Quality Education India Development Impact Bond
Aligned SDGs
- Quality Education India Development Impact Bond
- General overview
- Location
- Involved organisations
- Outcome metrics
- Results
- SyROCCo reports
- Other resources
- Spreadsheet of data
- Quality Education India Development Impact Bond
- General overview
- Location
- Involved organisations
- Outcome metrics
- Results
- SyROCCo reports
- Other resources
- Spreadsheet of data
General overview
Stage of development: Complete
Policy sector: Education
Date outcomes contract signed: Jul 2018
Start date of service provision: Apr 2018
Capital raised (minimum): USD 3m
Max potential outcome payment: USD 9.18m
Service users: 200k+ individuals
Intervention
The QEI DIB aims to support the education crisis in India by funding four high performing service providers to improve grade appropriate learning outcomes for more than 200,000 primary school aged children over four years. The service providers are KEF, GyanShala, SARD and Pratham Infotech Foundation.The service providers are delivering four interventions with a mix of direct and indirect education model types, including: directly operating classroom (direct), supplementary programmes (direct), and teacher/ school leader training (in-direct).
Target population
Primary school-aged children
Location
Country
- India
Service delivery locations
- Gujarat
- Mumbai
- Uttar Pradesh
- NCR Delhi
Involved organisations
Configuration of contracting parties:
- Framework contract between main parties with individual sub-contracts
Outcome metrics
- Learning outcome improvement 1. Learning outcome improvement: standard deviation (standard points of variation around the mean) as a difference from the comparison group performance. (Directly operating in classrooms)
- Learning outcome improvement 2. Learning outcome improvement: standard deviation (standard points of variation around the mean) as a difference from the comparison group performance. (Remedial programmes)
- Learning outcome improvement 3. Learning outcome improvement: standard deviation (standard points of variation around the mean) as a difference from the comparison group performance. (teacher/principal training)
Powered by SyROCCo SyROCCo reports
The following articles are taken from the Systematic Review of Outcomes Contracts Collaboration (SyROCCo) Machine Learning tool.
The tool is a collaboration between the Government Outcomes Lab and machine learning experts from the University of Warwick, that allows you to navigate and explore data extracted from nearly 2000 academic and grey literature publications related to outcomes-based contracting.
Spreadsheet of data
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