Exploring Alternative Mechanisms for Recognised Educational Certification in Contexts of Fragmented Governance and Displacement
Summary
Children and young people affected by fragmented governance and protracted displacement increasingly complete their education without access to recognised, portable certification. Without such certification, learners are prevented from progressing to higher education, technical and vocational education and training, and formal employment. As a result, individual and national opportunities for stabilisation and recovery are undermined. It is necessary to consider the opportunities and barriers of alternative mechanisms for educational certification.
Assessment and certification systems are typically organised around summative examinations administered by a single internationally recognised government. These systems assume continuity: stable schooling, safe mobility to examination sites, reliable identity documentation, and efficient, quality-assured administrative procedures. In contexts of fragmented governance and protracted displacement, these conditions are rare. Learning may continue through state, de facto, or community provision, but widely recognised certification is available to only the most privileged few.
This rapid review examines barriers to, and plausible pathways for, recognised pre-tertiary certification in fragmented governance contexts. It applies a political economy lens, focusing on actors, incentives, legitimacy claims, and resources, to understand how assessment, certification, and recognition operate under contested authority. Methodologically, it uses a rapid review approach drawing on two case studies (Sudan and Myanmar), publicly available English-language secondary sources, and light-touch key-informant inputs. This is not a “best practice” guide but an analysis of how certification systems function and falter under fragmentation. It also identifies quality standards that would serve pre-tertiary learners in contrast to existing alternative certification models.
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