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The encyclopedia · Strategy & Leadership · People decision · 2024–2025

Sierra Leone matched teachers to schools by algorithm instead of political postings

A GIS-supported preference-matching algorithm deployed 2,341 new teachers to remote, understaffed schools in the 2024/25 cycle.

Teaching Service Commission, Sierra Leone · Fab Inc · EdTech Hub

the move

Sierra Leone's teacher shortage is unequal: the pupil-to-qualified-teacher ratio is about 44:1 in urban centers but 76:1 in rural areas, and discretionary deployment decisions left remote schools hardest to staff and open to political interference.

In 2024 the Teaching Service Commission, supported by EdTech Hub and Fab Inc, piloted a GIS-supported preference-matching algorithm for the national deployment cycle. Teachers' preferences, school needs, demographics and locations fed a rules-based algorithm that produced the assignments centrally and transparently, with training embedded in the Commission.

Early evaluation of 2,341 new teacher allocations found the majority of Commission priorities met: more qualified teachers passed the licensing exam, and deployments went disproportionately to schools with worse pupil-to-payroll-teacher ratios and to more remote schools — while staff and researchers reported improved fairness, accountability and reduced political interference.

why it works

  • Published rules replaced discretionary judgment, cutting room for favoritism.
  • Teacher preferences were honored within needs-based priorities, aiding retention.
  • GIS mapping made remoteness and need legible in the allocation itself.
  • A centralized process scaled cleanly to thousands of placements a year.
the payoffLet a preference-matching algorithm deploy teachers by needneat

what transfers

When allocation is discretionary, everyone suspects favoritism; an algorithm with published rules makes the assignment fair and the outcome auditable.

what came after

The 2024/25 pilot was the first national-level deployment of a matching algorithm for teachers in Sub-Saharan Africa; the research program continues to track retention and outcomes and to refine the algorithm with the government.

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