Understanding the Bias in Teaching Ratings

Last registered on June 23, 2023
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Pre-Trial

Trial Information

General Information

Title
Understanding the Bias in Teaching Ratings
RCT ID
AEARCTR-0011529
Initial registration date
June 06, 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
June 23, 2023, 3:43 PM 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
University College London
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Additional Trial Information

Status
In development
Start date
2023-06-06
End date
2028-06-06
Keywords
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 lead to bias in teaching ratings.
External Link(s)

Registration Citation

Citation
Heller, Monika, Kamalini Ramdas and Tong Wang. 2023. "Understanding the Bias in Teaching Ratings." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.11529-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-06-06
Intervention End Date
2023-06-30

Primary Outcomes

Primary Outcomes (end points)
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 prior ratings and gender on teaching ratings. Details are in the pre-analysis plan in the version of "Understanding Bias in Teaching Ratings_PAP_June2023."
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 2000 participants.
Sample size: planned number of observations
2000 individuals.
Sample size (or number of clusters) by treatment arms
There are 250 participants per condition and in total 8 conditions. Details regarding random assignments are in the pre-analysis plan in the version of "Understanding Bias in Teaching Ratings_PAP_June2023."
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
2020-09-08
IRB Approval Number
REC644-09062023
Analysis Plan

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