Learning without Teachers? Using Mobile Phones to Promote Adult Education in Niger

Last registered on December 09, 2024

Pre-Trial

Trial Information

General Information

Title
Learning without Teachers? Using Mobile Phones to Promote Adult Education in Niger
RCT ID
AEARCTR-0014974
Initial registration date
December 05, 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
December 09, 2024, 4:53 PM EST

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

Locations

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Primary Investigator

Affiliation
Tufts University

Other Primary Investigator(s)

PI Affiliation
Dartmouth College

Additional Trial Information

Status
In development
Start date
2024-12-14
End date
2026-12-14
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Almost 1 billion adults worldwide are unable read or write in any language, with an estimated cost of US$ 5 billion annually to low-income countries (UNESCO 2020). This is of particular concern in West Africa, which has some of the lowest education indicators in the world. In Niger, the subject of our study, adult illiteracy rates are estimated at 70% (USAID 2023). Illiteracy is particularly striking in rural areas and among women. Niger’s ranking in terms of educational attainment is comparable to other Sahelian countries, namely Burkina Faso, Chad and Mali (UNDP 2017).

While policymakers and academics alike have focused on primary and secondary education programs, such programs will only have impacts in the medium to long-term. Adult education programs have the potential to bridge these gaps and yield more immediate returns, but are often “characterized by low attendance, high drop-out, limited skills attainment and rapid skills depreciation (Aker et al 2024). This is potentially due to high opportunity costs for adults, the irrelevancy of such skills in daily life, poorly-adapted pedagogical approaches and teacher absenteeism.

The growth of information technology has offered new opportunities to address some of these constraints, either by providing learners with greater flexibility during the learning process (Ksoll et al 2023, Angrist et al 2022), allowing students to practice outside of class or affecting the returns to education (Aker et al 2012).

Our solution is a mobile phone-based adult literacy program. It will build upon platform originally developed for native Spanish-speakers in the US (Cell-Ed). The platform uses voice, audio and SMS to deliver literacy lessons (micro-modules). Each micro-module has three components: 1) a short audio lesson on a particular concept (letters, syllables, words); 2) a SMS reinforcing the voice lesson; and 3) a SMS-based interactive quiz on the lesson. To activate the program, participants send a SMS to a pre-arranged phone number. Students can access the program 24 hours a day, 7 days a week, allowing them to learn when, where and how they wish.

This research will test the impact of this innovation in Niger, targeting low-literate adult men and women in the Dosso region. We will test the platform in Hausa, one of the primary indigenous languages in Niger. Across 100 villages, we will stratify by geographic area and randomly assign villages to have access to the platform (which involves training on how to use it, and access to a facilitator) or none. We will also cross-randomize a subsidy, provided via mobile phone credit, to determine if and how liquidity constraints affect access.

External Link(s)

Registration Citation

Citation
Aker, Jenny and Mahounan Yedomiffi. 2024. "Learning without Teachers? Using Mobile Phones to Promote Adult Education in Niger." AEA RCT Registry. December 09. https://doi.org/10.1257/rct.14974-1.0
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Experimental Details

Interventions

Intervention(s)
The primary treatment is the introduction of the mobile phone-based Hausa literacy platform. Within treatment villages, the platform will be introduced, and targeted participants will be trained in how to use the system. In addition, two literate facilitators will be identified and trained. The facilitators will answer questions about the platform and resolve issues for learners. We will also provide a subsidy (in the form of airtime credit) in treatment and control villages, which will be cross-randomized.

Prior to the program, we will collect data on baseline literacy rates, willingness to pay for the platform, income and children’s schooling. Administrative data on usage will be monitored. We will conduct literacy tests six months after the introduction of the platform and a household survey one year later.

The approach is designed to assess participants’ demand for the system; the key barriers to usage, including liquidity and technology; the optimal periods for learning; and the impact on adults’ learning, as well as other welfare measures.
Intervention Start Date
2025-01-04
Intervention End Date
2025-12-04

Primary Outcomes

Primary Outcomes (end points)
Adopt and usage of the platform, per day/month
Amount of spending on the platform
Reading levels (based upon an in-person reading test)
Mobile phone knowledge and usage
Attitudes towards education
Children's enrollment and attendance in school
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will use a village-level cluster RCT, stratifying by sub-region and randomly assigning 100 villages to treatment or control. After stratifying by treatment status, villages will be randomly assigned to three different subsidy levels, in the form of airtime credit.

Within all villages, we will first identify eligible participants, defined as those who are illiterate. Amongst eligible participants, we will stratify by gender and randomly select 12 men and 12 women per village, which conforms with Ministry norms. We will also have a spillover sample of 6 participants per village.
Experimental Design Details
Not available
Randomization Method
This is a stratified, cluster-level RCT with randomized done in the office and by a computer.
Randomization Unit
The key unit of randomization is the village level.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
The proposed sample size if 100 villages, with 24 students per village.
Sample size: planned number of observations
We will choose 24 students per village, plus 6 spillover students, for a total of 30 students per village and 3,000 students. However, as we will not have the financing to collect data from all 30 students, we will aim to collect data from 16 students per village, for a sample of 1600 students.
Sample size (or number of clusters) by treatment arms
We will have 50 treatment villages and 50 control villages
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Tufts University
IRB Approval Date
2024-11-02
IRB Approval Number
N/A