Technology to Empower Actors Across the Learning Ecosystem

Last registered on October 25, 2022

View Trial History

Pre-Trial

Trial Information

General Information

Title

Technology to Empower Actors Across the Learning Ecosystem

RCT ID

AEARCTR-0009905

Initial registration date

October 25, 2022

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

October 25, 2022, 2:54 PM EDT

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

Locations

Country

Pakistan

Region

Islamabad Capital Territory

Primary Investigator

Name

Isabel Macdonald

Affiliation

UC Berkeley

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Christina Brown

PI Affiliation

University of Chicago

Contact Investigator

PI Name

Tahir Andrabi

PI Affiliation

Pomona College

Contact Investigator

PI Name

Asim Khwaja

PI Affiliation

Harvard Kennedy School

Contact Investigator

Additional Trial Information

Status

In development

Start date

2022-09-01

End date

2023-02-28

Keywords

Education

Additional Keywords

education technology

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Education systems around the world face a “learning crisis” of low average learning and high learning inequality. The COVID-19 pandemic has exacerbated these problems, and threatens lasting consequences for a generation of students. In this project, we conduct a randomized control trial in around 500 public primary schools in the Islamabad Capital Territory in Pakistan to explore how low cost technology can empower home-based and school-based actors to boost student learning in foundational math. We use phone-based technology (a novel smartphone app, messaging, and automated call services) to alleviate constraints relating to information about children's learning and potential learning activities, guidance about how to connect learning activities to a given learning level, and teacher monitoring structures that may inhibit learning. We explore whether alleviating these constraints can empower actors at school and at home to provide children with more personalized learning and overall improved learning outcomes.

External Link(s)

Registration Citation

Citation

Andrabi, Tahir et al. 2022. "Technology to Empower Actors Across the Learning Ecosystem." AEA RCT Registry. October 25. https://doi.org/10.1257/rct.9905-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We evaluate how using phone-based technology to alleviate constraints relating to information, guidance, and teacher monitoring structures can empower school-based and home-based actors to personalize learning and improve learning outcomes.

Intervention Start Date

2022-11-07

Intervention End Date

2023-01-31

Primary Outcomes

Primary Outcomes (end points)

Student learning outcomes in math

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Student learning outcomes in English and Urdu, classroom behavior, parent behavior (tutoring, checking workbooks, communicating with school), take up of the tech tool and messages

Secondary Outcomes (explanation)

Experimental Design

We randomly assign school and home based actors to receive nothing (control), information, guidance, and/or an altered teacher monitoring regime to emphasize student learning.

Experimental Design Details

We randomly assign classrooms at formal and non-formal schools in grades 2-4 at treatment schools to one of the following treatments:

1. Control - participants conduct “business as usual”, where teachers use the normal math textbook and parents likely do not receive any communication from the school about student learning. Half the sample will receive the workbook (described below) only.

2. Information – teachers and parents will receive:
a. test score information about student performance in foundational math, delivered via a smartphone app for teachers and a series of automated phone calls and messages for parents
b. a set of math learning activities in the form of a workbook and (for teachers) an accompanying lecture guide
In this group, actors decide how to respond to each child’s learning results with activities from the workbook, lecture guide, and/or standard textbook. Teachers can deliver this content during ther regular math period and/or assign it as homework

3. Guidance – participants will receive everything in the information treatment as well as specific instructions on which learning activities from the workbook to complete with each child. For teachers, this includes instructions for which lectures to deliver to the class overall and workbook pages to assign to different groups of learners as classwork and homework. For parents, this includes specific workbook pages to review and instructions to share information with whoever helps the child with homework if not the parent (tutor, sibling, etc.)

Classrooms receive a separate school and home-based assignment to one of these three groups, leading to 9 potential treatment combinations.

In addition, we cross-randomize each formal school in our sample (note: not classroom!) into one of two teacher monitoring regimes:
Control monitoring - status quo monitoring system where principals regularly check each teachers’ syllabus completion
Learning level monitoring - principals are instructed not to check which lessons teachers complete, but rather review student learning results via the same smartphone app used by teachers and discuss progress with teachers

Randomization Method

Randomization done in office by a computer

Randomization Unit

Information/guidance: classroom
Monitoring: school

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

1,242 classrooms
584 schools (336 formal, 248 informal)

Sample size: planned number of observations

37,260 students (30/classroom)

Sample size (or number of clusters) by treatment arms

Information/guidance: 138 classrooms per school/home treatment combination
Monitoring: 168 schools per monitoring treatment (note: monitoring treatments only assigned in the 336 formal schools)

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB