Predictive model of high school students’ dropout risk in Mexico

National high school dropout rates in Mexico, fluctuate between 14.5 % and 16.5 %, and empirical research suggests that dropout is mostly associated with failure, and that this in turn, is related to issues such as lack of learning self-regulation and study habits. The objective of this research was...

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Main Authors:	Hernández-Jácquez, Luis Fernando, Montes-Ramos, Frine Virginia
Format:	Online
Language:	spa
Published:	Universidad Autónoma de Tamaulipas 2020
Online Access:	https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1349
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id	oai:ojs.pkp.sfu.ca:article-1349
record_format	ojs
institution	CIENCIA UAT
collection	OJS
language	spa
format	Online
author	Hernández-Jácquez, Luis Fernando Montes-Ramos, Frine Virginia
spellingShingle	Hernández-Jácquez, Luis Fernando Montes-Ramos, Frine Virginia Predictive model of high school students’ dropout risk in Mexico
author_facet	Hernández-Jácquez, Luis Fernando Montes-Ramos, Frine Virginia
author_sort	Hernández-Jácquez, Luis Fernando
title	Predictive model of high school students’ dropout risk in Mexico
title_short	Predictive model of high school students’ dropout risk in Mexico
title_full	Predictive model of high school students’ dropout risk in Mexico
title_fullStr	Predictive model of high school students’ dropout risk in Mexico
title_full_unstemmed	Predictive model of high school students’ dropout risk in Mexico
title_sort	predictive model of high school students’ dropout risk in mexico
description	National high school dropout rates in Mexico, fluctuate between 14.5 % and 16.5 %, and empirical research suggests that dropout is mostly associated with failure, and that this in turn, is related to issues such as lack of learning self-regulation and study habits. The objective of this research was to establish a model that predicts the risk of high school students’ drop in Mexico. A quantitative, non-experimental and cross-sectional research was developed. The independent variable, which was the risk of dropping out of school, was assessed through the School Dropout Questionnaire, while the predictive variables study habits, self-regulation learning and learning styles (as requested by the participating institution) were assessed through the Study Habits Questionnaire, the Learning Strategies and Motivation Questionnaire (CEAM II), and the Honey – Alonso Learning Styles Questionnaire (CHAEA). To determine the predictive equation, the binary logistic regression model was used using the “Wald backward elimination steps” method, with a sample of 192 first semester students of an agricultural technological baccalaureate, whose ages ranged between 14 and 16 years. A model that includes the dimensions of note taking study planning strategies related to study habits; and self-efficacy for learning, related to self-regulation was obtained. This model explained 37.0 % of the phenomenon. It is concluded the establishment of dropout risk prediction mechanisms could be improve or increase the development of the aforementioned dimensions in order to reduce to a certain extent the risk of dropping out.
publisher	Universidad Autónoma de Tamaulipas
publishDate	2020
url	https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1349
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spelling	oai:ojs.pkp.sfu.ca:article-13492020-08-01T19:26:43Z Predictive model of high school students’ dropout risk in Mexico Modelo predictivo del riesgo de abandono escolar en educación media superior en México Hernández-Jácquez, Luis Fernando Montes-Ramos, Frine Virginia abandono escolar autorregulación del aprendizaje bachillerato hábitos de estudio modelo matemático dropout learning self-regulation high school study habits mathematical model National high school dropout rates in Mexico, fluctuate between 14.5 % and 16.5 %, and empirical research suggests that dropout is mostly associated with failure, and that this in turn, is related to issues such as lack of learning self-regulation and study habits. The objective of this research was to establish a model that predicts the risk of high school students’ drop in Mexico. A quantitative, non-experimental and cross-sectional research was developed. The independent variable, which was the risk of dropping out of school, was assessed through the School Dropout Questionnaire, while the predictive variables study habits, self-regulation learning and learning styles (as requested by the participating institution) were assessed through the Study Habits Questionnaire, the Learning Strategies and Motivation Questionnaire (CEAM II), and the Honey – Alonso Learning Styles Questionnaire (CHAEA). To determine the predictive equation, the binary logistic regression model was used using the “Wald backward elimination steps” method, with a sample of 192 first semester students of an agricultural technological baccalaureate, whose ages ranged between 14 and 16 years. A model that includes the dimensions of note taking study planning strategies related to study habits; and self-efficacy for learning, related to self-regulation was obtained. This model explained 37.0 % of the phenomenon. It is concluded the establishment of dropout risk prediction mechanisms could be improve or increase the development of the aforementioned dimensions in order to reduce to a certain extent the risk of dropping out. Los índices nacionales en materia de abandono escolar o deserción en la educación media superior en México fluctúan entre 14.5 % y 16.5 %, y la investigación empírica sugiere que el abandono se encuentra mayormente asociado a la reprobación, y esta, a su vez, a cuestiones como la falta de autorregulación en el aprendizaje y a los hábitos de estudio. La presente investigación tuvo como objetivo el establecimiento de un modelo para predecir el riesgo de abandono escolar en estudiantes de nivel medio superior en México. Se desarrolló una investigación cuantitativa, no experimental y transversal. La variable independiente, que fue el riesgo de abandono escolar, se valoró a través del Cuestionario de Abandono Escolar, mientras que las variables predictoras fueron los hábitos de estudio, la autorregulación del aprendizaje y los estilos de aprendizaje (por así convenir a la institución), valorados mediante el Cuestionario de Hábitos de Estudio, el Cuestionario de Estrategias de Aprendizaje y Motivación II (CEAM), y el Cuestionario Honey – Alonso de Estilos de Aprendizaje (CHAEA). Para determinar la ecuación predictiva, se utilizó el modelo de regresión logística binaria, mediante el método “pasos hacia atrás de Wald”, con una muestra de 192 estudiantes del primer semestre de un bachillerato tecnológico agropecuario, en su mayoría con edades de entre 14 y 16 años. Se obtuvo un modelo que incluye las dimensiones de estrategias para la planificación del estudio y estrategias para la toma de apuntes, relacionadas con los hábitos de estudio; y autoeficacia para el aprendizaje, relacionada con la autorregulación, explicando el 37.0 % del fenómeno. Se concluye que con el establecimiento de mecanismos de predicción del riesgo de abandono escolar, se podrían mejorar o incrementar las dimensiones ya mencionadas, para reducir en cierta medida el riesgo de abandono escolar. Universidad Autónoma de Tamaulipas 2020-08-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf text/html text/xml https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1349 10.29059/cienciauat.v15i1.1349 CienciaUAT; Vol. 15 No. 1. July-December 2020; 75-85 CienciaUAT; Vol. 15 No. 1: Julio-Diciembre 2020; 75-85 2007-7858 2007-7521 spa https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1349/748 https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1349/745 https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1349/781 Derechos de autor 2020 CienciaUAT

Predictive model of high school students’ dropout risk in Mexico

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