Using Rapid Data and Existing Evidence to Mitigate the Educational Impacts of COVID-19 in Peru

• In Event: Using Evidence to Inform Education Delivery during COVID-19

Proposal

A research and policy NGO is implementing a multi-faceted approach with the Ministry of Education in Peru to provide the Ministry with rapid data to mitigate the educational impacts of the COVID-19 pandemic. The three aspects of this engagement enable the Ministry to make evidence-based policy decisions to recommend necessary changes and policies for education delivery during the pandemic:

Monitoring remote learning - Parent-teacher survey guides decision-making: The NGO provides technical support in monitoring the implementation of the national remote education strategy, “I Learn at Home.” Implementers designed a phone survey to better understand the experiences of parents with the program, reaching over 8,000 respondents. The survey provided Minedu with information on its remote learning initiative during its first week of implementation. The success of the survey led Minedu to continue using this methodology and continue feeding the dashboard created during the pandemic. The learnings from the survey provide actionable information to the Ministry on the strategy and ways to improve the delivery and take-up of distance education. Data insights assist the partner in making improvements for better learning delivery and take-up, which include the active role that caregivers play in children's education, family utilization and level of satisfaction with distance education resources, and the efficacy of communications methods (such as phone or WhatsApp) between teachers and parents. For example, learning that 39 percent of respondents had limited internet access allowed the Ministry to explore content and methodologies that are better suited for cell phone screens and avoid file downloads.

Adding value to existing data - machine learning tools improve delivery of tablets for remote learning: This project leverages existing educational administrative data from the Ministry by applying machine learning tools to identify areas where it may be more challenging to deliver tablets for remote learning to students across the country. The use of machine learning techniques allows the Ministry to better design its delivery strategy without having to invest in further data collection. The research team complemented the data on tablet distribution with a survey to parents in areas targeted for tablet delivery to better understand their potential limitations when using the tablets for learning purposes.

Using existing evidence to inform pandemic response: After the Ebola outbreak, many students whose education was interrupted due to the pandemic did not return to school once they reopened. To avoid this experience, the Ministry of Education implemented a previously evaluated intervention that provides students with information about the returns to education through a telenovela-style mini-series, “Choosing a Better Future,” that was found to be effective in reducing student drop-out rates in Peru. The Ministry chose this proven intervention based on existing evidence to be part of the “I Learn at Home” strategy, and broadcasted the videos on national TV to prevent COVID-19-related dropouts. The Ministry also sent text messages to parents nationwide to encourage them to make sure that their children watched the mini-series.

This presentation will discuss the theoretical aspects of the intervention and how they were used to inform key decisions, and the practical constraints policymakers with the Ministry had to balance when developing different delivery methods.

Author

• Juan Hernandez-Agramonte, Innovations for Poverty Action