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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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Published in:Systems Research & Behavioral Science Vol. 30; no. 2; pp. 194 - 204
Main Authors: Hardman, Julie, Paucar‐Caceres, Alberto, Fielding, Alan
Format: Article
Published: Wiley-Blackwell Mar/Apr2013
Subjects:
Manchester Metropolitan University
Higher education
Classroom environment
Achievement gains (Education)
Courseware
Management information systems
Computer software
Online Access:View this record in EBSCOhost