Spanish validation of the Vocational Engagement Instrument in Vocational Training
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2024Publicado en:
Revista de educación. 2024, n. 406, octubre-diciembre ; p. p. 233-263Resumen:
Se presenta el proceso de validación del Instrumento de Vinculación Estudiantil (IVE), una nueva herramienta psicométrica que mide Vinculación del Estudiante en el ámbito de la Formación Profesional (FP). Se utilizó una muestra total de 4522 estudiantes españoles (64.6% hombres) de Mallorca (n = 1511, 33.4%), Barcelona (n = 1038, 23%) y Valencia (n = 1973, 43.6%), todos matriculados en el primer año de FP básica (n = 1370, 30.3%) o FP de grado medio (n = 3152, 69.7%). Se llevó a cabo una estrategia de comparación de modelos que incluyó modelos 5F bajo las perspectivas unifactorial, de cinco factores, y bifactorial. El análisis factorial confirmatorio (CFA) y los modelos de ecuaciones estructurales exploratorias (ESEM) se implementaron utilizando el método de estimación WLSMV. Los resultados mostraron un ajuste adecuado (RMSEA=.031, CFI=.970, TLI=.970, SRMR=.039) en el modelo bifactorial 5F del constructo evaluado (vinculación estudiantil). Además, se comprobó la invariancia de medias considerando el nivel de FP (básico/grado medio) (RMSEA=.028 y CFI=.910) y el género autoinformado (masculino/femenino) (RMSEA=.029, CFI=.913). En futuros estudios se debe proporcionar evidencia de validez convergente/discriminante y consecuencial para completar el proceso de validación. Estos prometedores resultados sobre la estructura latente del IVE pueden conducir a obtener patrones diferenciales de vinculación de los estudiantes, y desarrollar e implementar programas de intervención centrados en minimizar el abandono escolar y contribuir a un mejor rendimiento académico.
Se presenta el proceso de validación del Instrumento de Vinculación Estudiantil (IVE), una nueva herramienta psicométrica que mide Vinculación del Estudiante en el ámbito de la Formación Profesional (FP). Se utilizó una muestra total de 4522 estudiantes españoles (64.6% hombres) de Mallorca (n = 1511, 33.4%), Barcelona (n = 1038, 23%) y Valencia (n = 1973, 43.6%), todos matriculados en el primer año de FP básica (n = 1370, 30.3%) o FP de grado medio (n = 3152, 69.7%). Se llevó a cabo una estrategia de comparación de modelos que incluyó modelos 5F bajo las perspectivas unifactorial, de cinco factores, y bifactorial. El análisis factorial confirmatorio (CFA) y los modelos de ecuaciones estructurales exploratorias (ESEM) se implementaron utilizando el método de estimación WLSMV. Los resultados mostraron un ajuste adecuado (RMSEA=.031, CFI=.970, TLI=.970, SRMR=.039) en el modelo bifactorial 5F del constructo evaluado (vinculación estudiantil). Además, se comprobó la invariancia de medias considerando el nivel de FP (básico/grado medio) (RMSEA=.028 y CFI=.910) y el género autoinformado (masculino/femenino) (RMSEA=.029, CFI=.913). En futuros estudios se debe proporcionar evidencia de validez convergente/discriminante y consecuencial para completar el proceso de validación. Estos prometedores resultados sobre la estructura latente del IVE pueden conducir a obtener patrones diferenciales de vinculación de los estudiantes, y desarrollar e implementar programas de intervención centrados en minimizar el abandono escolar y contribuir a un mejor rendimiento académico.
Leer menosThe concept of student engagement plays a crucial role in understanding the risk factors leading to dropout, particularly among vulnerable students. The literature has divided school engagement into three subtypes: academic, cognitive, and emotional (Fredericks et al., 2004). This model proves highly relevant in contributing to empirical studies that assess academic engagement among vocational education students, as this educational level faces a significant dropout rate. In this context, this article presents evidence of the validity of scores from the Vocational Engagement Instrument (VEI), a new psychometric tool designed to measure engagement in the context of Vocational Education and Training (VET) students. The study was conducted using stratified cluster sampling of 4,522 students (64.6% males) from three Spanish regions: Mallorca (n = 1,511, 33.4%), Barcelona (n = 1,038, 23%), and Valencia (n = 1,973, 43.6%). Participants were enrolled in the first year of basic VET (n = 1,370, 30.3%) or intermediate VET (n = 3,152, 69.7%). A model comparison strategy included different latent structures (unifactorial, pentafactorial, bifactor) through Confirmatory Factor Analysis (CFA) and Exploratory Structural Equation Models (ESEM), using the Weighted Least Squares Mean and Variance adjusted (WLSMV) estimation method. The bifactor model achieved the best overall fit (chi-square/df=4.64, RMSEA=.031, CFI=.970, TLI=.970, SRMR=.039). Furthermore, measurement invariance was verified considering the VET level (basic/intermediate) (RMSEA=.028 and CFI=.910) and self-reported sex (male/female) (RMSEA=.029, CFI=.913). These promising results regarding the latent structure of the VEI may lead to the identification of differential patterns of student engagement. Additionally, they could facilitate the development and implementation of intervention programs focused on minimizing school dropout and enhancing academic performance.
The concept of student engagement plays a crucial role in understanding the risk factors leading to dropout, particularly among vulnerable students. The literature has divided school engagement into three subtypes: academic, cognitive, and emotional (Fredericks et al., 2004). This model proves highly relevant in contributing to empirical studies that assess academic engagement among vocational education students, as this educational level faces a significant dropout rate. In this context, this article presents evidence of the validity of scores from the Vocational Engagement Instrument (VEI), a new psychometric tool designed to measure engagement in the context of Vocational Education and Training (VET) students. The study was conducted using stratified cluster sampling of 4,522 students (64.6% males) from three Spanish regions: Mallorca (n = 1,511, 33.4%), Barcelona (n = 1,038, 23%), and Valencia (n = 1,973, 43.6%). Participants were enrolled in the first year of basic VET (n = 1,370, 30.3%) or intermediate VET (n = 3,152, 69.7%). A model comparison strategy included different latent structures (unifactorial, pentafactorial, bifactor) through Confirmatory Factor Analysis (CFA) and Exploratory Structural Equation Models (ESEM), using the Weighted Least Squares Mean and Variance adjusted (WLSMV) estimation method. The bifactor model achieved the best overall fit (chi-square/df=4.64, RMSEA=.031, CFI=.970, TLI=.970, SRMR=.039). Furthermore, measurement invariance was verified considering the VET level (basic/intermediate) (RMSEA=.028 and CFI=.910) and self-reported sex (male/female) (RMSEA=.029, CFI=.913). These promising results regarding the latent structure of the VEI may lead to the identification of differential patterns of student engagement. Additionally, they could facilitate the development and implementation of intervention programs focused on minimizing school dropout and enhancing academic performance.
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