Influence of Family Involvement and Children's Socioemotional Development on the Learning Outcomes of Chilean Students.

There is an extensive body of evidence to support both family involvement and students' socioemotional development as key factors in the promotion of learning outcomes. However, there is insufficient evidence to establish exactly what this impact is when both factors are considered simultaneously. Therefore, the aim of this study is to analyze the influence of family involvement and socioemotional development on learning outcomes of Chilean students, identifying the structure that most correctly identifies the influence of the predictor variables (family involvement and socioemotional development) on learning outcomes. We present the following three hypotheses that consider possible basic interrelation structures: (1) The influence of family involvement on learning outcomes is mediated by students' socioemotional development (mediation hypothesis); (2) The influence of family involvement on learning outcomes is moderated by students' socioemotional development (moderation hypothesis); (3) Family involvement and students' socio emotional development directly affect learning outcomes (covariance hypothesis). The structures were evaluated by means of a structural equation model analysis. The study included 768 students who attended second and third elementary grades in Chilean schools. The children were between 7 and 11 years old (M = 8.29, SD = 0.86); 41.3% were girls and 58.7% were boys. The results show that family involvement and students' emotional development directly affect learning outcomes (CFI = 0.995, TLI = 0.993, RMSEA = 0.016). From the results, we can conclude that the data support the hypothesis that both family involvement and socioemotional development are predictors of learning outcomes, thereby rejecting that the impact of family involvement on learning outcomes is mediated or moderated by socioemotional development.

Precisión en la recuperación de parámetros, con datos ordinales, en el Análisis de Estructura de Covarianza y el Modelo de Rutas mediante Mínimos Cuadrados Parciales / Accuracy on Parameter Recovery, with Ordinals Data, of Structure Covariance Analysis and Partial Least Squares Path Modeling

Se compara la precisión en la recuperación de parámetros del Análisis de Estructura de Covarianza (ACOV) y el Modelo de Rutas mediante Mínimos Cuadrados Parciales (PLS-PM), en un modelo simple con variables manifiestas simuladas con escala ordinal de cinco puntos. Se utiliza un diseño experimental, manipulando el método de estimación, tamaño muestral, nivel de asimetría y tipo de especificación del modelo. Se valora la media de las diferencias absolutas para el modelo estructural. ACOV presenta estimaciones más precisas que PLS-PM, en distintas condiciones experimentales. Cuando se utiliza un tamaño muestral pequeño, ambas técnicas son igualmente precisas. Se sugiere utilizar ACOV frente a PLS-PM. Se desaconseja fundamentar la elección de PLS-PM frente a ACOV en la utilización de una muestra pequeña.

The accuracy on parameter recovery is compared between Structure Covariance Analysis (ACOV) and Partial Least Squares Path Modeling (PLS-PM), with simulated ordinals data with 5 points, in a simple model. An experimental design is used, controlling the estimation method, sample size, skewness level and model specification. Mean absolute differences are used to assess accuracy for the structural model. ACOV provided more accurate estimates of the structural parameters than PLS-PM in different experimental conditions. With a small sample size, both techniques are equally accurate. Using ACOV against PLS -PM is suggested. PLS choosing ACOV instead based on the use of a small sample size is not recommended.