|
Field
Abstract
|
Before
This study examines whether weather-induced travel costs to school could be reduced through a low-cost adaptation tool. I am implementing a cluster-randomized controlled trial with around 2,000 students across 106 secondary schools. Schools are randomly assigned to the treatment or control group. In treatment schools, students receive a foldable umbrella plus a one-off information nudge designed to encourage regular use and reduce reallocation within households. The primary outcome is absenteeism on adverse-weather school days, constructed from school attendance registers and linked to daily rainfall and temperature data. Baseline and endline student surveys provide complementary outcomes on learning and wellbeing. The study provides evidence on a low-cost, scalable approach to mitigating weather-related disruptions to schooling.
|
After
The study examines whether a low-cost adaptation to recurrent weather events, specifically rain and radiant heat, can reduce student absenteeism. I implement a cluster-randomized controlled trial with around 2,000 students across 105 secondary schools. Schools are randomly assigned to the treatment or control group. In treatment schools, students receive a foldable umbrella plus a one-off information nudge designed to encourage regular use and reduce reallocation within households. The primary outcome is absenteeism on rainy instructional school days, constructed from school attendance registers and linked to daily rainfall data. Baseline and endline student surveys provide complementary outcomes on learning and wellbeing. The study provides evidence on a low-cost, scalable approach to mitigating weather-related disruptions to schooling.
|
|
Field
Last Published
|
Before
June 15, 2026 01:57 PM
|
After
June 22, 2026 05:53 AM
|
|
Field
Primary Outcomes (End Points)
|
Before
Absenteeism rate on adverse-weather school days.
|
After
Absenteeism rate on rainy instructional school days.
|
|
Field
Primary Outcomes (Explanation)
|
Before
The adverse-weather absenteeism rate is defined for each student as the number of adverse school days absent divided by the total number of adverse-weather school days.
|
After
The absenteeism rate is defined for each student as the number of rainy instructional school days absent divided by the total number of rainy instructional school days between the baseline and endline surveys.
|
|
Field
Experimental Design (Public)
|
Before
School Selection
The study is a cluster-randomized controlled trial with randomization at the school level. A list of all registered schools was obtained from the District Education Office in Pabna. The list contains 325 secondary schools, of which 241 are located within the five study subdistricts.
Schools were considered ineligible if they met any of the following criteria:
1. The school was designated as a center for the Secondary School Certificate (SSC) public examination.
2. The school was single-sex (i.e., not co-educational);
3. The school had fewer than 200 enrolled students in total, or
4. The school was not a standard secondary school (i.e., it was a junior secondary school serving up to grade 8 or a higher secondary school serving up to grade 12).
After applying these eligibility criteria, 134 schools remained eligible for participation. From this pool, 106 schools were randomly selected and subsequently assigned to either the treatment or control group. Randomization was conducted prior to baseline data collection.
Student Selection
Within each study school, the target population is Grade 8 students. Student eligibility was determined through a short screening survey administered to all, or nearly all, Grade 8 students present on the survey day. Students were eligible for inclusion if they met both of the following criteria:
1. The student walked to school or used a rickshaw van as the primary commuting mode; and
2. The student lived in a household with no more than one usable umbrella.
In treatment schools, I aimed to enroll approximately 30 eligible students per school. If more than 30 students were eligible in a treatment school, up to 30 students were randomly selected from the eligible list through an on-the-spot lottery. This cap was imposed because the number of umbrellas available for distribution was limited. In control schools, all eligible students were included in the study sample.
Data Collection
Baseline survey
To assess eligibility, I conducted a short paper survey consisting of three questions. The eligible students completed a structured survey in a classroom setting on a tablet computer. They also attended a standardized cognitive test covering English, mathematics, and general aptitude. In parallel, I administered a short school questionnaire to the headteachers to capture key school characteristics. I extracted the attendance data up to the survey date (Jan- April 2026) from the school records.
Endline survey
At the endline, I will re-survey students and headteachers. Students will complete a cognitive assessment comparable in structure and difficulty to the baseline test. There will also be a survey module on relevant behaviors and experiences over the study period.
During-intervention data
During the intervention period, I will collect implementation and monitoring data to assess treatment intensity and compliance. First, I will conduct unannounced school visits in both treatment and control schools to measure (i) student attendance on the day of the visit and (ii) umbrella use. I plan four visits per school: two during the monsoon and two during the hot season. Second, I will compile high-frequency attendance outcomes by digitizing school register data. Third, I will compile high-frequency weather data for the study area, including daily rainfall (mm) and daily temperature (°C). I will align these measures to the finest feasible geographic and temporal resolutions.
|
After
School Selection
The study is a cluster-randomized controlled trial with randomization at the school level. A list of all registered schools was obtained from the District Education Office in Pabna. The list contains 325 secondary schools, of which 241 are located within the five study subdistricts.
Schools were considered ineligible if they met any of the following criteria:
1. The school was designated as a center for the Secondary School Certificate (SSC) public examination.
2. The school was single-sex (i.e., not co-educational);
3. The school had fewer than 200 enrolled students in total, or
4. The school was not a standard secondary school (i.e., it was a junior secondary school serving up to grade 8 or a higher secondary school serving up to grade 12).
From the eligible schools, 106 were randomly selected and subsequently assigned to either the treatment or control group. Randomization was conducted prior to baseline data collection.
Student Selection
Within each study school, the target population is Grade 8 students. Student eligibility was determined through a short screening survey administered to all, or nearly all, Grade 8 students present on the survey day. Students were eligible for inclusion if they met both of the following criteria:
1. The student walked to school or used a rickshaw van as the primary commuting mode; and
2. The student lived in a household with no more than one usable umbrella.
In treatment schools, I aimed to enroll approximately 30 eligible students per school. If more than 30 students were eligible in a treatment school, up to 30 students were randomly selected from the eligible list through an on-the-spot lottery. This cap was imposed because the number of umbrellas available for distribution was limited.
Data Collection
Baseline survey
To assess eligibility, I conducted a short paper survey consisting of three questions. The eligible students completed a structured survey in a classroom setting on a tablet computer. They also attended a standardized cognitive test covering English, mathematics, and general aptitude. In parallel, I administered a short school questionnaire to the headteachers to capture key school characteristics. I extracted the attendance data up to the survey date (Jan- April 2026) from the school records.
Endline survey
At the endline, I will re-survey students and headteachers. Students will complete a cognitive assessment comparable in structure and difficulty to the baseline test. There will also be a survey module on relevant behaviors and experiences over the study period.
During-intervention data
During the intervention period, I will collect implementation and monitoring data to assess treatment intensity and compliance. First, I will conduct unannounced school visits in both treatment and control schools to measure (i) student attendance on the day of the visit and (ii) umbrella use. I plan four visits per school: two during rainy days and two during high-radiant-heat days. Second, I will compile high-frequency attendance outcomes by digitizing school register data. Third, I will compile high-frequency weather data for the study area, including daily rainfall, daily temperature, and solar radiation. I will align these measures to the finest feasible geographic and temporal resolutions.
|
|
Field
Planned Number of Observations
|
Before
2000
|
After
~2047 students
|
|
Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes
|
Before
MDE of 0.15–0.20 SD in absenteeism during adverse-weather days
|
After
MDE of 0.2–0.25 SD in absenteeism on rainy instructional school days
|
|
Field
Secondary Outcomes (End Points)
|
Before
Seasonal sickness (self-reported)
Standardized test scores
Girls' mobility
|
After
Absenteeism on high-radiant-heat days
Seasonal sickness (self-reported)
Standardized test scores
|