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This paper is one of a series of research studies in the project on the Impact of GIS-Supported Teacher Allocation in Sierra Leone led by EdTech Hub and research partners Fab Inc. and the Learning Generation Initiative. In this study, we generate new evidence and insights from Sierra Leone, where the government has recently shifted to a centralised, tech-enabled teacher deployment process, which used a preference matching algorithm. This paper seeks to understand how these changes impacted decision-making on teacher allocation, while a companion paper, focusing on a quantitative analysis of the research, titled 'Data-Driven Teacher Deployment in Sierra Leone', examines the practicalities of the same process to understand the impact of the matching algorithm on equitable teacher allocation and other policy goals. See the related resources below for a link to the companion paper. An output of the EdTech Hub, https://edtechhub.org/
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A companion paper associated with this research, titled 'Data-Driven Teacher Deployment in Sierra Leone', examines the impact of the implementation of the matching algorithm on equitable teacher allocation and other policy goals and includes a quantitative analysis of the study. It is available in the EdTech Hub Evidence Library at https://docs.edtechhub.org/lib/ICRSXHTV
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