Predicting Students' Progression in Higher Education by Using the Random Forest Algorithm.

This paper proposes the use of data available at Manchester Metropolitan University to assess the variables that can best predict student progression. We combine virtual learning environment (VLE) and management information systems student records datasets and apply the Random Forest (RF) algorithm...

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Publicado en:	Systems Research & Behavioral Science Vol. 30; no. 2; pp. 194 - 204
Autores principales:	Hardman, Julie, Paucar‐Caceres, Alberto, Fielding, Alan
Formato:	Artículo
Publicado:	Wiley-Blackwell Mar/Apr2013
Materias:	Manchester Metropolitan University Higher education Classroom environment Achievement gains (Education) Courseware Management information systems Computer software
Acceso en línea:	Ver este registro en EBSCOhost