Effects of Relative Rank in Achievement and Effort

Last registered on August 28, 2024

Pre-Trial

Trial Information

General Information

Title
Effects of Relative Rank in Achievement and Effort
RCT ID
AEARCTR-0014216
Initial registration date
August 22, 2024

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
August 28, 2024, 3:11 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

Affiliation
University of Florida

Other Primary Investigator(s)

PI Affiliation
University of Florida
PI Affiliation
University of Florida

Additional Trial Information

Status
In development
Start date
2024-08-26
End date
2024-12-13
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This research proposal seeks to explore how receiving information regarding relative standing within an academic environment—such as a student’s individual rank in comparison to peers—affects students’ learning experiences, engagement levels, and overall achievement. When student achievement is independent of peer achievement, economic theory predicts that information on relative achievement rank should have no impact on student effort allocation or future achievement. Extensive literature demonstrates this is simply not true [for a review, see Delaney and Devereux (2022)]. This study adds an additional dimension to this literature by introducing relative effort ranks. Rather than providing all students with information regarding their rank in some achievement distribution, we would provide a subset of students with information on their rank in an effort distribution. Our work, by considering a new type of information, is well suited to address the practical limitations of the existing literature on rank effects.
External Link(s)

Registration Citation

Citation
Estrada, Carlos, Thomas Knight and Garrison Pollard. 2024. "Effects of Relative Rank in Achievement and Effort." AEA RCT Registry. August 28. https://doi.org/10.1257/rct.14216-1.0
Experimental Details

Interventions

Intervention(s)
This study is to be conducted in an introductory economics course (Principles of Macroeconomics) at a large, comprehensive research university.

When grades are posted for the first and second exam in Principles of Macroeconomics, the course grader will send an email or Canvas message to each student providing: (1) their grade on the exam, (2) a link to the answer key for the exam, and (3) one of 3 randomly chosen messages:
1. (Treatment 1) Information on their Relative Performance Rank (i.e. percentile) on the exam
2. (Treatment 2) Information on their Relative Effort Rank (i.e. percentile) in the period prior to the exam
3. (Control) No Additional Information
The Relative Performance Rank will be determined using actual test score distributions for the entire course. The Relative Effort Rank will be determined by an index measure generated using Canvas course analytics to capture relative course engagement.
Intervention Start Date
2024-09-30
Intervention End Date
2024-11-08

Primary Outcomes

Primary Outcomes (end points)
1 - Future Exam Performance
2 - Course Withdrawal
Primary Outcomes (explanation)
Future exam performance is the exam score on the exam immediately following the intervention. Course withdrawal is whether the student withdrew from the course before the end of the course.

Secondary Outcomes

Secondary Outcomes (end points)
1 - Future Course Engagement
Secondary Outcomes (explanation)
Future course engagement refers to an index measure generated using Canvas course analytics to capture relative course engagement.

Experimental Design

Experimental Design
Students in a large introductory economics course will receive an email after each exam containing information on their performance on the exam as well as some additional information on relative performance which varies by treatment arm.
Experimental Design Details
Not available
Randomization Method
Randomization by computer
Randomization Unit
Individual-exam
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1200 students (approximation which depends on student enrollment)
Sample size: planned number of observations
1200 students (approximation which depends on student enrollment)
Sample size (or number of clusters) by treatment arms
400 control, 400 treatment 1, 400 treatment 2
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Florida
IRB Approval Date
2024-08-19
IRB Approval Number
IRB202401228