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Download full textEdelsbrunner, 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
Politis, John; Politis, Denis – Electronic Journal of e-Learning, 2016
Online learning is becoming more attractive to perspective students because it offers them greater accessibility, convenience and flexibility to study at a reduced cost. While these benefits may attract prospective learners to embark on an online learning environment there remains little empirical evidence relating the skills and traits of…
Descriptors: Electronic Learning, Synchronous Communication, Integrated Learning Systems, Online Courses
