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- W4200580604 abstract "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 Italian university." @default.
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- W4200580604 date "2021-12-22" @default.
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- W4200580604 title "Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques" @default.
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- W4200580604 doi "https://doi.org/10.1080/03075079.2021.2018415" @default.
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