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Edelsbrunner, Peter; Schneider, Michael – Frontline Learning Research, 2013
Musso et al. (2013) predict students' academic achievement with high accuracy one year in advance from cognitive and demographic variables, using artificial neural networks (ANNs). They conclude that ANNs have high potential for theoretical and practical improvements in learning sciences. ANNs are powerful statistical modelling tools but they can…
Descriptors: Prediction, Statistical Analysis, Structural Equation Models, Academic Achievement

Peer reviewed
