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Street smart or school smart? Leveraging working children’s competencies to teach them mathematics
Initial registration date
March 02, 2017
May 21, 2020 10:09 AM EDT
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Other Primary Investigator(s)
Abdul Latif Jameel Poverty Action Lab (J-PAL) South Asia
Massachusetts Institute of Technology (MIT)
Additional Trial Information
According to large-scale surveys, most children and adolescents in India perform poorly in “abstract” arithmetic (i.e., the arithmetic operations typically taught in school). Yet, those employed in informal markets seem to perform relatively complex arithmetic operations mentally when handling transactions (e.g., to calculate amounts due or change). Is it possible to leverage the skills that these children already have to help them succeed in abstract arithmetic? We will conduct a study to address this question, by surveying children and adolescents selling in markets in and around Delhi in order to understand why they might succeed at “market” arithmetic, but struggle with abstract arithmetic.
Banerjee, Abhijit et al. 2020. "Street smart or school smart? Leveraging working children’s competencies to teach them mathematics." AEA RCT Registry. May 21.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
1. Child performance on market v. abstract arithmetic
We will describe the performance of children in the market transactions and abstract arithmetic operations. We will also compare the performance of these children to that of the average child in their states (drawing on the 2016 ASER report and urban ward surveys).
2. Factors associated with performance
We will explore whether we observe any heterogeneous effects in children’s performance in the market transactions and abstract arithmetic according to their demographic, education, and employment characteristics. Then, we will try to predict which children succeeded at the transactions but failed at the same arithmetic operations using the items in the three math exercises in the survey. 3. Causal effect of performance incentives
We also plan to explore whether there is a suggestive relationship between incentives and performance. We will try to estimate the causal effect of performance incentives on children’s ability to perform abstract arithmetic operations. 4. Benchmark against comparison samples
We will compare the performance of children and adults in the same survey. Then, we will compare the performance of children in the markets and those attending neighboring schools. These analyses will allow us to place the performance of the children in markets in context.
Primary Outcomes (explanation)
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
We will recruit around 350 to 400 children working in markets in Delhi to administer a two-part survey.
The first part, in which each child will be approached by a “mystery shopper” (a surveyor dressed like a regular shopper), aims to verify that these children can calculate the amount due and change for transactions that are normally made in these markets.
The second part of the survey, wherein the mystery shopper will administer informed consent, aims to assess whether these children can perform abstract arithmetic calculations and to test for potential explanations why this might not be the case. This part of the survey will include: i. ASER test which aims to assess the child’s ability to perform abstract arithmetic operations (e.g., divisions with remainders and subtractions with carry-overs);
ii. Orally-administered questions of school-type mathematics as well as market-type mathematics, in order to determine whether children struggle with abstract math because they are unfamiliar with the notation or cannot think in abstract terms; and
iii. Market-contextual questions, in order to determine whether children’s familiarity with the goods, prices, and transactions at their shops help them use arithmetic in the market, but not in other situations.
It is also possible that children perform better in the first than in the second part of the survey because they have a clear incentive to get the market transactions correctly. Thus, we will randomly assign children to non-incentivized and incentivized versions of the second part of the survey. In the incentivized version, children will be offered a reward proportional to the number of correct answers in the second part of the survey.
Finally, we are also interested in placing the abilities of these children in context. Thus, we plan to draw two comparison samples. First, we will administer a version of the survey to 200 adults working in the same markets, following the same sampling protocol described above. Second, in Delhi, we will identify public schools in the districts where the markets are located and administer a version of the survey to 200 children attending these schools.
Experimental Design Details
Randomization of performance incentives is done in office by a computer
Randomization of incentives is done at the individual level, i.e., at the level of the child.
Was the treatment clustered?
Sample size: planned number of clusters
Sample size: planned number of observations
This study presents several important challenges related to the sampling of markets and children, specifically because: (i) there is no comprehensive list of markets that employ children - partly, because child labor is illegal in India; (ii) there is no roster of children working at each market and the number and composition of children changes across times of the day and days of the week; and (iii) not all children at the markets are involved in selling, since some are accompanying their relatives or helping with other tasks. In light of these challenges, we cannot accurately predict the number, age and gender composition of children who will participate in this study. Yet, based on our initial visits, we estimate that we will recruit approximately:
― 350 to 400 children working in markets
― 200 adults working in markets
― 200 children attending neighboring schools
Sample size (or number of clusters) by treatment arms
Approximately 200 market children will participate in an incentivized version of the survey, and approximately 200 market children will participate in a non-incentivized version of the survey.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
If we succeed in recruiting 400 children and assign incentives at the individual level, we will have 80% power to detect an effect of .28 standard deviations with a 5% alpha level.
INSTITUTIONAL REVIEW BOARDS (IRBs)
Massachusetts Institute of Technology Committee on the Use of Humans as Experimental Subjects
IRB Approval Date
IRB Approval Number