Raising Teaching Quality through Instructional Modeling and Coaching: Evidence from a Large-Scale, Randomized Evaluation in Rural India

Last registered on March 08, 2023

Pre-Trial

Trial Information

General Information

Title
Raising Teaching Quality through Instructional Modeling and Coaching: Evidence from a Large-Scale, Randomized Evaluation in Rural India
RCT ID
AEARCTR-0010986
Initial registration date
February 22, 2023

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, 2023, 11:20 AM EST

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

Locations

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Primary Investigator

Affiliation
Freeman Spogli Institute for International Studies, Stanford University

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2022-06-01
End date
2025-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Students in low- and middle-income countries often exhibit poor learning outcomes, which in the long-term can hinder economic development and exacerbate social inequality. While in theory poor learning outcomes can be improved by exposing students to higher quality teaching, it is not immediately clear how to systematically raise teaching quality in low- and middle-income country settings. In particular, teacher professional development (or teacher training) programs, which are often implemented by policymakers for the purpose of raising teaching quality, have thus far proven ineffective in low- and middle-income country settings. One possible reason for the lack of effectiveness is that these programs are often of short duration and of low quality. The goal of this study is to instead examine the impacts of introducing “high-quality” teacher professional development which uses practices often shown to be effective in high-income countries. Specifically, we conduct a randomized controlled trial with 140 rural public schools in India, in which half of the schools are assigned to a teacher professional development program which relies on an instructional modeling and coaching of sustained duration; the other half of the schools are assigned to a control condition of no professional development. We examine impacts of two dimensions of the program on a range of student learning outcomes: (a) co-teaching with a more experienced instructional coach; (b) teaching on one’s own after having been accompanied by the instructional coach. Importantly, we also examine whether the professional development program improves essential teacher behaviors such as the avoidance of verbal abuse and corporal punishment.
External Link(s)

Registration Citation

Citation
Loyalka, Prashant. 2023. "Raising Teaching Quality through Instructional Modeling and Coaching: Evidence from a Large-Scale, Randomized Evaluation in Rural India." AEA RCT Registry. March 08. https://doi.org/10.1257/rct.10986-1.0
Experimental Details

Interventions

Intervention(s)
Instructional coach regularly accompanies (models and coaches) an existing schoolteacher in “best instructional practices” and for a sustained duration
Intervention Start Date
2022-08-16
Intervention End Date
2022-12-23

Primary Outcomes

Primary Outcomes (end points)
literacy, numeracy, cognitive skills test scores (z-scored); whether teacher uses verbal/corporal means (1/0)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
A large-scale, cluster-level randomized controlled trial (RCT) will be conducted among rural children in one state in India. The RCT will include approximately 7,500 students in 140 schools (in 235 classrooms) that were randomly sampled from a particular region in that state. The sample schools will be randomly assigned within strata to either receive the program to raise teacher quality (the treatment group) or not (the control group). Each stratum consists of four schools that are most similar in average baseline literacy scores, and within each stratum, 2 schools are randomly assigned to treatment and 2 schools are randomly assigned to control.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
school
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
140
Sample size: planned number of observations
~7500
Sample size (or number of clusters) by treatment arms
70 schools in each arm
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For the purposes of the power analysis, we set power at 0.8, alpha at 0.01 (in the conservative case of making Bonferroni adjustments to test five different hypotheses), R-squared conservatively at 0.4 (capturing the relationship between the outcome measure and baseline controls including the digital literacy pre-test score), and approximately 53 students per school (7,500 students in 140 schools). After stratifying schools into groups of 4 based on their average literacy score at baseline (and randomizing 2 classes to each treatment condition within each stratum), we estimate that the intraclass correlation coefficient in the digital literacy test is 0.000. For each pairwise treatment comparison, the minimum detectable effect size (MDES) is approximately 0.08 SDs. We expect to lose only a small amount of statistical power due to minimal student attrition from baseline to endline surveys.
IRB

Institutional Review Boards (IRBs)

IRB Name
Stanford University IRB
IRB Approval Date
2021-04-02
IRB Approval Number
57827
Analysis Plan

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