x

NEW UPDATE: Completed trials may now upload and register supplementary documents (e.g. null results reports, populated pre-analysis plans, or post-trial results reports) in the Post Trial section under Reports, Papers, & Other Materials.
What is the effect of informing schools of their internal efficiency indicators? Experimental evidence from Argentina
Last registered on August 02, 2018
View Trial History

Pre-Trial

Trial Information
General Information
Title
What is the effect of informing schools of their internal efficiency indicators? Experimental evidence from Argentina
RCT ID
AEARCTR-0003033
Initial registration date
May 31, 2018
Last updated
August 02, 2018 6:49 PM EDT
Location(s)
Country
Argentina
Region
Primary Investigator
Name
Alejandro Ganimian
Affiliation
New York University
Contact Primary Investigator
Other Primary Investigator(s)
PI Name
María A. Cortelezzi
PI Affiliation
Proyecto Educar 2050
Contact Investigator
PI Name
Jonah E. Rockoff
PI Affiliation
Columbia Business School
Contact Investigator
PI Name
Alejandro J. Ganimian
PI Affiliation
Steinhardt School of Culture, Education, and Human Development - New York University
Contact Investigator
Additional Trial Information
Status
On going
Start date
2017-03-15
End date
2019-07-01
Keywords
Education
Additional Keywords
JEL code(s)
C93, I21, I22, I25
Secondary IDs
Abstract
Many developing countries provide schools with diagnostic feedback on their performance. Yet, evidence on these initiatives focuses on the effect of providing information on student achievement. We conducted four experiments in Argentina to estimate the effect of providing schools with information on internal efficiency (e.g., passing, repetition, and dropout rates), which is more readily available and easier to understand.

In 2017, we carried out two studies. In study 1, which covered 23 out of Argentina’s 24 provinces, we randomly assigned schools to one of three groups: (a) one in which they received report cards that compared their internal efficiency indicators to those of all other schools in the country; (b) one in which they received similar reports that only compared them to schools of the same management type (i.e., public or private); or (c) one that did not receive any reports. In study 2, in the Province of Tucumán, we randomly assigned schools to one of four groups: (a) one of the three groups in study 1; or (b) one in which schools received report cards that compared their internal efficiency indicators to those of all other schools in the country and a professional development workshop for principals.

In 2018, we conducted two more studies. In study 3, which covered 23 provinces, we randomly assigned schools to one of two groups: (a) one in which they received report cards that compared their internal efficiency indicators to those of all other schools in the country; or (b) one that did not receive any report cards. In study 4, in the Province of Salta, we randomly assigned schools to: (a) a group that received a print version of the report; or (b) one that did not receive any reports.


External Link(s)
Registration Citation
Citation
Cortelezzi, María et al. 2018. "What is the effect of informing schools of their internal efficiency indicators? Experimental evidence from Argentina." AEA RCT Registry. August 02. https://doi.org/10.1257/rct.3033-2.0.
Former Citation
Cortelezzi, María et al. 2018. "What is the effect of informing schools of their internal efficiency indicators? Experimental evidence from Argentina." AEA RCT Registry. August 02. http://www.socialscienceregistry.org/trials/3033/history/32579.
Sponsors & Partners

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2017-03-15
Intervention End Date
2018-12-31
Primary Outcomes
Primary Outcomes (end points)
number of enrolled students, passing rates, grade failure rates, repetition rates, dropout rates, learning outcomes
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In 2017, we carried out two studies. In study 1, which covered 23 out of Argentina’s 24 provinces, we randomly assigned 14,404 primary schools and 8,016 secondary schools to one of three groups: (a) one in which schools received report cards that compared their internal efficiency indicators to those of all other schools in the country; (b) one in which schools received similar report cards that only compared them to schools of the same management type (i.e., public or private); or (c) one that did not receive any reports. In study 2, in one of the 24 provinces, we randomly assigned 605 primary schools and 398 secondary schools to one of four groups: (a) one of the three groups in study 1; or (b) one in which schools received report cards that compared their internal efficiency indicators to those of all other schools in the country and a professional development workshop for principals. All treatment schools in 2017 accessed the report cards through an online platform.

In 2018, we conducted two more studies. In study 3, which covered 23 provinces, we randomly assigned 13,776 primary schools and 8,109 secondary schools to one of two groups: (a) one in which schools received report cards that compared their internal efficiency indicators to those of all other schools in the country; or (b) one that did not receive any report cards. All treatment schools accessed the report cards through the same online platform from 2017, but we made it more difficult for schools to opt out of the report. In study 4, in one of the 24 provinces, we randomly assigned 629 primary schools and 241 secondary schools to: (a) a group that received a print version of the report; or (b) one that did not receive any reports.
Experimental Design Details
Randomization Method
Randomization was conducted in Stata 15 in a computer
Randomization Unit
Schools
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
N/A
Sample size: planned number of observations
Study 1: 14,404 primary schools and 8,016 secondary schools Study 2: 605 primary schools and 398 secondary schools Study 3: 13,776 primary schools and 8,109 secondary schools Study 4: 629 primary schools and 241 secondary schools
Sample size (or number of clusters) by treatment arms
We ran two lotteries in 2017. In study 1, which covered 23 out of Argentina’s 24 provinces, we randomly assigned 14,404 primary schools and 8,016 secondary schools to one of three groups: (a) one in which schools received report cards that compared their internal efficiency indicators to those of all other schools in the country (group 1A); (b) one in which schools received similar report cards that only compared them to schools of the same management type (i.e., public or private) (group 1B); or (c) one that did not receive any reports (group 2). In study 2, in one of the 24 provinces, we randomly assigned 605 primary schools and 398 secondary schools to one of four groups: (a) one of the three groups in study 1; or (b) one in which schools received report cards that compared their internal efficiency to that of all other schools in the country and a professional development workshop for principals (group 3).

We also ran two lotteries in 2018. In study 3, which covered 23 provinces, we randomly assigned 13,776 primary schools and 8,109 secondary schools to one of two groups: (a) one in which schools received report cards that compared their internal efficiency indicators to those of all other schools in the country (group 1A); or (b) one that did not receive any reports (group 2). In study 4, in one of the 24 provinces, we randomly assigned 629 primary schools and 241 secondary schools to one of three groups: (a) one in which schools received web-based report cards that compared their internal efficiency to that of all other schools in the country (group 1A); (b) one in which schools received similar printed report cards (group 1C); or (b) one that did not receive any reports (group 2).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is 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