Field
Abstract

Before
This project investigates how the adoption of a peerlearning pedagogy by teachers affects (i) the number and diversity of interactions between students of a class, (ii) the composition of students friendship network over time, (iii) students communication with their class peers, (iv) students cooperation with their peers. We estimate the effect of peer learning using a Randomized Control Trial. We randomly assign students to a peerlearning platform and we measure the evolution of students’ friendship networks, communication, and cooperation on a monthly basis over a sixmonths period.

After
This project investigates how the adoption of a peer learning platform by teachers affects (i) the number and diversity of workrelated interactions between students of a class, (ii) the density and diversity of students’ friendship networks, (iii) students’ cooperation with their peers and students’ prosocial behaviors, (iv) students’ wellbeing measured by their level of selfesteem, school satisfaction, frequency of positive and negative emotions, and prevalence of bullying. We estimate the effect of peer learning using a Randomized Control Trial. We randomly assign volunteer teachers at the school level to three treatment arms: (i) no access to the peer learning platform, (ii) access to the peer learning platform, (iii) access to the peer learning platform with information and encouragements to use peer learning outside of the platform and during daily lessons.

Field
Trial Start Date

Before
January 31, 2022

After
November 14, 2023

Field
Trial End Date

Before
June 30, 2025

After
July 15, 2027

Field
Last Published

Before
February 01, 2022 01:08 PM

After
November 14, 2023 01:05 PM

Field
Intervention (Public)

Before
We evaluate the effect of the introduction of a new pedagogical online platform to teach students digital sciences (“sciences numériques” in French). Note that the introduction of digital science to the elementary school curriculum is a part of national education reform. Thus, control classes will also have a similar curriculum of the same duration (2 hours per week), with the difference that they will not use the peerlearning platform. The platform contains two core features:
1. The “peer help” component encourages students to ask for help whenever they do not understand one of the activities and to help their peers when they need help. When a student needs help, he clicks on a button labeled “J’ai besoin d’aide” (“I need help” in English). This sends a help request to all the peers in the class who can volunteer to help. Note that the help requests are always anonymous. When a student volunteers to help, he physically joins the student who needs help at his desk.
2. The “peer evaluation” component implies that students evaluate each other’s work, without any intervention from teachers. In practice, when a student has finished a task on his computer, he indicates that he needs to be evaluated and the platform randomly assigns a corrector who will physically join the student at his desk to review the task with him/her.
3. Finally, the “cooperative learning” component means that students learn through a combination of individual and collaborative projects. Collaborative projects involve inperson interactions between students who seat next to each other in front of a computer to perform a task.
Students use the new platform for 2 hours each week, which corresponds to about 50 hours of exposure to the peerlearning pedagogy over the academic year. Peer evaluations and cooperative learning not only increase the number of interactions that students have with their peers, but they also affect which students they are interacting with. The random assignment of helpers, graders, and group projects partners encourages interactions students tend to naturally shy away from, such as interactions between boys and girls and between students from different social backgrounds.

After
We evaluate the effects of the adoption of a peer learning platform by teachers. This online platform helps students learn the bases of computer sciences, using two key pillars to foster interactions: (i) inperson peer helpevery time students need help, they ask their classmates rather than their teacher, and (ii) inperson peer evaluationsevery time students finish a task, they ask their classmates to evaluate them rather than their teacher.
The ministry recommends that teachers use the platform with their students 45 minutes per week.
The assignment of helpers and graders aims at enhancing the diversity of interactions within each classroom. When a student requests help or an evaluation, all other students see a popup image indicating that someone is seeking assistance or an assessment. However, they do not see who made the request. In addition, to ensure that students who rarely interact with others get an opportunity to do so via the peer learning platform, those who have frequently helped or graded their peers will experience a slight delay before seeing the popup. The first student to respond to a request for help or evaluation will be assigned to be the helper or grader.

Field
Intervention Start Date

Before
January 31, 2022

After
November 14, 2023

Field
Intervention End Date

Before
June 30, 2025

After
July 06, 2024

Field
Primary Outcomes (End Points)

Before
This project investigates how the adoption of a peerlearning pedagogy affects five main outcomes:
(i) the number and diversity of interactions between students of a class
(ii) the composition of students friendship network over time
(iii) students communication with their class peers
(iv) students cooperation with their peers

After
This project investigates how the adoption of a peer learning platform affects four main outcomes:
(i) the number and diversity of workrelated interactions between students of a class;
(ii) the density and diversity of students’ friendship networks;
(iii) students’ cooperation and students’ prosociality;
(iv) students’ wellbeing measured by their level of selfesteem, school satisfaction, frequency of positive and negative emotions, and prevalence of bullying.

Field
Primary Outcomes (Explanation)

Before
Over a period of six months, students in the treated and control groups will take monthly tests to measure the evolution of four main outcomes:
1. The number and diversity of interactions between students of a class. Each month, we ask students to name students they play during class breaks and students they worked with today. We are particularly interested in checking whether peer learning increases interactions between boys and girls, as well as between students from different social and ethnic backgrounds.
2. Network of friends. Each month, we ask students to name their closest friends. Combined with information on gender, social background, and ethnic origin, this information will allow us to document monthly changes in the number of friends for students in the treated and control groups, but also monthly changes in the peers composition over time. We are particularly interested in checking whether peer learning increases friendship between boys and girls, as well as between students from different social and ethnic backgrounds.
3. Communication between students. To measure communication, we have designed a game which we carryout over a threemonth period. We will measure communication using the probability that the students know a fact previously shared with other students from the same class. If that probability is higher in the treated group than in the control group, this shows that peer learning increases communication between students.
4. Cooperation between students. We measure cooperation using a standard cooperation game in experimental economics (the prisoner’s dilemma game). We will investigate whether cooperation increases more over time in the treated group than in the control group.

After

Field
Experimental Design (Public)

Before
We evaluate the effect of peer learning using a Randomized Controlled Trial. The first year of the evaluation (academic year 2021/2022), 65 volunteer classes participate in the evaluation. 33 classes are randomly assigned to the treatment group— these classes benefit from a peerlearning pedagogy from January 2021 onward—while 32 classes are assigned to the control group, who do not have access to the peerlearning technology in 2021/2022 academic year. With 25 students per class and an expected consent rate of about 85%, our final sample will contain about 1,380 students.
The experiment will continue during the academic years 2022/2023 with a larger sample of 300 schools with at least one class per school (at least 6,375 students). We will randomly assign schools to the treatment and control to avoid spillover effects between treated and control classes of a given school.
During the two years of the experiment, classes or schools will be assigned to the treatment or control condition using a stratified random lottery with strata defined on the basis of school location and school status.

After
To study the effects of peer learning on student social networks and their noncognitive skills and wellbeing, we partnered with the French Ministry of Education to evaluate the effect of the adoption of a peer learning platform by teachers of primary school students (4th and 5th grades). The peer learning platform was designed by the “Ecole 42”, a private, nonprofit and tuitionfree IT school in France.
We plan to evaluate the effects of this platform adoption using a Randomized Controlled Trial (RCT) during the academic years 2023/2024. With the help of the French Ministry of Education, we will recruit 300 volunteer primary school teachers in Autumn 2023. 200 teachers will be randomly assigned to the treatment groupthese teachers will be able to use the new peer learning platform from January 2024 onwardwhile 100 teachers will be assigned to the control groupthey will only have access to the new peer learning platform in September 2024. Among treated schools, we will implement two treatment pathways, one in which teachers only use the peer learning platform for 45 minutes per week (100 classes), and another one in which teachers are encouraged to use peer learning outside of the platform and during their daily lessons (100 classes). Teachers will receive information on how to do so.
We will randomize the control status and the two treatment pathways at the school level: all volunteer teachers from the same school will be assigned the same status.
We will measure the causal effects of peer learning by comparing the evolution, over one academic year, of student outcomes in the treated and control groups. We will also explore whether the two treatment pathways have differential effects.
The experiment will continue during the academic years 2022/2023 with a larger sample of 300 schools with at least one class per school (at least 6,375 students). We will randomly assign schools to the treatment and control to avoid spillover effects between treated and control classes of a given school.
During the two years of the experiment, classes or schools will be assigned to the treatment or control condition using a stratified random lottery with strata defined on the basis of school location and school status.

