Student dropout in times of COVID-19

Autor: Byron Oviedo Bayas, Evelym Ruth Morán Morán, Lelly María Useche Castro
Rok vydání: 2022
Předmět:
Zdroj: International journal of health sciences. :13869-13879
ISSN: 2550-696X
2550-6978
Popis: This article presents a study on student dropout in COVID19 time. As a case study, the socioeconomic and academic performance data of students of the State Technical University of Quevedo, Ecuador in the periods from 2019 to 2022 where educational activities were developed in virtual modality are analyzed. With the requested information, the objective variable (Permanence) was constructed and a process of exploration and analysis of the information was carried out. From this process, 58 variables were chosen and used for the construction of two classification models using Decision Trees and Logistic Regression. Of the algorithms studied, Decision Trees was the best model for identifying students who dropped out, with a value higher than 95% correct classification.
Databáze: OpenAIRE