The 'Good' Schools: The Effects of Student Growth Data on Parental School Preferences

Last registered on March 08, 2021
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Pre-Trial

Trial Information

General Information

Title
The 'Good' Schools: The Effects of Student Growth Data on Parental School Preferences
RCT ID
AEARCTR-0007014
Initial registration date
March 06, 2021

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
March 08, 2021, 10:26 AM EST

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

Locations

Country
United States of America
Region

Primary Investigator

Name
David Houston
Affiliation
George Mason University
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Other Primary Investigator(s)

PI Name
Jeffrey Henig
PI Affiliation
Teachers College, Columbia University
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Additional Trial Information

Status
In development
Start date
2021-03-15
End date
2021-04-05
Keywords
Education
Additional Keywords
JEL code(s)
Secondary IDs
Abstract
When communicating with the public, school systems often rely on measures of academic performance that poorly reflect schools’ contributions to student learning and which correspond closely to school demographics, potentially sustaining or exacerbating existing segregation. We seek to understand if the distribution of different kinds of academic performance information affects parents’ school preferences.

For nearly every public school in the US, the Stanford Education Data Archive (SEDA) provides estimates of average achievement status (student academic performance at one point in time) and average achievement growth (the rate of improvement in student academic performance over time). Average growth is not only a better measure of school effectiveness than average status, it also has a weaker relationship with school demographics. Using a nationally representative sample of 2,800 parents of children age 0-12, we will conduct an online survey experiment in which participants are asked to select their preferred schools from a series of options. All participants will receive demographic information for each school. In addition, some participants will be randomly assigned to receive status and/or growth information for each school. We hypothesize that parents who receive growth information--rather than status information or no academic performance information--will rely more heavily on this indicator and, as a result, prefer less white and less affluent schools.
External Link(s)

Registration Citation

Citation
Henig, Jeffrey and David Houston. 2021. "The 'Good' Schools: The Effects of Student Growth Data on Parental School Preferences." AEA RCT Registry. March 08. https://doi.org/10.1257/rct.7014-1.0
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Experimental Details

Interventions

Intervention(s)
We seek to understand whether distributing information about student growth encourages families to choose schools that serve a less advantaged student body on average, facilitating a decline in the racial/ethnic and economic segregation between schools. We propose an online survey experiment featuring a nationally representative sample of 2,800 parents and caretakers of children age 0-12 provided by the survey research firm YouGov. Participants will be asked to select their preferred school from a set of three options. Every participant will receive demographic information for each school: total enrollment, the racial/ethnic composition of the study body, the percentage of FRPL-eligible students, and the percentage of students with limited English proficiency. Every participant will also receive a randomly assigned value for the distance of each school from their home. In addition, one-quarter of participants will be randomly assigned to receive average status information for each school, one-quarter will receive average growth information for each school, and one-quarter will receive both status and growth information for each school. The remaining quarter, the control group, will only receive demographic information.

Participants will complete this task six times. For five tasks of these tasks, they will choose between three randomly selected schools (serving students in grades 3-8) drawn from a randomly selected district (with the district sampling weighted by total enrollment to produce a proportional number of large and small districts). For the sixth task, they will choose between three randomly selected schools drawn from their own district.

This research design will allow us to estimate the average effects of providing growth information on the demographic characteristics of participants’ preferred schools. In other words, we can learn whether the provision of growth information causes participants to choose less white and less affluent schools on average. Moreover, because each participant chooses between schools in a different set of districts, we can learn about the kinds of districts where the provision of growth information facilitates integration, where it has no effect, and where it potentially exacerbates segregation. Because participants choose between schools in their own district for the final task, we can also learn if overall patterns replicate there or if the effects of providing growth information are neutralized by participants’ prior knowledge of local schools.
Intervention Start Date
2021-03-15
Intervention End Date
2021-04-05

Primary Outcomes

Primary Outcomes (end points)
Our primary outcome variables are the academic, demographic, and geographic characteristics (status, growth, racial/ethnic composition, the percentage of FRPL-eligible students, the percentage of students with limited English proficiency, and distance from home) of participants' preferred schools.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Please see our description of our intervention for the details of our experimental design.
Experimental Design Details
Randomization Method
Randomization done by a computer
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2,800 individuals
Sample size: planned number of observations
2,800 individuals
Sample size (or number of clusters) by treatment arms
700 individuals in the Control Group, 700 individuals in the Status Group, 700 individuals in the Growth Group, and 700 individuals in the Both Group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
George Mason University IRB
IRB Approval Date
2020-10-16
IRB Approval Number
N/A
Analysis Plan

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