What Is It About Communicating With Parents?

Last registered on November 26, 2020

Pre-Trial

Trial Information

General Information

Title
What Is It About Communicating With Parents?
RCT ID
AEARCTR-0001379
Initial registration date
June 26, 2016

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 26, 2016, 3:40 PM EDT

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

Last updated
November 26, 2020, 4:52 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
University of Zurich

Other Primary Investigator(s)

PI Affiliation
Stanford University
PI Affiliation
Stanford University
PI Affiliation
University of São Paulo

Additional Trial Information

Status
Completed
Start date
2016-06-13
End date
2017-01-27
Secondary IDs
Abstract
While there is increasing evidence that enhancing the communication between schools and parents significantly improves students’ performance, less is known about what mechanisms drive those effects. Is it because, by providing parents with information about their children’s effort, communication primarily alleviates the moral hazard problem between parents and children (Burztyn and Coff, 2008)? Or is it because parents have limited attention, and communication makes parenting “top of mind”? This paper attempts to decompose the effects of communicating with parents into those two mechanisms. Specifically, we investigate whether informing parents about their children’s attendance, lateness and assignment completion, improves students’ outcomes above and beyond the effects of communication aimed at increasing awareness about those dimensions of children’s effort. The distinction matters: providing timely and accurate information about children’s behavior requires integrated systems and customized communication, which can be quite costly, particularly in developing countries. Conversely, simply nudging to raise awareness does not require any information systems in place.
External Link(s)

Registration Citation

Citation
Bettinger, Eric et al. 2020. "What Is It About Communicating With Parents?." AEA RCT Registry. November 26. https://doi.org/10.1257/rct.1379-1.1
Former Citation
Bettinger, Eric et al. 2020. "What Is It About Communicating With Parents?." AEA RCT Registry. November 26. https://www.socialscienceregistry.org/trials/1379/history/80536
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Experimental Details

Interventions

Intervention(s)
Our experiment has Math teachers fill in information about students’ attendance, lateness and assignment completion, and then randomly assigns within classroom what information is conveyed to each parent over SMS. Parents in the control group receive no SMS; those in the awareness treatment group receive only general statements about the relevance of monitoring their child’s behavior (e.g.: “Attending classes every day is important for Nina’s grades”); and those in the awareness + information treatment group receive what the teacher informed about their child (e.g.: “Nina was absent less than 3 times in the previous 3 weeks”). The questions of interest are whether awareness alone improves student’s attendance, grades, and drop-out rates, and to what extent adding pupil-level information further improves those outcomes.
Intervention Start Date
2016-07-04
Intervention End Date
2016-12-02

Primary Outcomes

Primary Outcomes (end points)
We will conduct surveys through automated voice calls (Interactive Voice Response, IVR) at the end of the intervention to collect self-reported parenting practices and parents’ views about their children. We conducted a baseline survey through IVR on the week of June 16th, surveying parents about their demand for information, as well their previous knowledge about their kids (Annex 2). At the end of the project, we will be able to investigate if treatment effects are heterogeneous by the accuracy of prior knowledge about children’s behavior and the ones by ex-ante demand for information about child-level behavior.

At the end of the intervention, the São Paulo Education Secretariat will provide data on student attendance and grades in 2016 (per quarter), and enrollment in 2017. Moreover, the Secretariat implements an yearly standardized test to all schools in the state of São Paulo, SARESP (System of School Performance Evaluation of the State of São Paulo). All students in grades 1st, 3rd, 5th, 7th, 9th of primary school and the 3rd (final) year of high school are tested on their knowledge of Mathematics and Portuguese.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The intervention’s treatment arms are as follows:
1) [Awareness treatment] General statements about attendance, lateness and assignment completion (e.g. “attending school is important”) – T1
2) [Awareness + information treatment] Child-level attendance, lateness and assignment completion – T2
3) [Awareness + relative information treatment] Child- and classroom-level attendance, lateness and assignment completion – T3

