Evidence Library – The EdTech Hub - Custom feed
Evidence Library – The EdTech Hub
https://docs.edtechhub.org/lib/
2024-03-29T04:11:29.001640+00:00
https://docs.edtechhub.org/lib/atom.xml?creator=%22Angrist,+Noam%22
Kerko
Stemming learning loss during the pandemic: A rapid randomized trial of a low-tech intervention in Botswana
https://docs.edtechhub.org/lib/VDBNW37T
2024-03-15T16:59:07Z
2024-03-18T21:31:39Z
The COVID-19 pandemic has closed schools for over 1.6 billion children, with potentially longterm consequences. This paper provides some of the first experimental evidence on strategies to minimize the fallout of the pandemic on education outcomes. We evaluate two low-technology interventions to substitute schooling during this period: SMS text messages and direct phone calls. We conduct a rapid trial in Botswana to inform real-time policy responses collecting data at fourto six-week intervals. We present results from the first wave. We find early evidence that both interventions result in cost-effective learning gains of 0.16 to 0.29 standard deviations. This translates to a reduction in innumeracy of up to 52 percent. We show these results broadly hold with a series of robustness tests that account for differential attrition. We find increased parental engagement in their child’s education and more accurate parent perceptions of their child’s learning. In a second wave of the trial, we provide targeted instruction, customizing text messages to the child's learning level using data from the first wave. The low-tech interventions tested have immediate policy relevance and could have long-run implications for the role of technology and parents as substitutes or complements to the traditional education system.
Angrist, Noam
Bergman, Peter
Brewster, Caton
Matsheng, Moitshepi
2020
en
Stemming learning loss during the pandemic: A rapid randomized trial of a low-tech intervention in Botswana
Practical Lessons for Phone-Based Assessments of Learning
https://docs.edtechhub.org/lib/SIUERIEE
2023-11-29T19:59:57Z
2023-11-29T20:02:08Z
Angrist, Noam
Bergman, Peter
Evans, David K.
Hares, Susannah
Jukes, Matthew C. H.
Letsomo, Thato
2020-07
en
Practical Lessons for Phone-Based Assessments of Learning
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions using the New Learning-Adjusted Years of Schooling Metric
https://docs.edtechhub.org/lib/MFJLAVX6
2023-10-17T10:54:55Z
2023-10-17T10:55:38Z
Angrist, Noam
Evans, David K.
Filmer, Deon
Glennerster, Rachel
Rogers, F. Halsey
Sabarwal, Shwetlena
2020-10-21
The World Bank
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions using the New Learning-Adjusted Years of Schooling Metric
Building Resilient Education Systems: Evidence from Large-Scale Randomized Trials in Five Countries
https://docs.edtechhub.org/lib/AFKK5JK7
2023-10-09T10:45:45Z
2023-10-09T10:45:55Z
Angrist, Noam
Ainomugisha, Micheal
Bathena, Sai Pramod
Bergman, Peter
Crossley, Colin
Cullen, Claire
Letsomo, Thato
Matsheng, Moitshepi
Panti, Rene Marlon
Sabarwal, Shwetlena
Sullivan, Tim
05/2023
en
Building Resilient Education Systems: Evidence from Large-Scale Randomized Trials in Five Countries
Learning Curve: Progress in the Replication Crisis
https://docs.edtechhub.org/lib/48MA4RDL
2023-10-09T10:40:32Z
2023-10-09T10:40:40Z
We present detailed monitoring data across a five-country randomized trial of phone-based targeted tutoring–one of the largest multicountry replication efforts in education to date. We study an approach shown to work in Botswana and replicated in India, Kenya, Nepal, the Philippines, and Uganda. While the existing literature often finds diminishing effects as proof-of-concept studies are replicated and scaled, we find the opposite: implementation fidelity (the degree of targeted educational instruction) improves across replications and over time. This demonstrates that replication is not intractable; rather, equipped with mechanisms to learn from experience, organizational “learning curves” can enable effective replication and scale-up.
Angrist, Noam
Cullen, Claire
Ainomugisha, Micheal
Bathena, Sai Pramod
Bergman, Peter
Crossley, Colin
Letsomo, Thato
Matsheng, Moitshepi
Panti, Rene Marlon
Sabarwal, Shwetlena
Sullivan, Tim
2023-05-01
https://doi.org/10.1257/pandp.20231009
2574-0768, 2574-0776
en
Learning Curve: Progress in the Replication Crisis
Experimental evidence on learning using low-tech when school is out
https://docs.edtechhub.org/lib/BBFICUKT
2023-10-09T10:36:48Z
2023-10-09T10:37:00Z
Angrist, Noam
Bergman, Peter
Matsheng, Moitshepi
2022-06-13
https://doi.org/10.1038/s41562-022-01381-z
2397-3374
en
Experimental evidence on learning using low-tech when school is out
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions using the New Learning-Adjusted Years of Schooling Metric
https://docs.edtechhub.org/lib/UZH2P3ET
2023-07-14T09:27:04Z
2023-07-14T09:30:53Z
Angrist, Noam
Evans, David K.
Filmer, Deon
Glennerster, Rachel
Rogers, F. Halsey
Sabarwal, Shwetlena
2020-10-21
https://doi.org/10.1596/1813-9450-9450
en
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions using the New Learning-Adjusted Years of Schooling Metric
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions using the New Learning-Adjusted Years of Schooling Metric
https://docs.edtechhub.org/lib/UZH2P3ET
2023-07-14T09:27:04Z
2023-07-14T09:30:53Z
Angrist, Noam
Evans, David K.
Filmer, Deon
Glennerster, Rachel
Rogers, F. Halsey
Sabarwal, Shwetlena
2020-10-21
https://doi.org/10.1596/1813-9450-9450
en
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions using the New Learning-Adjusted Years of Schooling Metric
Building back better to avert a learning catastrophe: Estimating learning loss from COVID-19 school shutdowns in Africa and facilitating short-term and long-term learning recovery
https://docs.edtechhub.org/lib/7MUIIRXU
2022-12-09T13:01:31Z
2022-12-09T13:03:22Z
We model learning losses due to the COVID-19 pandemic and the potential for cost-effective strategies to build back better. Data from Early Grade Reading Assessments in Ethiopia, Kenya, Liberia, Tanzania, and Uganda suggest half to over a year’s worth of learning loss. In modeling losses over time, we found that learning deficits for a child in grade 3 could lead to 2.8 years of lost learning by grade 10. While COVID-19 has stymied learning, bold, learning-focused reform consistent with the literature reviewed in this paper—specifically reform on targeted instruction and structured pedagogy—could improve learning even beyond pre-COVID-19 levels.
Angrist, Noam
de Barros, Andreas
Bhula, Radhika
Chakera, Shiraz
Cummiskey, Chris
DeStefano, Joseph
Floretta, John
Kaffenberger, Michelle
Piper, Benjamin
Stern, Jonathan
2021-07-01
https://doi.org/10.1016/j.ijedudev.2021.102397
0738-0593
en
Building back better to avert a learning catastrophe: Estimating learning loss from COVID-19 school shutdowns in Africa and facilitating short-term and long-term learning recovery
Remote Learning: Evidence from Nepal during COVID-19
https://docs.edtechhub.org/lib/F89QL28Q
2022-07-28T21:20:19Z
2022-07-28T21:21:21Z
This note discusses early results from a distance education program on foundational numeracy for primary school students in Nepal during Coronavirus (COVID-19) evaluated in a randomized trial. The trial included 3,700 households with children in public school (grades 3-5). It provided support for foundational numeracy through mobile phone-based tutoring. The trial tested delivery through public school teachers and also through NGO facilitators. It led to a 30 percent increase in foundational numeracy, with teachers being slightly more effective at producing learning gains than NGO facilitators. These results suggest that instructional support through mobile phones can be a high-access and low-cost approach to providing instruction at scale
Radhakrishnan, Karthika
Sabarwal, Shwetlena
Sharma, Uttam
Cullen, Claire
Crossley, Colin
Letsomo, Thato
Angrist, Noam
2021-07
English
http://creativecommons.org/licenses/by/3.0/igo
Remote Learning: Evidence from Nepal during COVID-19
Limiting Learning Loss using Phone-based Programming during Covid-19 in Botswana
https://docs.edtechhub.org/lib/S6P3E5AS
2022-07-28T21:20:19Z
2022-07-28T21:21:30Z
Working in Botswana, researchers rapidly evaluated a phone-based remote learning program aimed at keeping children engaged with math during the Covid-19 pandemic. Students who received weekly SMS messages and phone calls to review math exercises increased their math skills after twelve weeks, while students who received only SMS messages did not.
Angrist, Noam
Bergman, Peter
Brewstar, Caton
Matsheng, Moitshepi
2020
en
Limiting Learning Loss using Phone-based Programming during Covid-19 in Botswana
School’s Out: Experimental Evidence on Limiting Learning Loss Using “Low-Tech” in a Pandemic
https://docs.edtechhub.org/lib/YHH4SI2X
2022-01-18T20:45:36Z
2022-08-04T17:02:41Z
Schools closed extensively during the COVID-19 pandemic and occur in other settings, such as teacher strikes and natural disasters. This paper provides some of the first experimental evidence on strategies to minimize learning loss when schools close. We run a randomized trial of low-technology interventions – SMS messages and phone calls – with parents to support their child. The combined treatment cost-effectively improves learning by 0.12 standard deviations. We develop remote assessment innovations, which show robust learning outcomes. Our findings have immediate policy relevance and long-run implications for the role of technology and parents as partial educational substitutes when schooling is disrupted.
Angrist, Noam
Bergman, Peter
Matsheng, Moitshepi
2020-12
School’s Out: Experimental Evidence on Limiting Learning Loss Using “Low-Tech” in a Pandemic
Global Dataset on Education Quality : A Review and Update (2000-2017)
https://docs.edtechhub.org/lib/MCNGDVIH
2021-07-27T13:54:04Z
2021-07-27T13:54:35Z
Patrinos, Harry Anthony
Angrist, Noam
2018
en
Global Dataset on Education Quality : A Review and Update (2000-2017)
Planning for School Reopening and Recovery After COVID-19
https://docs.edtechhub.org/lib/M8UVBAGZ
2021-06-10T12:57:05Z
2021-06-10T12:57:44Z
Carvalho, Shelby
Rossiter, Jack
Angrist, Noam
Hares, Susannah
Silverman, Rachel
2020
en
Planning for School Reopening and Recovery After COVID-19
Learning-Adjusted Years of Schooling (LAYS): Defining A New Macro Measure of Education
https://docs.edtechhub.org/lib/TP9IZVSC
2021-05-09T21:19:45Z
2023-02-17T12:07:25Z
Filmer, Deon
Rogers, Halsey
Angrist, Noam
Sabarwal, Shwetlena
2018
en
© World Bank. https://openknowledge.worldbank.org/handle/10986/30464 License: CC BY 3.0 IGO.
Learning-Adjusted Years of Schooling (LAYS): Defining A New Macro Measure of Education
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions Using the New Learning-Adjusted Years of Schooling Metric
https://docs.edtechhub.org/lib/67PNDWSU
2020-10-22T12:54:35Z
2022-12-19T10:15:40Z
Many low- and middle-income countries lag far behind high-income countries in educational access and student learning. Limited resources mean that policymakers must make tough choices about which investments to make to improve education. Although hundreds of education interventions have been rigorously evaluated, making comparisons between the results is challenging. Some studies report changes in years of schooling; others report changes in learning. Standard deviations, the metric typically used to report learning gains, measure gains relative to a local distribution of test scores. This metric makes it hard to judge if the gain is worth the cost in absolute terms. This paper proposes using learning-adjusted years of schooling (LAYS)—which combines access and quality and compares gains to an absolute, cross-country standard—as a new metric for reporting gains from education interventions. The paper applies LAYS to compare the effectiveness (and cost-effectiveness, where cost is available) of interventions from 150 impact evaluations across 46 countries. The results show that some of the most cost-effective programs deliver the equivalent of three additional years of high-quality schooling (that is, schooling at quality comparable to the highest-performing education systems) for just $100 per child—compared with zero years for other classes of interventions.
Angrist, Noam
Evans, David K.
