Mitigating Bias in Teaching Ratings

Last registered on May 18, 2026
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Pre-Trial

Trial Information

General Information

Title
Mitigating Bias in Teaching Ratings
RCT ID
AEARCTR-0018648
Initial registration date
May 14, 2026

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
May 18, 2026, 7:24 AM EDT

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

Locations

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Primary Investigator

Name
Tong Wang
Affiliation
London Business School
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Other Primary Investigator(s)

PI Name
Kamalini Ramdas
PI Affiliation
London Business School
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PI Name
Monika Heller
PI Affiliation
EHESP French School of Public Health
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Additional Trial Information

Status
In development
Start date
2026-05-15
End date
2029-12-31
Keywords
Behavior, Education, Gender
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
In this experiment, we aim to study factors that may mitigate bias in teaching ratings.
External Link(s)

Registration Citation

Citation
Heller, Monika, Kamalini Ramdas and Tong Wang. 2026. "Mitigating Bias in Teaching Ratings." AEA RCT Registry. May 18. https://doi.org/10.1257/rct.18648-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-05-15
Intervention End Date
2029-12-31

Primary Outcomes

Primary Outcomes (end points)
Teaching ratings and learning outcomes (described in the pre-analysis plan).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We are conducting this experiment to explore the effect of cognitive load on gender bias in teaching ratings. Details are in the pre-analysis plan in the version of "Mitigating Bias in Teaching Ratings_PAP_May2026."
Experimental Design Details
Not available
Randomization Method
Randomization of the survey will be done via the randomizing function in Qualtrics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We plan to recruit 1500 participants.
Sample size: planned number of observations
1500 individuals.
Sample size (or number of clusters) by treatment arms
There are 150 participants per condition and in total 10 conditions. Details regarding random assignments are in the pre-analysis plan in the version of "Mitigating Bias in Teaching Ratings_PAP_May2026."
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
London Business School
IRB Approval Date
2025-01-09
IRB Approval Number
REC1000
Analysis Plan

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