First, schools will be randomly assigned to 4 different subsamples (A-D), determining the treatment arms each school will have access. Then, students will be randomized within class to each treatment arm:
A. Pure control – ~25 schools
B. T1 + control – ~25 schools
C. T1 + T2 + control – ~100 schools
D. T1 + T2 + T3 + control – ~50 schools
Experimental Design Details
The intervention’s treatment arms are as follows:
1) [Awareness treatment] General statements about attendance, lateness and assignment completion (e.g. “attending school is important”) – T1
2) [Awareness + information treatment] Child-level attendance, lateness and assignment completion – T2
Comparing T2 to T1 and T1 to control allows separating the effects of information and awareness.
There are two main concerns about how this design may potentially underplay the effects of information. The first is that parents may already have (to a reasonable extent) information about their child, such that the key piece of information missing is how to place their child relatively to his or her classmates. In fact, other studies often focus on relative behavior: e.g. Rogers and Feller (2016) inform parents about how their children’s attendance fares relatively to his/her classroom modal attendance.
To deal with this concern, we pursue two strategies. First, we survey parents at baseline about their best guess for their child’s attendance, lateness and assignment completion, so as to investigate heterogeneity of treatment effects by baseline accuracy (Annex 2). Second, for a subsample of schools, we add an alternative awareness + information treatment that conveys parents both with pupil- and classroom-level information, to test whether that treatment has additional effects.
3) [Awareness + relative information treatment] Child- and classroom-level attendance, lateness and assignment completion – T3
The second concern is contamination, or peer effects. While there is a concern that assigning different treatments within the same classroom may lead to contamination, we are less worried about it in this setting parents typically have no recurring interactions at this age – most of them no longer take their children to school, and parent-teacher meetings are rather infrequent in Brazilian public schools. However, peer effects may lead us to underestimate treatment effects.

To deal with this concern, our design varies the exposure to the different treatments across different subsamples of schools, allowing us to estimate spillovers. Randomization will be performed in two steps. First, schools will be randomly assigned to 4 different subsamples (A-D), determining the treatment arms each school will have access. Then, students will be randomized within class to each treatment arm:
A. Pure control – 25 schools
B. T1 + control – 25 schools
C. T1 + T2 + control – 100 schools
D. T1 + T2 + T3 + control – 50 schools
Subsample C allows separating the effects of information and awareness; subsamples A and B allow estimating spillover effects. Subsample D is meant to address the concern about relative vs. absolute child-level information.
In order to collect cellphones and information from parents in the control group, and also to control for the proportion of parents registered in the program, we will offer the control and the treatment group access to send school events through the platform.
Randomization Method
Randomization done in office by a computer
Randomization Unit
First, schools will be randomized to a group (A, B, C or D). Then, students will be randomized within class to each treatment arm (T1, T2 or T3), or to the control group, depending on which group their school was assigned to. Randomization takes place within classrooms in each school.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
223 school
Sample size: planned number of observations
~16000
Sample size (or number of clusters) by treatment arms
A. Pure control – ~25 schools
B. T1 + control – ~25 schools
C. T1 + T2 + control – ~100 schools
D. T1 + T2 + T3 + control – ~50 schools

About 72 pupils per school
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
MDEs for Math standardized test scores: - 0.106 for awareness vs. control - 0.106 for awareness vs. information - 0.150 for absolute vs. relative information - 0.143 for spillovers on the control group - 0.159 for spillovers on the awareness treatment MDEs for Portuguese standardized test scores: - 0.105 for awareness vs. control - 0.105 for awareness vs. information - 0.148 for absolute vs. relative information - 0.134 for spillovers on the control group - 0.149 for spillovers on the awareness treatment
Supporting Documents and Materials

Documents

Document Name
Proposal
Document Type
proposal
Document Description
Pre-analysis plan
File
Proposal

MD5: 8f21cd321a6076ff976351a53292f6b2

SHA1: 077f9ebbc422a3b4dc49b36b33be67d6ff3a8ac8

Uploaded At: June 26, 2016

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IRB

Institutional Review Boards (IRBs)

IRB Name
Stanford University IRB
IRB Approval Date
2016-05-10
IRB Approval Number
35332

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials