Do Students Benefit from Blended Instruction? Experimental Evidence from India
This experimental study investigates the causal effect of a teacher capacity building program that promotes blended instruction, on student learning. It will be implemented in government schools in Haryana, India, in collaboration with a large, local NGO (“Avanti Fellows”). The program’s objective is to positively affect the instruction of mathematics and science, in grades nine and ten. The study hypothesizes that student learning improves if teachers are given resources and training, to enrich their instruction with video-based learning materials. Secondly, the study hypothesizes that the intervention’s cost-effectiveness outperforms that of an alternative model of teacher capacity building, which does not rely on infrastructure upgrades and uses printed workbooks only.
- AEA RCT Registration
- J-PAL project description
- USAID Development Innovation Ventures (DIV) Funding
- J-PAL Post-Primary Education (PPE) Initiative Funding
This study investigates the causal effects of repeat, formative performance evaluations, under Chile’s national teacher evaluation system. The study’s main results suggest that student learning, teacher beliefs and teaching behaviors are not positively affected by a teacher’s evaluation, both in the year of the evaluation and in the year thereafter. These findings rest on data-sources with unusually comprehensive coverage of a national education system—positive effects on student performance are thus ruled out precisely. The article moreover confirms that its results are not driven by a teacher’s level of work experience, by student sorting, by systematic attrition, or by its model specification.
This research uses a randomized experiment to investigate the long-run effects of additional education on prosocial behavior. The article builds on an intervention in Cambodia that offered scholarships to students as they were beginning the fourth grade of primary school. The study follows these students as they are now approximately 21 years old. To measure prosocial behavior, I conduct large-scale, in-the-field dictator games (with tangible outcomes, and respondent deception).
With Alejandro Ganimian
We leverage a nationally-representative and previously unpublished dataset on the learning outcomes of 101,084 public-school students in grades 4, 6, and 8 across 18 Indian states and one union territory to diagnose their mathematics skills. Importantly, these data allow us to diagnose their achievement not only in commonly assessed skills (number sense and arithmetic) but also on less frequently assessed skills (geometry, fractions and decimals, measurement). We use a novel psychometric approach to estimate the share of students who can meet fourth-grade standards. We find that the mathematics skills of Indian children may be even lower than previously documented. These children also make less progress than believed. We also document how gender gaps in these skills emerge between grades 4 and 6 and persist in grade 8. Our results indicate that the learning crisis in India may go further than previously diagnosed.
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
With Noam Angrist, Radhika Bhula, Shiraz Chakera, Chris Cummiskey, Joseph DeStefano, John Floretta, Michelle Kaffenberger, Benjamin Piper, and Jonathan Stern
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.
Learning by Doing? Experimental Evidence on Activity-based Instruction in India
With Johanna Fajardo-Gonzalez, Paul Glewwe, and Ashwini Sankar
The number of rigorous studies on “what works” to foster education in less developed countries has strongly increased, but there is surprisingly little evidence on how to improve child learning through changes in instructional practice. We study the effect of an innovative program in Karnataka, India, that promotes activity-based learning through teacher training, community engagement, and additional inputs. In a Randomized Controlled Trial (RCT), we assign 98 administrative units (Gram Panchayats) and 294 of their schools to either receiving the program or not. Our primary outcome of interest is child learning, in mathematics, for students enrolled in grade four (at baseline). The study’s secondary analyses disentangle the effect of individual program components, investigate mediating variables (instructional behaviors, community and parental engagement), and assess the program’s implementation fidelity. Sub-group analyses focus on differential effects by students’ initial skill level, gender, and geographic location (i.e., district).
- AEA RCT Registration
- Registered Report conditionally accepted via pre-results review at the Journal of Development Economics (JDE)
Levers for Learning: Relationships Between School-Level Factors and Literacy Outcomes in Low-Income Schools in Colombia
With Felipe Barrera-Osorio, Sarah Dryden-Peterson, Bethany Mulimbi, Nozomi Nakajima, and Paola Uccelli
We study the correlation between literacy outcomes and four levers for learning – instructional practice; school-community engagement; student, teacher, and parent well-being; and community belonging – in ten public schools in a mid-size city in Colombia, serving similar, low-income communities. We find that (1) some schools show significantly higher literacy outcomes, despite serving similar students; and (2) the most salient school-level factors in explaining literacy performance are higher levels of student sense of belonging and low levels of bullying.
Long-Term Impacts of Alternative Approaches to Increase Schooling: Experimental Evidence from a Scholarship Program in Cambodia
With Felipe Barrera-Osorio and Deon Filmer
This randomized trial investigates the long-term effects of a primary school scholarship program in rural Cambodia. We estimate impacts—nine years after program inception—on educational attainment, cognitive skills, socioemotional outcomes, labor market outcomes, and well-being. Our results point to systematic improvements in attainment, but no average impacts on long-term cognitive or socioemotional outcomes. A merit-based (as opposed to poverty-based) targeting strategy did, however, increase cognitive outcomes, especially for poorer students. The results suggest positive effects on cognition for males. We find no improvements for labor market outcomes, yet positive effects on well-being, driven by recipients of the merit-based scholarships. The findings are robust to alternative approaches of accounting for attrition.
Which Students Benefit from Personalized Learning? Experimental Evidence from a Math Software in Public Schools in India
With Alejandro Ganimian
This is one of the first studies to evaluate the impact of personalized learning delivered through technology in a developing country. We randomly assigned 1,528 students in grades 6-8 in 15 “model” public schools who were using a computer-adaptive learning software to: (a) a control group, in which they were only able to access the activities for their enrolled grade level (i.e., the norm for most software products evaluated in developing countries); or (b) a treatment group, in which they were assigned exercises appropriate for their individual preparation level, across a wide range of grade levels, based on a diagnostic test. After nine months, personalized learning had a null effect on the math achievement of the average student. However, treatment students with low initial performance outperformed their control counterparts by 0.22 standard deviations. Our results suggest that personalized learning is most beneficial for relatively low-performing students, who need help to catch up with their peers.
Which Students Benefit from Practice Exercises? Experimental Evidence from a Math Software in Private Schools in India
With Alejandro Ganimian and Anuja Venkatachalam
This study is one of the first evaluations of independent (i.e., self-guided) practice in math in a developing country. We randomly assigned 4,461 students in grades 4-7 in “unaided” private schools across seven Indian cities who were using a computer-assisted learning software to: (a) a control group, in which they moved from one unit to the next upon completion; or (b) a treatment group, in which they had to complete practice exercises before progressing to the next topic. After six months, the additional practice had a precisely estimated null effect on the math achievement of the average student. However, treatment students with low initial performance outperformed their control counterparts by 0.14 standard deviations (SDs). Our results suggest that independent practice may help private-school students from relatively well-off families in need of catching up with their peers.