- Funding Programme
- Year
- 2022
Forecasting the Teaching Workforce in Italy
The “Forecasting the Teaching Workforce in Italy” project supported the Italian Ministry of Education and Merit (MIM) in gaining a deeper understanding of the main challenges related to the teaching workforce and in developing a forecasting model to accurately estimate the demand and supply of teachers in Italy. The project was funded by the European Union through the Technical Support Instrument (TSI).
Context
The Italian education system faces challenges such as teacher shortages in some areas and surpluses in others, along with issues like uneven teacher distribution, an ageing workforce, and a declining student population. Low salaries and limited career opportunities further reduce the attractiveness of the profession. Launched in July 2023 and running for 19 months, the project had two key objectives:
- Analysing the causes of the mismatch between teacher demand and supply in Italy by exploring challenges through stakeholder consultations and reviewing international best practices (Outcome 1);
- Developing a forecasting model to help MIM accurately predict the future demand for teachers (Outcome 2).
Support delivered
The project included activities such as workshops, interviews with national stakeholders and international experts, and a study visit to Portugal. Additionally, a broader Steering Committee, comprising Ministry of Education and Merit (MIM), National Institute for Documentation, Innovation, and Educational Research (INDIRE), National Institute for the Evaluation of the Education and Training System (INVALSI), European Commission and the provider, has been established to oversee the implementation of the project.
Results achieved
The activities highlighted critical issues in the Italian education system and identified structural challenges such as recruitment difficulties, an ageing workforce and a growing reliance on temporary contracts.
The project also developed a forecasting model to estimate the future demand for teachers and optimise resource planning. The model analyses demand based on student enrolment projections, compares demand with available teacher supply, considering factors like retirements and mobility and focuses on key subject areas, such as STEM.
In the long-term, the project is expected to contribute towards more informed, sound and evidence-based decision-making in educational planning and management.
More about the project
You can read the documents related to the project here: