Big Data Analytics to Measure the Performance of Higher Education Students with Online Classes


Abstract:

The pandemic that hit the world in 2020 created a transition period from classes to an e-learning environment. In this type of teaching, a lot of data is generated about different topics that can help improve the class’s daily routine. This paper presents an online case study performed during the 1st semester of the 2020/2021 school year. Online data were analysed in order to understand the students’ behaviour and the course’s success regarding the TechTeach methodology. This data was collected through the ioEduc platform, used in every class, and stored information about the evaluation and day-to-day work. With this research work, it was possible to verify a strong relationship between high attendance and class participation (online activity) with excellent academic performance. In this study, 77% of the students could take a final grade above 15, most of whom attended all classes.

Año de publicación:

2022

Keywords:

  • OLAP cube
  • Data Analysis
  • BIG DATA
  • Unstructured Data

Fuente:

googlegoogle
scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Análisis de datos
  • Tecnología educativa

Áreas temáticas:

  • Programación informática, programas, datos, seguridad
  • Escuelas y sus actividades; educación especial
  • Métodos informáticos especiales