Filmer, Deon
Glennerster, Rachel
Rogers, F. Halsey
Sabarwal, Shwetlena
2020
en
http://creativecommons.org/licenses/by/3.0/igo
How to Improve Education Outcomes Most Efficiently? A Comparison of 150 Interventions Using the New Learning-Adjusted Years of Schooling Metric
Planning for School Reopening and Recovery After COVID-19: An Evidence Kit for Policymakers
https://docs.edtechhub.org/lib/U3VEH3WA
2020-08-18T08:13:26Z
2021-02-14T19:54:52Z
Carvalho, Shelby
Rossiter, Jack
Angrist, Noam
Hares, Susannah
Silverman, Rachel
2020
Planning for School Reopening and Recovery After COVID-19: An Evidence Kit for Policymakers
Stemming Learning Loss During the Pandemic: A Rapid Randomized Trial of a Low-Tech Intervention in Botswana
https://docs.edtechhub.org/lib/7YTYUC4P
2020-08-12T15:36:02Z
2023-05-26T19:38:33Z
The COVID-19 pandemic has closed schools for over 1.6 billion children, with potentially long-term consequences. This paper provides some of the first experimental evidence on strategies to minimize the fallout of the pandemic on education outcomes. We evaluate two low-technology interventions to substitute schooling during this period: SMS text messages and direct phone calls. We conduct a rapid trial in Botswana to inform real-time policy responses collecting data at four- to six-week intervals. We present results from the first wave. We find early evidence that both interventions result in cost-effective learning gains of 0.16 to 0.29 standard deviations. This translates to a reduction in innumeracy of up to 52 percent. We find increased parental engagement in their child’s education and more accurate parent perceptions of their child’s learning. In a second wave of the trial, we provide targeted instruction, customizing text messages to the child's learning level using data from the first wave. The low-tech interventions tested have immediate policy relevance and could have long-run implications for the role of technology and parents as substitutes or complements to the traditional education system.
Angrist, Noam
Bergman, Peter
Brewster, Caton
Matsheng, Moitshepi
2020
https://doi.org/10.2139/ssrn.3663098
1556-5068
en
Stemming Learning Loss During the Pandemic: A Rapid Randomized Trial of a Low-Tech Intervention in Botswana
Practical Lessons for Phone-Based Assessments of Learning
https://docs.edtechhub.org/lib/ESLUMEE3
2020-07-06T09:44:35Z
2022-08-04T17:02:08Z
School closures affecting more than 1.5 billion children are designed to prevent the spread of current public health risks from the COVID-19 pandemic, but they simultaneously introduce education risks as well as new, longer run health risks, via lost education. While some studies measure student involvement in educational activities during the crisis through phone-based surveys, the literature on assessing learning by phone is almost nonexistent, despite the fact that learning loss has major implications for school dropout and rising inequality. In this article, we draw on our pilot testing of phone-based assessments in Botswana, along with the existing literature on oral testing of reading and mathematics, to propose a series of preliminary principles to guide researchers and service providers as they try phone-based learning assessments. We provide guidance to help teams (1) ensure that children are not put at risk, (2) test the reliability and validity of phone-based measures, (3) use simple instructions and practice items to ensure the assessment is focused on the target skill, not general language and test-taking skills, (4) adapt the items from oral assessments that will be most effective in phone-based assessments, (5) keep assessments brief while still gathering meaningful learning data, (6) learn from the speed and confidence of responses, (7) use effective strategies to encourage respondents to pick up the phone, and (8) build rapport with adult caregivers and youth respondents.
Angrist, Noam
Bergman, Peter
Evans, David K.
Hares, Susannah
Jukes, Matthew C. H.
Letsomo, Thato
July 2020
https://doi.org/10.1136/bmjgh-2020-003030
2059-7908
en
Practical Lessons for Phone-Based Assessments of Learning
Learning-adjusted years of schooling (LAYS): Defining a new macro measure of education
https://docs.edtechhub.org/lib/9SKUVUJ9
2020-04-03T16:20:46Z
2022-04-12T11:13:09Z
The standard summary metric of education-based human capital used in macro analyses is a quantity-based one: The average number of years of schooling in a population. But as recent research shows, students in different countries who have completed the same number of years of school often have vastly different learning outcomes. We therefore propose a new summary measure, the Learning-Adjusted Years of Schooling (LAYS). This measure combines quantity and quality of schooling into a single easy-to-understand metric of progress, revealing considerably larger cross-country education gaps than the standard metric. We show that the comparisons produced by this measure are robust to different ways of adjusting for learning and that LAYS is consistent with other evidence, including other approaches to quality adjustment. Like other learning measures, LAYS reflects learning, and barriers to learning, both inside and outside of school; also, cross-country comparability of LAYS rests on assumptions related to learning trajectories and the validity, reliability, and comparability of test data. Acknowledging these limitations, we argue that LAYS nonetheless improves on the standard metric in key ways.
Filmer, Deon
Rogers, Halsey
Angrist, Noam
Sabarwal, Shwetlena
February 19, 2020
https://doi.org/10.1016/j.econedurev.2020.101971
0272-7757
en
Learning-adjusted years of schooling (LAYS): Defining a new macro measure of education