Luis Fernando Hernández-Jácquez, Frine Virginia Montes-Ramos
{"title":"Modelo predictivo del riesgo de abandono escolar en educación media superior en México","authors":"Luis Fernando Hernández-Jácquez, Frine Virginia Montes-Ramos","doi":"10.29059/CIENCIAUAT.V15I1.1349","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":42451,"journal":{"name":"CienciaUat","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CienciaUat","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29059/CIENCIAUAT.V15I1.1349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 3
Abstract
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.