Field
Randomization Unit

Before
Pilot phase (2021/2022): Randomization is done at the class level.
Scaleup phase (2022/2023): Randomization is done at the school level to avoid withinschool betweenclass spillover effects.

After
Schools

Field
Planned Number of Clusters

Before
Pilot phase (2021/2022): 65 clusters, as we will use a stratified randomization at the class level with 65 classes.
Scaleup phase (2022/2023): 300 clusters, as we will use a stratified randomization at the school level with 300 schools.

After
We aim at recruiting 250 schools with an average of 1.2 volunteer teachers per school.

Field
Planned Number of Observations

Before
Pilot phase (2021/2022): With 25 students per class, an expected consent rate of 85% and 65 classes, our final sample will contain about 1380 students.
Scaleup phase (2022/2023): With 25 students per class, an expected consent rate of 85%, 300 schools and at least one class per school, our final sample will contain at least 6,375 students.

After
If we succeed in recruiting 250 schools with an average of 1.2 volunteer teachers per school and an average of 20 participating students per class, our expected sample size will be of about 6,000 students.
Scaleup phase (2022/2023): With 25 students per class, an expected consent rate of 85%, 300 schools and at least one class per school, our final sample will contain at least 6,375 students.

Field
Sample size (or number of clusters) by treatment arms

Before
There is only one treatment arm, so answer is the same as above.

After
We will assign one third of volunteer schools to the control group, one third to the first treatment pathway, and one third to the second treatment pathway. If we succeed in recruiting 250 schools, we will therefore assign about 83 of them to each status.

Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes

Before
For the pilot phase, the minimum detectable effect on the number of classmates that students report as close friends is +0.717 with the following assumptions:
 The randomization is conducted at the class level, with 65 classes and 25 students per and an expected consent rate of 85%.
 Mean number of close friends in control classes: 4.730; standard deviation: 3.184.
 Intraclass correlation: 0.059.
 Power: 0.8; alpha: 0.05.
The minimum detectable effect on the number of coins that students contribute to the common moneybox is +0.051 with the following assumptions:
 The randomization is conducted at the class level, with 65 classes and 25 students per and an expected consent rate of 85%.
 Mean number of coins in control classes: 0.720; standard deviation: 0.269.
 Intraclass correlation: 0.027.
 Power: 0.8; alpha: 0.05.
The minimum detectable effect on the number of rotating facts that students guessed correctly is +0.098 with the following assumptions:
 The randomization is conducted at the class level, with 65 classes and 25 students per and an expected consent rate of 85%.
 Mean number of facts guessed in control classes: 1.794; standard deviation: 0.408.
 Intraclass correlation: 0.073.
 Power: 0.8; alpha: 0.05.
We will compute minimum detectable effects for the scaleup phase of the experiment based on the data collected during the pilot phase.

After
We computed the minimum detectable effects on the main outcomes for which we have data from the pilot phase of the experiment:
Number of classmates with whom students have worked during the previous week: +0.34.
Probability that students have worked with a classmate of the opposite gender: +0.05.
Probability that students have worked with a classmate of the opposite social background: +0.06.
Number of close friends: +0.62.
Probability that students are isolated: +0.02.
Probability that students have a close friend of the opposite gender: +0.05.
Probability that students have a close friend of the opposite social background: +0.03.
Number of coins that students contribute to the common moneybox when playing with random students from different schools: 0.17.
Probability that students exhibit a high level of cooperation when playing with random students from different schools: 0.06.
The minimum detectable effects are computed with a sample size of 250 schools with 24 students per school, and using information from the pilot experiment on the mean, standard deviation and intraclass correlations of the abovementioned outcomes.

Field
Secondary Outcomes (End Points)

Before

After
See the pre analysis plan for the secondary outcomes.
