A Data Mining Approach to Predict Undergraduate Students' Performance

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

Martins, MPG (Autor) Outra; Vera L. Miguéis (Autor) FEUP; Fonseca, DSB (Autor) Outra

Ata de Conferência Internacional

Título: Iberian Conference on Information Systems and Technologies, CISTI

Páginas: 1-7

13th Iberian Conference on Information Systems and Technologies, CISTI 2018

13 June 2018 through 16 June 2018

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 4 Citações

Outras Informações

ID Authenticus: P-00P-1J5

DOI: 10.23919/cisti.2018.8399175

Abstract (EN): This paper presents a methodology based on random forest algorithm to predict the undergraduate academic performance of students from a polytechnic institution. The approach followed enabled to select 11 explanatory variables, starting from an initial set of around fifty, which allow to obtain a good predictive performance (R-2=0.79). These variables reveal crucial aspects for the definition of management strategies focused on promoting academic success.

Idioma: Português

Tipo (Avaliação Docente): Científica

Nº de páginas: 7