The COVID-19 Situational Analysis Lessons Learned research project was launched by iMMAP in 2021 to document the changing data landscape during the pandemic. The project covered five humanitarian sectors—Education, Food Security, Livelihoods, Protection, and WASH— and six countries—Bangladesh, Burkina Faso, Colombia, DRC, Nigeria, and Syria. The research sought to understand how COVID-19 affected data availability and data quality, how humanitarian actors adapted to these changes, and what lessons learned can be gleaned from this experience. This report focuses on the Education sector.
The research approach included a desk review of iMMAP monthly reports on the pandemic and other sources, secondary analysis of quantitative data from the DEEP platform, and key informant interviews (KIIs) with Education Cluster Coordinators in the target countries. The research was conducted between mid-July and early September 2021.
The countries examined in this study had diverse experiences with data collection in the education sector during COVID-19. While it reasonably could have been assumed that data availability and data quality would have declined during the pandemic, this was not necessarily the case in all contexts; some countries found that the increased urgency of COVID-19 and resulting attention increased data collection efforts. However, the requirement for remote data collection in most countries led to a cascading series of challenges that required adaptation. Commonly cited challenges included the need for additional resources (human, financial, and time) to implement remote data collection approaches, and/or health protection measures during adapted in-person data collection; the inability to acquire a representative sample of respondents given the reliance on phone- or internet-based data collection methods; and access constraints due to lockdowns. Despite the additional resources dedicated to data collection in some cases, the quality of information was still generally below the pre-pandemic benchmark. Notwithstanding these difficulties, the planning and implementation of education activities proceeded during the pandemic.
Educator actors reported making do with the information they had available, which in some cases was actually better than prior to the pandemic.
The challenges posed by data collection during the pandemic did provide an opportunity for education actors to develop new tools or ways of working. In Burkina Faso, Colombia, Nigeria, and Syria (Turkey Cross-Border Hub), the Education Cluster developed new frameworks and tools, and improved or initiated new remote data collection methodologies that will continue to be used in the future. In DRC, the shift to online Cluster meetings provided an opportunity for partners who previously did not join meetings to call in remotely; however, in several countries, online meetings proved difficult for some partners, and led to decreased Cluster communication and participation. In Nigeria, the increased reliance on national actors during the pandemic has jump-started a sustained localization effort.
The rest of the report will proceed as follows. First, an introduction on the project is presented, followed by an explanation of the research methods. Next, the key findings are presented, organized by data availability, data quality, and adapted ways of working. The conclusion offers cross-country observations and high-level takeaways, followed by recommendations and overall lessons learned.