Summary
Sierra Leone, like many low- and middle-income countries (LMICs), faces persistent challenges in deploying qualified teachers across its schools equitably. In 2024, the Teaching Service Commission (TSC), with support from EdTech Hub, the Learning Generation Initiative, and Fab Inc., introduced an innovative matching algorithm in the teacher deployment process.
The algorithm aimed to increase transparency and equity by incorporating data on teacher preferences, pupil-to-qualified-teacher ratios (PQTR), and school locations. This system demonstrated that algorithm-supported deployment can increase fairness in teacher placement and promote transparency and efficiency.
However, the initiative also exposed governance and data limitations, including inconsistencies in teacher records and tensions between automated decisions and actors accustomed to discretionary control over placements.
This brief highlights key findings from qualitative and quantitative research of the 2024 deployment process undertaken by the Learning Generation Initiative, Fab Inc., and EdTech Hub, and provides actionable recommendations to improve the system.
Authors and contributors
- Adam, Taskeen (Author)
- Frazer, Madleen (Author)
- Godwin, Katie (Author)
- Haßler, Björn (Author)
- Mackintosh, Alasdair (Author)
Citation
Frazer, M. M., Adam, T., Godwin, K., Mackintosh, A., & Haßler, B. (2025). Transforming Teacher Deployment: Lessons from a matching algorithm tool. EdTech Hub. https://doi.org/10.53832/edtechhub.1114. Available at https://docs.edtechhub.org/lib/F5557ITX.
Link to this record
https://docs.edtechhub.org/lib/F5557ITX
Key themes
- Data
- School administrators and senior leadership team
- Teachers
- Urban schools
Type
- Policy Brief
