Early pbkp_rediction of dropout in online courses using Artificial Neural Networks


Abstract:

Increasing technological advances have created the need to implement new teaching methods. Hence, online education was born, which is defined as education mediated by a virtual learning environment. This type of education, not being a traditional classroom education, difficult to monitor students getting high dropout rates. The use of artificial neural networks helps to pbkp_redict the behavior of students using historical data and obtain results in the early stages of their student performance, allowing teachers to define strategies to address the high rate of student dropout and take early actions to avoid it.

Año de publicación:

2020

Keywords:

  • Mooc
  • early pbkp_rediction
  • artificial neural networks
  • online courses
  • DROPOUT
  • tracking logs

Fuente:

scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Aprendizaje automático
  • Tecnología educativa

Áreas temáticas:

  • Escuelas y sus actividades; educación especial