Identifying Institutional Structures for Data Policy and Governance Frameworks: Case for The Education Sector in Kenya
| dc.contributor.author | Eldah Onsomu | |
| dc.contributor.author | Gideon Nyakundi | |
| dc.contributor.author | Japheth Kathenge | |
| dc.date.accessioned | 2026-02-23T09:55:27Z | |
| dc.date.available | 2026-02-23T09:55:27Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | The population aged 35 years and below constitutes 75% of the population in Kenya, with 36.1% of the population aged between 15 and 35 years, presenting a significant development opportunity. If properly educated and skilled, this demographic could drive innovation, productivity, and sustainable development. However, education systems across the sub-Saharan region, Kenya included, often suffer from inefficiencies that stem from weak data coordination and management. This study aims to critically assess the state of data governance in Kenya’s education sector and the effects on education outcomes. Five foundational pillars of data governance—Roles and Responsibilities, Privacy Standards, Policies, Tools and Practices, and Processes and Procedures—were assessed using six key operational dimensions. The overall Data Governance Index (DGI) shows a clear and positive relationship with the Human Development Index (HDI) across Kenya’s counties, confirming that counties with stronger data governance frameworks tend to achieve higher levels of education outcomes and development. Counties with well-structured data systems—characterized by high data quality, accessibility, timeliness, security, metadata documentation, and stewardship—demonstrate stronger planning capabilities, more efficient service delivery, and better outcomes in the education sector. However, main constraints affecting data governance in the education sector include: Undefined roles and responsibilities in counties; Lack of dedicated data teams and committees; Inconsistent funding for data leadership and capacity building; Incomplete or outdated metadata in counties; Lack of standard documentation guidelines and tools and Limited staff awareness and technical capacity. Interventions towards improving data governance in the education sector include: implementing mandatory data quality checks and validation protocols; automating collection processes to reduce manual errors; and providing training on data accuracy and integrity. Enforce encryption, access controls, and multi-factor authentication; Provide regular staff training on cybersecurity; Monitor and report compliance with data protection laws. Develop open-access platforms for education data; Standardize accessibility policies across counties; Create user feedback channels for improvement; Enforce routine data submission timelines; Invest in mobile data collection tools and dashboards; Schedule periodic data audits; Institutionalize stewardship roles and guidelines; Form cross-sectoral education data committees; Allocate dedicated budget lines for data leadership activities; Adopt national metadata standards; Train staff on metadata use and documentation; Establish centralized metadata repositories per county. | |
| dc.identifier.uri | https://publication.aercafricalibrary.org/handle/123456789/4074 | |
| dc.publisher | AERC | |
| dc.title | Identifying Institutional Structures for Data Policy and Governance Frameworks: Case for The Education Sector in Kenya |