4th KIX Knowledge Café on Statistical Processes that make Education Data Usable and Credible

The 4th KIX Knowledge Café examined the statistical processes that determine whether education data can be trusted and used. Convened by AU-IPED under the GPE KIX Africa 19 Hub, the session brought together education planners, EMIS practitioners, statisticians, researchers and development partners for a country-led exchange on data validation, quality assurance, harmonization, documentation and institutional coordination.

The consistent message was that collecting more data, or collecting it more frequently, does not automatically result in better statistics or better decisions. Credibility is established in the processes between collection and use - through checks for completeness, plausibility, consistency, reproducibility and timeliness; through validation at source; and through clear documentation of how figures are produced.

“More frequent data or greater volumes of data do not necessarily produce better statistics or better decisions. Credibility is won or lost during processing…through validation, quality assurance, harmonization and documentation.”

— Polycarp Otieno, Education Specialist, UNICEF Eastern and Southern Africa Regional Office

Country presentations demonstrated different stages of EMIS development. Sierra Leone described layered quality controls and independent verification. Malawi presented a largely paper-based system undergoing digitization, supported by a strong institutional relationship with its National Statistical Office but challenged by fragmented subsector platforms. Education officials working in Somaliland described a web-based EMIS combined with paper collection in low-connectivity areas, while identifying gaps in formal validation, statistical capacity, documentation and coordination.

Participants explicitly requested technical and capacity-building support on EMIS interoperability, integrated education data, data-exchange mechanisms, EMIS–NSO collaboration, statistical analysis and validation. The discussion also identified personal-data protection as an emerging priority for future peer learning.