Re-evaluating learning.

AuthorDuflo, Esther
PositionResearch Summaries

Developing countries have rapidly increased access to primary school, but the quality of education has remained low. Many children are now in school, but they are hardly learning. In India, for example, a 2007 nationwide survey by Pratham (1), a large education nonprofit, found that 97 percent of the of-age children are in primary school, but only 51 percent of third graders could read a simple first-grade paragraph, and only 33 percent could do simple subtraction. If developing countries are to attain meaningful universal primary education, they must improve the quality of education.

This is a formidable task: for starters, rising enrollment, unaccompanied by additional budget outlays, has increased pressure on available resources. Classes in the lower grades often are very large, and the children arrive with wide-ranging levels of preparedness. These large and heterogeneous classes can challenge pedagogy. The curricula, set nationally and often inherited in large part from the colonial period, are not adapted to local challenges and needs. Too often, they presuppose competencies that many of the first-generation learners do not have. Besides these challenges, teachers face lax incentives, so teacher motivation is low: many teachers do not come to school and even those who do come do not always teach.

What can be done to improve education quality in developing countries? My recent research suggests some answers to this question. My approach has centered on using randomized evaluations to identify the causal effects of promising education programs.

In a randomized evaluation, from the program's inception the researcher works in close collaboration with the practitioner. The program gets assigned randomly to part of the sample--the treatment group--which is compared to the rest, the comparison group. In recent years, there has been an explosion in research using randomized evaluations in development economics. Development economists have pioneered the use of research partnerships with non-governmental organizations (NGOs) or private companies. These partnerships often allow greater control over the research design and, increasingly often, input into the program design itself. Rachel Glennerster, Michael Kremer, and I (2) describe the various ways of incorporating random assignment in the evaluation design, and the practical challenges that go with it.

In "The Experimental Approach to Development Economics", Abhijit Banerjee and I (3) review the evolution of the use of randomization in development economics research. Much like earlier work in labor economics, health, and education, the experimental research in development economics started with concerns over the reliable identification of program effects in the face of complex and multiple channels of causality. The central difficulty that randomization seeks to address is selection bias. When program participants are not randomly selected, their outcomes may differ systematically from those of non-participants. This makes it difficult to attribute any differences observed between participants and non-participants to the program itself. For example, schools that receive better inputs also may differ systematically from the other schools in other ways, for example in pedagogy and teacher incentives. However, when the program is randomly assigned, these initial differences even out and selection bias disappears. Experiments allow researchers to vary one factor at a time by randomly assigning the program to part of the sample, and therefore they yield internally valid estimates of program effects.

Thus, in the mid-1990s, development economists started doing experiments to answer basic questions about the education production function: Does better access to inputs (textbooks, teachers) affect school outcomes (attendance, test scores)--and if so, by how much? The motivating theoretical framework was very simple, but the results were surprising. For example: Glewwe, Kremer, and Moulin (4) found...

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