Educación virtual: Impacto de los factores socioemocionales y pedagógicos en el rendimiento académico basado en redes neuronales y Regresión Stepwise

EasyChair Preprint no. 6287

Abstract

The objective was to determine the impact of socio-emotional and pedagogical factors on the academic performance of students from the UNAM professional school of Public Management and Social Development during the COVID 19 pandemic, based on neural networks and step-by-step regression. Of the 38 indicators of socio-emotional and pedagogical factors applied to 236 students, the stepwise regression model determined 7 significant indicators (pedagogical and personal problems) that impact academic performance, the neural network model determined the importance of influencing performance academic, considering personal difficulties first, followed by pedagogical and family problems. The mean square error for the stepwise regression model is 7.25 and the coefficient of determination was 0.221, for the neural network model the mean square error was 6.78, while the coefficient of determination was 0.256. The students of the professional school of Public Management and Social Development according to the results of both methodologies, pedagogical and personal problems in their academic performance during the COVID 19 pandemic

Keyphrases: academic performance, COVID-19, neural network, Pandemic, tepwise regression

@Booklet{EasyChair:6287,
  author = {José Luis Morales Rocha and Mario Aurelio Coyla Zela and Nakaday Irazema Vargas Torres and Jarol Teófilo Ramos Rojas and Santos Octavio Morillos Valderrama and Genciana Serruto Medina},
  title = {Educación virtual: Impacto de los factores socioemocionales y pedagógicos en el rendimiento académico basado en redes neuronales y Regresión Stepwise},
  howpublished = {EasyChair Preprint no. 6287},

  year = {EasyChair, 2021}}