Massachusetts Institute of Technology

For Supporting Local NGOs To Grow And Innovate On The TaRL Approach In Africa

Overview
Teaching at the Right Level (TaRL) is a pedagogical approach that involves evaluating children using a simple assessment tool, and then grouping them according to learning level rather than age or grade.The Abdul Latif Jameel Poverty Action Lab (J-PAL) at the Massachusetts Institute of Technology and its partner Pratham have extensively evaluated this approach, showing that it substantially raises reading and math learning outcomes. With this grant, J-PAL and Pratham will launch a competitive implementation funding window for local African NGOs. These NGOs will develop and expand locally grounded approaches to TaRL, share innovations with and learn from the TaRL Africa Community of Practice, and support governments considering implementing TaRL.
About the Grantee
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www.mit.edu 
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77 Massachusetts Avenue 26-237, Cambridge, MA, 02139-4307, United States
Grants to this Grantee
for CEEPR’s Industrial Strategy Economic Monitor  
A team at MIT, in collaboration with researchers at Stanford and Employ America, is developing the Industrial Strategy Economic Monitor to assess progress implementing U.S. industrial strategy. The monitor will feature a data tool enabling users to easily visualize and download data including on employment, input costs, investment, output, and trade and a dashboard summarizing data by industry and production stage. It will facilitate close-to-real-time assessment of tailwinds and headwinds for targeted industries and the broader macroeconomy, spur debate and research on the best way to evaluate industrial strategies, and promote high-quality, nonpartisan analysis of the industrial strategy experiment.
for support of the AI + Open Education Initiative  
MIT Open Learning transforms education at MIT and around the globe through innovative digital technologies. With this grant, MIT Open Learning will solicit rapid response papers and multimedia projects from stakeholders in the United States and internationally to articulate how generative AI might accelerate (or hinder) the promise of open education to offer engaging learning experiences. This work will draw upon MITs connections with trailblazers who are shaping AI and open education, and it will inform approaches for developing effective teaching practices and bolstering an inclusive open education field responsive to diverse stakeholders. (Substrategy: Field Building)
for support of the Election Data and Science Lab  
The MIT Election Data and Science Lab advances and disseminates scientific knowledge about the conduct of elections, primarily in the United States but with attention to the rest of the world. By addressing the multiple audiences of academic researchers, the general public, and practitioners, it serves a unique role among individuals and institutions dedicated to improving the conduct of American elections, and it supports a growing network of election science research centers across the U.S.

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