Effect of targeted messages and informational videos on school data quality in South Africa

Last registered on June 15, 2026
View Trial History

Pre-Trial

Trial Information

General Information

Title
Effect of targeted messages and informational videos on school data quality in South Africa
RCT ID
AEARCTR-0018888
Initial registration date
June 08, 2026

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
June 15, 2026, 4:17 PM EDT

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Bianca L. Böhmer
Affiliation
Stellenbosch University
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2025-08-01
End date
2027-02-28
Keywords
Education
Additional Keywords
Data Quality
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
High-quality administrative education data are essential for monitoring system performance, allocating resources, and informing decision-making. However, the value of these data depends on schools submitting information that is accurate, complete, and timely. Despite significant improvements over time and ongoing investments in education management information systems and data dashboards in South Africa, challenges remain in ensuring consistent and high-quality data submissions across schools.

This study evaluates whether low-cost, scalable communication interventions can improve the frequency, completeness, and quality of administrative data submissions to the South African School Administration and Management System (SA-SAMS). Specifically, the study examines the impact of targeted messages and informational videos delivered to schools participating in the Data Driven Districts (DDD) programme.

The evaluation will be implemented as a randomised controlled trial involving approximately 10,550 schools. By testing interventions that can be deployed at scale with minimal resource requirements, the study aims to generate evidence on practical approaches for strengthening administrative data quality and improving the effectiveness of data-driven decision-making within education systems.
External Link(s)

Registration Citation

Citation
Böhmer, Bianca L.. 2026. "Effect of targeted messages and informational videos on school data quality in South Africa." AEA RCT Registry. June 15. https://doi.org/10.1257/rct.18888-1.0
Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
Experimental Details

Interventions

Intervention(s)
Schools in the treatment group will receive a combination of the following nudges, in addition to existing communication that is already part of the normal Data Driven Districts (DDD) operations.
1. Targeted messaging
Users receive SMS or email messages containing customised:
• Notifications of missing or incorrect data fields
• Reminders to complete submissions.
• Information about their recent data submissions (in comparison to other schools)
Messages are customised based on current data or previous submission patterns.
2. Informational videos
Users receive video(s) explaining:
• Roles and responsibilities in data management
• Data submission procedures (can include links)
• Reminders on the importance of high-quality data.
Intervention Start Date
2026-01-14
Intervention End Date
2026-06-26

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes pertain to the completeness of data entry for Learner National Identifyer (ID) and an estimate of the quality of the Learner attendance and Educator attendance data at the school level.
Primary Outcomes (explanation)
Learner IDs - Percentage of missing learner identifiers within a school [Completeness]
Learner Attendance (Primary Measure A) - Percentage of schools reporting 100% attendance for the term [data quality]
Learner Attendance (Primary B) - Percentage of schools whose attendance rate lies above a selected percentile of the expected distribution (using a beta-binomial model). [Data quality]
Educator Attendance (Primary Measure A) - Percentage of schools reporting 100% attendance for the term [Data quality]
Educator Attendance (Primary B) - Percentage of schools whose attendance rate lies above a selected percentile of the expected distribution (using a beta-binomial model). [Data quality]

Secondary Outcomes

Secondary Outcomes (end points)
The secondary outcomes look at the quality of Learner National Identifyer (ID) and the frequency and speed to submission of Learner and Educator attendance data. Aside from the secondary outcomes on the three main variables, there is a secondary outcomes that will be analysed, namely user engagement with the DDD system.
Secondary Outcomes (explanation)
Learner IDs (Secondary Measure A) - Proportion of duplicate IDs (in different schools), which is an indicator of outdated information in one of the schools. [Data quality]
Learner IDs (Secondary Measure B) - Percentage of invalid or erroneous entries by school [Data quality]
Learner Attendance (Secondary Measure A) - Tracks the frequency of submissions by measuring the number of weekly submissions by a school per term (Number of weeks submitted / total number of weeks). [Frequency/speed of data submission]
Learner Attendance (Secondary Measure B) - Tracks timing of submissions relative to reporting deadlines (end of term). The measure would look at the difference in days between the end of the term and the submission date. [Frequency/speed of data submission]
Educator Attendance (Secondary Measure A) - Tracks the frequency of submissions by measuring the number of weekly submissions by a school per term (Number of weeks submitted / total number of weeks). [Frequency/speed of data submission]
Educator Attendance (Secondary Measure B) - Tracks timing of submissions relative to reporting deadlines (end of term). The measure would look at the difference in days between the end of the term and the submission date. [Frequency/speed of data submission]

User engagement metrics for the DDD dashboard. Three (linked) metrics will be tracked:
- Measure A - At least one user at the school logged in at least once
- Measure B - Number of users at the school accessing the dashboard at least once
- Measure C - Number of log-ins of the most active user at the school

Experimental Design

Experimental Design
The evaluation will be conducted as a randomised controlled trial. Randomisation will take place at the school level. Schools will be randomly assigned to either the treatment or control group:
- The control group will consist of about 5275 school who would receive no additional interventions on top of normal planned district and DDD operations.
- The treatment group will consist of about 5275 schools who will receive targeted data submission messages as well as data quality training videos and guidelines sent to schools in Term 1 and 2 of 2026
Experimental Design Details
Not available
Randomization Method
Randomisation done on a computer
Randomization Unit
Randomisation was performed at the school level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clustering
Sample size: planned number of observations
~10,550 schools
Sample size (or number of clusters) by treatment arms
~5,275 in control and 5,275 in treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Using a single-level trial, with the school as the unit of randomisation. Assuming N = 10550 (C+T), alpha = 0.05, Power = 0.8 and an estimated R^2 of 0.015 based on data from previous years. This produced an MDES of 0.050 standard deviations. In Units of the Primary measures using values from Term 1 in 2025, this is equivalent to: - Missing Learner ID's: ~0.9 ppt or ~15% reduction (about 4.5 IDs per school) - Learner Attendance for schools reporting 100% attendance: ~1.8 ppt or ~11.5% reduction - Educator Attendance for schools reporting 100% attendance: ~1.3 ppt or ~17.6% reduction
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Stellenbosch University Social, Behavioural and Education Research Ethics Committee (REC: SBE)
IRB Approval Date
2025-10-27
IRB Approval Number
33259
Analysis Plan

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information