Random Experiment on Relative Feedback with University Students

Last registered on October 02, 2025

Pre-Trial

Trial Information

General Information

Title
Random Experiment on Relative Feedback with University Students
RCT ID
AEARCTR-0014016
Initial registration date
July 13, 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
July 17, 2024, 1:44 PM EDT

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

Last updated
October 02, 2025, 4:43 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
Universidad Rey Juan Carlos

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2022-01-09
End date
2024-12-31
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Our research analyzes the impact of relative feedback on the academic performance and motivation of university students at one of the leading universities in Madrid. After the students take a midterm exam, the treatment group is given their percentile rank in relation to the class average grades. At the end of the course, we aim to determine whether the feedback's impact on the treatment group improves their grades or, conversely, if it leads to overconfidence and worsens their results.
External Link(s)

Registration Citation

Citation
Macías, Cristian. 2025. "Random Experiment on Relative Feedback with University Students." AEA RCT Registry. October 02. https://doi.org/10.1257/rct.14016-1.1
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Our research analyzes the impact of relative feedback on the academic performance and motivation of university students at one of the leading universities in Madrid. After the students take a midterm exam, the treatment group is given their percentile rank in relation to the class average grades. At the end of the course, we aim to determine whether the feedback's impact on the treatment group improves their grades or, conversely, if it leads to overconfidence and worsens their results.

As a post-trial update, we wish to register that, in addition to the pre-specified average treatment effect analyses, we have conducted a series of heterogeneity analyses. These include subgroup interactions by baseline performance (low initial grades), socioeconomic indicators (scholarship status, low parental education), self-reported expectations, relative age (quarter of birth), gender, and academic history (number of enrollments, exam round, and age). We also explored variation across different PLAN assignments and interactions with resource indicators such as car ownership, driving license, and private classes. These analyses were performed using the same specifications as the main models, with robustness checks including PLAN fixed effects, individual controls, and alternative outcome definitions (e.g., grade improvements between midterm and final exam).

The results indicate that average treatment effects remain small and mostly insignificant, but important heterogeneity emerges. In particular, students with weaker academic histories (older, more exam attempts, or multiple prior enrollments) tend to benefit more from percentile feedback, consistent with a motivation-through-information mechanism. Similarly, students with lower expectations or disadvantaged family backgrounds display differential responses, though often imprecisely estimated. These findings, while exploratory and not pre-registered, enrich the interpretation of the intervention’s impact and highlight the importance of considering subgroup variation in the design of information-based educational interventions.
Intervention (Hidden)
The aim is to analyze whether knowledge of their percentile rank throughout the semester among students at Universidad Rey Juan Carlos in Madrid improves their final course grades. To achieve this, a database has been compiled over several semesters, comprising a sample of over 600 students. The class was divided into a treatment group, who received their percentile rank along with their midterm grade, and a control group, who only received their exam grade. To understand the sample, questionnaires were administered at the beginning of the course, asking for relevant data and their estimated final course grade. Additionally, at the end of the course, another questionnaire was administered to determine whether awareness of their percentile rank stimulates additional motivation or, conversely, leads to overconfidence.
Intervention Start Date
2022-01-10
Intervention End Date
2024-12-31

Primary Outcomes

Primary Outcomes (end points)
Determining whether relative feedback helps improve university students' grades
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The aim is to analyze whether knowledge of their percentile rank throughout the semester among students at Universidad Rey Juan Carlos in Madrid improves their final course grades. To achieve this, a database has been compiled over several semesters, comprising a sample of over 600 students. The class was divided into a treatment group, who received their percentile rank along with their midterm grade, and a control group, who only received their exam grade. To understand the sample, questionnaires were administered at the beginning of the course, asking for relevant data and their estimated final course grade. Additionally, at the end of the course, another questionnaire was administered to determine whether awareness of their percentile rank stimulates additional motivation or, conversely, leads to overconfidence.

As a post-trial update, we wish to register that, in addition to the pre-specified average treatment effect analyses, we have conducted a series of heterogeneity analyses. These include subgroup interactions by baseline performance (low initial grades), socioeconomic indicators (scholarship status, low parental education), self-reported expectations, relative age (quarter of birth), gender, and academic history (number of enrollments, exam round, and age). We also explored variation across different PLAN assignments and interactions with resource indicators such as car ownership, driving license, and private classes. These analyses were performed using the same specifications as the main models, with robustness checks including PLAN fixed effects, individual controls, and alternative outcome definitions (e.g., grade improvements between midterm and final exam).

The results indicate that average treatment effects remain small and mostly insignificant, but important heterogeneity emerges. In particular, students with weaker academic histories (older, more exam attempts, or multiple prior enrollments) tend to benefit more from percentile feedback, consistent with a motivation-through-information mechanism. Similarly, students with lower expectations or disadvantaged family backgrounds display differential responses, though often imprecisely estimated. These findings, while exploratory and not pre-registered, enrich the interpretation of the intervention’s impact and highlight the importance of considering subgroup variation in the design of information-based educational interventions.
Experimental Design Details
Randomization Method
Randomized experiment conducted using statistical software
Randomization Unit
University students from different degrees and subjects across various academic years
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
604 students
Sample size: planned number of observations
1500 students
Sample size (or number of clusters) by treatment arms
300 students in the control group and 304 in the treatment group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
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