Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students' Evaluations of University Teaching

Marsh, Herbert W.; Muthén, Bengt; Asparouhov, Tihomir; Lüdtke, Oliver; Robitzsch, Alexander; Morin, Alexandre J. S.; Trautwein, Ulrich

doi:10.1080/10705510903008220

Cited by 852 publications

(1,020 citation statements)

References 59 publications

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“…More complex exploratory models have been recently proposed by Marsh et al 16 , which consist of fitting exploratory models within a CFA framework. Called ESEM (Exploratory Structural Equation Model), this Exploratory/Confirmatory Factor Analysis (E/CFA) holds an advantage over the traditional EFA model in so far as it allows relaxing and effectively implementing some of the restrictions the latter imposes.…”

Section: The Seven Stepsmentioning

confidence: 99%

Assessing construct structural validity of epidemiological measurement tools: a seven-step roadmap

2014

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Guidelines have been proposed for assessing the quality of clinical trials, observational studies and validation studies of diagnostic tests. More recently, the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) initiative extended those in regards to epidemiological measurement tools in general. Among various facets proposed for assessment is the validity of an instrument’s dimensional structure (or structural validity). The purpose of this article is to extend these guidelines. A seven-step roadmap is proposed to examine (1) the hypothesized dimensional structure; (2) strength of component indicators regarding loading patterns and measurement errors; (3) measurement error correlations; (4) factor-based convergent and discriminant validity of scales; (5) item discrimination and intensity vis-à-vis the latent trait spectrum; and (6) the properties of raw scores; and (7) factorial invariance. The paper also holds that the suggested steps still require debate and are open to refinements.

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Section: The Seven Stepsmentioning

confidence: 99%

Assessing construct structural validity of epidemiological measurement tools: a seven-step roadmap

2014

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“…This is typical for some other examination methods which are based on integrated Confirmatory Factor Analysis (CFA) [8], [14], [15], Hierarchical Confirmatory Factor Analysis (HCFA) [16] and Structural Equation Models (SEM) [17] applied specifically for SET analysis. In general the correlation between theory and practical experience would be a better indicator for an engineering lecture in our opinion.…”

Section: Discussion Of the Evaluation Methodsmentioning

confidence: 99%

“…A plan, which was elaborated to restructurethe course and the measures to evaluate the changesare shown in Section V. This section also contains an analysis of the evaluation after the revision. A look at the key indicators and their interdependence is given which supports the principles of the explorative factor analysis (EFA) [6]- [8]. This is used to reflectively judge our ratings.…”

Section: Introductionmentioning

confidence: 99%

Revision of an Optical Engineering Lecture Based on Students’ Evaluation of University Teaching

Beuth¹,

Danilova²,

Babu³

et al. 2015

IJIET

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Abstract-This article describes the revision of a lecture in optical engineering based on an evaluation of university teaching by students. Although this evaluation method is widely accepted and investigated, only few practically oriented reports on the deduction of teaching improvements from the evaluation's results on lectures are available. Our approach is the analysis of evaluation results by applying the principles of the explorative factor analysis (EFA). The changes that were derived from this analysis were mainly focused on a revision of the course structure and its presentation style.Finally, the impact of the modifications was measured by the evaluation of the lecture after the completed revision. The later evaluation showed improvements in all intended areas of interests illustrating the benefit of thorough revisions for the quality of teaching.evaluate optical components and simple systems with Zemax (widely-used optical ray tracing software) in ODL. During the period under consideration the quality index ratings for OE tutorials was 94.4 out of 100 (winter term 2011/12) and 92 out of 100 for ODL (winter term 2011/12). These evaluation results are quoted for the sake of completeness and to emphasize that there is no necessity to restructure the tutorials and ODL.Both are courses but influenced significantly by OE. Therefore, in the course of restructuring OE, care has to be taken that these do not suffer. III. EVALUATION PROCESSAt the Karlsruhe Institute of Technology (KIT) it is mandatory that every lecture is evaluated by students [9]. Students can rate a wide range of indicators (up to 40) affecting classroom teaching like the usage of black boards, clarity of the speaker, script quality and learning success among others, with an integer value from 1 (very good) to 5 (very bad). For each indicator an average (vI) is calculated. The university supports the lecturer with the averaged value of each indicator and its standard derivation but just a graphical depiction of the raw data.Therefore, it is hard to inspect dependencies from year to year, e.g. by t-test statistics.Five key indicators are taken as a base to calculate a teaching quality index called "Lehrqualitätsindex" (LQI). If the indicator's average is between 1.0 and 2.5, its quality value (sLQI) is judged as 100. Between 2.5 and 3.5 there is a 100 . If the average is between 3.5 and 5, its sLQI is 0. Five sLQIs are weighted with a number between 0 and 1 and then summed up for the calculation of the overall lecture's LQI. The LQI is usually calculated for lectures by the key indicators overall impression, work load, course structure, (perceived) dedication of the lecturer and his responsiveness (these indicators are applicable for our evaluation as well). It is flexible in a way that indicators used in computation of the quality index can be changed upon request to more fitting items. The calculation process is displayed in Fig. 1. The LQI is taken as a raw measuring tool for the departmental advisory boards to identify issues in teaching ...

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“…Dentre estas, destacamse os procedimentos analíticos empregados, próprios para dados categóricos 17 . Outro ponto positivo concerne ao uso de modelos flexíveis como os MEEE 23 , que permitem, entre outros, o escrutínio de propriedades não antes visitadas na literatura afim. Em particular, foi possível avaliar a presença de correlações residuais 17 .…”

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“…Seguindo recomendação da literatura, considerou-se valores > 0,85 como sugestivos de falta de validade fatorial discriminante 17 . Antecipando um possível mau ajuste do modelo original e prevendo estruturas alternativas, reavaliou-se a estrutura dimensional do s-EMBU por meio de modelos de equação estrutural exploratórios (MEEE) 17,23 . Os MEEE estendem a capacidade das tradicionais análises explorató-rias, permitindo avaliar, por exemplo, correlações residuais, cuja presença indicaria possíveis redundâncias de itens 17 …”

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Estrutura dimensional da versão brasileira do instrumento s-EMBU para aferição de práticas educativas parentais em adolescentes

2016

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Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students' Evaluations of University Teaching

Cited by 852 publications

References 59 publications

Assessing construct structural validity of epidemiological measurement tools: a seven-step roadmap

Assessing construct structural validity of epidemiological measurement tools: a seven-step roadmap

Revision of an Optical Engineering Lecture Based on Students’ Evaluation of University Teaching

Estrutura dimensional da versão brasileira do instrumento s-EMBU para aferição de práticas educativas parentais em adolescentes

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