This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…

The performance of a school system can be evaluated through the learning levels of the pupils, usually summarized by school mean scores. The variability of the mean scores among schools is rarely studied in detail, though it is a crucial issue especially in primary schools: in fact, a high variability among schools raises doubts on the capacity of…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…