Identifying and Nurturing Math Talent at Scale: An Experiment with Art of Problem Solving Self-Paced Classes in Tamil Nadu, India

Last registered on August 06, 2024
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Pre-Trial

Trial Information

General Information

Title
Identifying and Nurturing Math Talent at Scale: An Experiment with Art of Problem Solving Self-Paced Classes in Tamil Nadu, India
RCT ID
AEARCTR-0014090
Initial registration date
July 30, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 06, 2024, 1:19 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name
Paolo Adajar
Affiliation
MIT
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Other Primary Investigator(s)

PI Name
Esther Duflo
PI Affiliation
MIT
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PI Name
Glenn Ellison
PI Affiliation
MIT
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PI Name
Sara Ellison
PI Affiliation
MIT
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PI Name
Harini Kannan
PI Affiliation
J-PAL
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Additional Trial Information

Status
In development
Start date
2024-08-12
End date
2030-06-01
Keywords
Education
Additional Keywords
JEL code(s)
D61, I24, I25, J24, O30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this project, partnering with the Art of Problem Solving (AoPS) and the Government of Tamil Nadu, we will test whether advanced online coursework and tutoring can identify and support high achievers who lack access to resources. Using administrative data and a screening mechanism, we will provide direct evidence of the distribution of high-potential students in Tamil Nadu. In an RCT with high-achieving students, we will test the effects of offering an advanced pre-algebra class and the additive benefits of support systems, such as tutoring. We aim to provide a model that can be extended to other Indian states or other countries if it proves successful.
External Link(s)

Registration Citation

Citation
Adajar, Paolo et al. 2024. "Identifying and Nurturing Math Talent at Scale: An Experiment with Art of Problem Solving Self-Paced Classes in Tamil Nadu, India ." AEA RCT Registry. August 06. https://doi.org/10.1257/rct.14090-1.0
Sponsors & Partners

Sponsors

Partner

Name
Art of Problem Solving
Type
private_company
URL
https://artofproblemsolving.com/
Experimental Details

Interventions

Intervention(s)
Students will receive one of four interventions.
a) Access to AoPS Pre-Algebra 1 course for six months, with various technological support
b) Identical access as in (a), and weekly group tutoring sessions
c) Identical access as in (b), and weekly 1:1 tutoring sessions
d) Control group used as a baseline for comparison.
Intervention Start Date
2024-10-01
Intervention End Date
2025-07-01

Primary Outcomes

Primary Outcomes (end points)
1. Retention, grades, and engagement in AoPS class (only for the treatment groups)
2. Test scores on regular TN examinations (administrative data)
3. Test scores on a customized test created to measure skills in the standard math curriculum, the AoPS curriculum, and general mathematical reasoning, with a higher ceiling than standardized tests, administered at the end of the RCT.
4. Performance at the grade 10 board examinations (a high-stakes exam administered to all children in Tamil Nadu).
5. Admission into Tamil Nadu elite high schools for grades 11 and 12. For this to be a reliable outcome, we may encourage our entire sample to apply and take the entrance exams.
6. Later-life outcomes, such as high school graduation, college matriculation, college selectiveness, and choice of a STEM major/career.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1. Qualitative evidence on students’ interest in STEM, belief in math abilities, future plans, and other behavioral outcomes, collected at the end of 10th and 12th grade.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Students will be selected for this intervention using a combination of test scores on government-administered public school examinations and a screening mechanism in which high-performing students will receive access to a sample of AoPS material.

After identifying students, they will be randomized to one of the four interventions described above.
Experimental Design Details
Not available
Randomization Method
Randomization performed in Stata with a saved seed.
Randomization Unit
Clustered at school level.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
1100 schools
Sample size: planned number of observations
2400 students
Sample size (or number of clusters) by treatment arms
800 students in control, 800 with AoPS only, 600 with group tutoring, 200 with 1:1 tutoring
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
0.3 standard deviations on outcomes with mean 0 and standard deviation 1
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
MIT
IRB Approval Date
2024-09-01
IRB Approval Number
N/A
Analysis Plan