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Educate Girls: improving learning outcomes for millions of children in India

Our work with Educate Girls has evolved over several years and provides an example of how in-depth, flexible learning partnerships can help our partners amplify their impact with data and evidence.

 

 

Students in Jahazpur, Rajasthan, settle in for lunch during the Educate Girls development impact bond evaluation. (Photo by Ryan Fauber)

Decision-maker’s challenge

Our work with Educate Girls has evolved over several years and provides an example of how in-depth, flexible Learning Partnerships can help our partners amplify their impact with data and evidence. 

Educate Girls (EG) is a Mumbai-based non-profit organization founded to improve girls’ enrollment in government primary and upper primary schools. They also provide tutoring and curriculum support with community-based volunteers. 

Initially, Educate Girls needed an evaluator to design and conduct a three-year impact evaluation that would determine financial returns for a Development Impact Bond (DIB). But as our work together unfolded, IDinsight and Educate Girls identified other areas where data could help them increase their impact at scale.

Impact opportunity

Beyond the direct impact opportunity of implementing the program, the DIB evaluation allowed Educate Girls and potential funders to understand the impact of their work and work over three years to tweak their model to maximize its effectiveness.

The Development Impact Bond evaluation (2015 – 2018)

Up to four million girls aged 6 to 14 are not enrolled in school in India. Even if enrolled in school, many students are not acquiring foundational skills like reading and basic arithmetic. As part of a Development Impact Bond, Educate Girls would:

  • Reach 7,300 children in 166 schools across 140 villages in Bhilwara, Rajasthan
  • Increase learning gains and increase enrollment of out-of-school girls

The DIB evaluation led by IDinsight allowed Educate Girls and potential funders to understand the impact of Educate Girl’s work. The data also helped EG tweak their model to maximize its effectiveness.

Read more about the development impact bond.

The Learning Partnership (2018 – Present)

Following the DIB, Educate Girls was selected as a 2019 Audacious Project recipient to enable the program to scale to 35,000 villages across northern India in pursuit of the following targets:

  • Enrollment of 1.6 million out-of-school girls, approximately 40% of all out-of-school girls in India, into grades 1 through 10. 
  • Retention of 1.4 million newly enrolled girls. 
  • Improvement in learning outcomes for 1 million girls and boys in grades 3 through 10. 
  • Development of 100,000 adolescent girls with life skills training. 
  • School governance and infrastructure improvement in 40,000 schools that serve 15.1 million boys and girls.

IDinsight is helping Educate Girls reach these goals in a comprehensive learning partnership. As Educate Girls scales, strengthening their ability to find, track, and deliver programming to girls will improve educational outcomes for millions of children. 

Our approach

The Development Impact Bond1

As part of the evaluation for the DIB, we measured two outcomes: learning gains of boys and girls in grades 3-5 and enrollment of out-of-school girls. 

Learning gains, which made up approximately 80% of the final DIB payments, were evaluated in a village-clustered randomized control trial. Enrollment of out-of-school girls, which contributed the remaining ~20% of the payments, was measured using a pre-post evaluation in the 141 villages where treatment schools are located.

The Learning Partnership

As Educate Girls looked to strengthen their implementation, they saw an opportunity to improve their ability to find and track program participants and deliver education services. We worked with the EG team on a suite of improvements to help EG reach more out-of-school girls for the same cost.

A major part of our collaboration is helping EG decide where to expand its operations. EG wanted to maximize the value of their operational resources by running their program in geographies with the highest concentration of out-of-school girls. We used machine learning algorithms to predict which villages would have high concentrations of out-of-school girls. Our analyses estimated that approximately 40% of out-of-school girls live in only 5% of the villages. We worked with EG to incorporate this information into their expansion plans. By focusing on expanding to these villages with high numbers of out-of-school girls, we estimated that EG could identify and reach 600,000 more girls while expending similar levels of resources.

We are also supporting EG to build lean, robust, and decision-oriented monitoring and evaluation systems so that their team has high-quality, timely information to optimize their operations and inform decisions about enrolling, retaining, and teaching more girls. We are also running a rigorous evaluation to provide insights on EG’s ability to change outcomes.

The results

The Development Impact Bond

We found that Educate Girls surpassed the DIB targets for both learning gains and enrollment. The effects of Educate Girls’ program on learning gains were large and statistically significant over the three-year program: 

  • Students in EG schools gained on average an additional 1.08 learning levels, or 28% and 0.31 standard deviations, compared to students in control schools. 
  • By the end of the three-year project, Educate Girls had enrolled 768 out-of-school girls, representing 92% of all identified out-of-school school girls eligible for enrollment. 
    • Educate Girls thus exceeded the enrollment target of 79% by 16%. 

In addition to determining final payments, midline results from IDinsight’s evaluation enabled Educate Girls to fully realize the flexibility in programming provided by the DIB set-up and made effective, data-driven course corrections along the way. The success of the world’s first DIB has enabled Educate Girls to secure more funding to scale up its proven program. 

The Learning Partnership

In the subsequent Learning Partnership, we supported Educate Girls expansion in the following ways: 

  1. Used machine learning to predict the number of out-of-school girls in expansion regions to inform program targeting. IDinsight’s predictions helped EG identify and expand to villages with 2.5x as many out-of-school girls compared to villages where they previously worked.
  2. Strengthened Educate Girls’ monitoring and evaluation (M&E) systems to track program implementation and measure their targeted outputs and taught their staff how to use the new system. Together with EG’s Impact team, we made recommendations for changes to the indicators they track and their data collection and quality processes. We also conducted a Theory of Change workshop for a new program. 
  3. Built dashboards to enable real-time monitoring of program expansion and inform course corrections. We created dashboards linked to Educate Girls’ backend data systems to monitor the progress of 
    • their comprehensive door-to-door survey in expansion regions (covering 8 million households),
    • enrollment of out-of-school-children in schools, and
    • quality issues across Educate Girls program components.
  1. IDinsight helped Educate Girls to transform their A for verifying enrollment of out-of-school girls from a paper-based system to a digital system. We estimate that these process improvements will reduce the time Educate Girls staff spend on enrollment verification by 90%, allowing Educate Girls to identify enrolled girls more quickly and reallocate staff time away from data collection and processing to programming. 
  2. Set up an impact evaluation and external data verification to assess EG’s progress against the Audacious targets from 2020-2024. These activities will provide Educate Girls with high-quality causal evidence on their program impact across key outcomes, which will inform program pivots. IDinsight is collaborating with Sambodhi to design and implement this evaluation.
  1. 1. This Development Impact Bond (DIB) was the first one in the world and was set up to finance Educate Girls’ program in Bhilwara district, Rajasthan. DIBs are a tool for financing social programs in which an investor provides capital up-front to a service provider and earns a return from a donor based on the effectiveness of the program. By shifting the focus from inputs to outcomes and incentivizing service providers to improve programs, DIBs hold the potential to make social programs more cost-effective. The lessons from this world’s first DIB can potentially inform the viability and design of future results-based financing models.