncover associations between trait constructs and external variables. We then used data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development to illustrate the substantive implications of fitting models that partially or completely ignore MTMM data structures. Results from analyses of both simulated and empirical data show noticeable biases when the MTMM data structure is partially or completely neglected.  相似文献   

16.
Data collected from questionnaires are often in ordinal scale. Unweighted least squares (ULS), diagonally weighted least squares (DWLS) and normal-theory maximum likelihood (ML) are commonly used methods to fit structural equation models. Consistency of these estimators demands no structural misspecification. In this article, we conduct a simulation study to compare the equation-by-equation polychoric instrumental variable (PIV) estimation with ULS, DWLS, and ML. Accuracy of PIV for the correctly specified model and robustness of PIV for misspecified models are investigated through a confirmatory factor analysis (CFA) model and a structural equation model with ordinal indicators. The effects of sample size and nonnormality of the underlying continuous variables are also examined. The simulation results show that PIV produces robust factor loading estimates in the CFA model and in structural equation models. PIV also produces robust path coefficient estimates in the model where valid instruments are used. However, robustness highly depends on the validity of instruments.  相似文献   

17.
对基于CFA（颜色滤波阵列）模型的篡改检测算法进行了改进。其检测过程为：首先,利用插值算法得到像素位置的预测误差,根据预测误差计算出CFA单元特征;然后,利用EM（期望最大化）算法估计特征模型的参数,算法对篡改位置的均值不做事先确定（从实验来看这种改进具有较好的效果）;最后,利用贝叶斯理论计算出每个像素点的似然率,根据似然率的不同来定位篡改区域。在进行单CFA阵列模式检测的情况下,对多种CFA阵列模式的图像也进行了检测分析,实验结果显示,该算法能够对多种CFA阵列模式的图像准确定位篡改区域。  相似文献   

18.
Namibia has been reported to be one of the countries with the highest unemployment rates. In this work, the reliability and validity of the self-assessment instrument used to measure competencies of graduates in Namibia were assessed using exploratory factor analysis (EFA) and second-order confirmatory factor analysis (CFA). The EFA results demonstrated that the twenty indicators can be categorized into five factors, namely, “management and resilience”, “professional and communication”, “teamwork and critical thinking”, “self-control”, and “achievement motive”. The CFA results showed that all of the factors and indicators are highly reliable with good construct validity. Students and graduates could employ this validated self-assessment instrument to assess or diagnose a pattern of strengths and weaknesses in their own competencies and provide themselves with a realistic and objective estimate of their employability, as well as help them increase effectiveness in their workplace.  相似文献   

19.
The underlying structure of the Revised Two factor version of the Study Process Questionnaire (R-SPQ-2F), a 20-item instrument for the evaluation of students’ approaches to learning (SAL), was examined at item level using two independent groups of undergraduate students enrolled in the first (n=314) and last (n=522) years of their studies. The methods used were (a) Exploratory factor analysis (EFA) assisted by rigorous procedures such as Velicer’s MAP test, parallel analysis and the Schmid Leiman solution with the first sample; and (b) confirmatory factor analysis (CFA) with the second sample. The results of EFA indicated that the latent structure of the R-SPQ-2F is best described by two factors and the results of CFA suggested that out of four a priori structural models, the best fit was achieved by a simple first-order two-factor model. Taken together, these results seemed to converge, suggesting (a) that SAL might be defined as a co-variation between a motive and its intended strategy, these not necessarily being divided into separate first-order factors (subscales), and (b) that the underlying structure of the R-SPQ-2F is apparently non-hierarchical, being best described by a parsimonious first-order two-factor model in which Deep and Surface learning approaches are each measured by their ten corresponding items.  相似文献   

20.
This article presents a new method for multiple-group confirmatory factor analysis (CFA), referred to as the alignment method. The alignment method can be used to estimate group-specific factor means and variances without requiring exact measurement invariance. A strength of the method is the ability to conveniently estimate models for many groups. The method is a valuable alternative to the currently used multiple-group CFA methods for studying measurement invariance that require multiple manual model adjustments guided by modification indexes. Multiple-group CFA is not practical with many groups due to poor model fit of the scalar model and too many large modification indexes. In contrast, the alignment method is based on the configural model and essentially automates and greatly simplifies measurement invariance analysis. The method also provides a detailed account of parameter invariance for every model parameter in every group.  相似文献   

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