AI Tutor in the Business Economics Classroom

Last registered on April 01, 2026
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Pre-Trial

Trial Information

General Information

Title
AI Tutor in the Business Economics Classroom
RCT ID
AEARCTR-0018215
Initial registration date
March 26, 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
April 01, 2026, 9:55 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
Yan Lau
Affiliation
American University
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Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2026-01-12
End date
2026-07-31
Keywords
Education
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
I study whether student usage of an AI tutor improves academic outcomes and affects usage of other learning resources. The AI tutor is specifically trained on course materials and instructed to be a learning guide to students. I will randomly assign students in an undergraduate business economics class into several treatment arms, which vary in the number of emails they receive advertising and encouraging use of the AI tutor. I will then track their AI tutor usage and subsequent academic outcomes and usage of other learning resources to investigate the effect of the AI tutor.
External Link(s)

Registration Citation

Citation
Lau, Yan. 2026. "AI Tutor in the Business Economics Classroom." AEA RCT Registry. April 01. https://doi.org/10.1257/rct.18215-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-03-26
Intervention End Date
2026-05-02

Primary Outcomes

Primary Outcomes (end points)
AI tutor usage: number of days accessed, intensity of chat queries
Academic outcomes: final course grade, scores in quizzes, homework assignments, lecture attendance and participation
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Canvas LMS usage: access counts, timing of homework submissions
Office hours attendance
Post-study survey responses
Secondary Outcomes (explanation)
Post-study survey: I will administer a survey after the study asking about usage of AI resources, usage of non-AI resources, opinions about AI tutor and AI more generally.

Experimental Design

Experimental Design
This RCT will be conducted in an undergraduate business economics classroom setting and participants will be students enrolled in the course. Intervention emails will be sent and AI tutor usage will be tracked while academic and other resource usage outcomes will be collected. At the end of the semester, a post-study survey will be administered to students.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Block randomization by the 6 sections of the course. (Sections are defined by their lecture meeting times.) Each block will have a balance of treatment arms.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Random assignment of treatment will not be clustered.
Sample size: planned number of observations
Approximately 230 students
Sample size (or number of clusters) by treatment arms
Approximately a quarter of all students in each of 4 treatment arms. Treatment arms will receive 1, 2, 3 or 4 emails.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
American University IRB
IRB Approval Date
2026-01-06
IRB Approval Number
IRB-2026-142
Analysis Plan

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