Data Pre-processing and Data Generation in the Student Flow: case Study

Luís Cavique ^[1] ^[2] ; Paulo Pombinho ^[2] ; Tallón-Ballesteros, Antonio J. ^[3] ; Luís Correia ^[2]
1. [1] Universidade Aberta
  
  Universidade Aberta
  
  Socorro, Portugal
2. [2] Universidade de Lisboa
  
  Universidade de Lisboa
  
  Socorro, Portugal
3. [3] Universidad de Huelva
  
  Universidad de Huelva
  
  Huelva, España
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Localización: Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference: Guimarães, Portugal; November 4–6, 2020. Proceedings / Cesar Analide (ed. lit.), Paulo Novais (ed. lit.) , David Camacho Fernández (ed. lit.) , Hujun Yin (ed. lit.), Vol. 2, 2020 (Part II), ISBN 978-3-030-62365-4, págs. 35-43
Idioma: inglés
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Resumen
- Education covers a range of sectors from kindergarten to higher education. In the education system, each grade has three possible outcomes: dropout, retention and pass to the next grade. In this work, we study the data from the Department of Statistics of Education and Science (DGEEC) of the Education Ministry. DGEEC maintains those outcomes for each school year, therefore, this study seeks a longitudinal view based on student flow. The document reports the data pre-processing, a stochastic model based on the pre-processed data and a data generation process that uses the previous model.