This thesis forecasts future teacher requirements using statistical techniques. By analyzing historical data, the study estimates staffing needs for the coming years, considering factors like student enrollment and additional teaching demands. The results offer actionable insights for optimizing teacher allocation and planning.

Teacher needs in Luxembourg: A statistical analysis to address the current shortage crisis.

OLIVATO, MATTEO
2023/2024

Abstract

This thesis forecasts future teacher requirements using statistical techniques. By analyzing historical data, the study estimates staffing needs for the coming years, considering factors like student enrollment and additional teaching demands. The results offer actionable insights for optimizing teacher allocation and planning.
2023
Teacher needs in Luxembourg: A statistical analysis to address the current shortage crisis.
Forecasting
Teacher attrition
Classification
File in questo prodotto:
File Dimensione Formato  
Olivato_Matteo.pdf

Accesso riservato

Dimensione 3.41 MB
Formato Adobe PDF
3.41 MB Adobe PDF

The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/80896