AI Information and High School Students' College Major Choices: Evidence from a Randomized Information Experiment

Last registered on June 15, 2026
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Pre-Trial

Trial Information

General Information

Title
AI Information and High School Students' College Major Choices: Evidence from a Randomized Information Experiment
RCT ID
AEARCTR-0018826
Initial registration date
June 03, 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
June 15, 2026, 5:33 AM EDT

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

Locations

Country
China
Region
Shaanxi

Primary Investigator

Name
Chaoqian Shi
Affiliation
Xi'an Jiaotong University
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Other Primary Investigator(s)

PI Name
Hui Mao
PI Affiliation
Xi'an Jiaotong University
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PI Name
Kaixin Huang
PI Affiliation
Peking University
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Additional Trial Information

Status
In development
Start date
2026-06-15
End date
2026-12-31
Keywords
Behavior, Education, Labor, Other
Additional Keywords
artificial intelligence, college major choice, high school students, information experiment, labor market expectations, China
JEL code(s)
I21, I23, J24, D83, O33
Secondary IDs
N/A
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study uses a randomized information experiment to examine whether information about artificial intelligence and future labor-market changes affects Chinese high school students' intended college major choices, expectations about employment prospects, perceptions of AI substitution and complementarity, and willingness to seek additional major-choice information. Participants complete a baseline questionnaire, are randomly assigned to read different standardized information materials, and then complete comprehension checks and follow-up outcome measures. The intervention does not provide individualized college-major recommendations and is designed as a low-risk educational information treatment.
External Link(s)

Registration Citation

Citation
Huang, Kaixin, Hui Mao and Chaoqian Shi. 2026. "AI Information and High School Students' College Major Choices: Evidence from a Randomized Information Experiment." AEA RCT Registry. June 15. https://doi.org/10.1257/rct.18826-1.0
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Experimental Details

Interventions

Intervention(s)
Participating classrooms will be randomly assigned to one of two standardized information materials. Students in control classrooms will receive general information about college major choice, while students in treatment classrooms will receive information about how artificial intelligence may affect future tasks, occupations, and college major choices. The materials do not provide individualized college application advice.
Intervention Start Date
2026-06-16
Intervention End Date
2026-07-15

Primary Outcomes

Primary Outcomes (end points)
Change in first-choice intended college major category; change in top-three intended major categories; expectations about employment prospects and income prospects for intended major fields; perceived AI substitution risk and AI complementarity for intended major fields; willingness to search for additional information about majors, employment, and AI impacts; willingness to use AI tools to assist major-choice information search.
Primary Outcomes (explanation)
Major-choice outcomes will be constructed by comparing baseline and post-intervention intended major categories. Changes in first-choice and top-three intended major categories will be coded as indicators of whether the reported category changes after the information treatment. Expectations, perceived AI risks and opportunities, and information-search willingness will be measured using post-intervention survey items and, where appropriate, standardized indices within outcome families.

Secondary Outcomes

Secondary Outcomes (end points)
AI career anxiety; AI opportunity beliefs; AI self-efficacy; confidence in major choice; perceived credibility, relevance, and comprehension of the information materials; interest in receiving additional major-choice information or AI prompting templates.
Secondary Outcomes (explanation)
Secondary outcomes will be measured using survey items or indices constructed from related Likert-scale questions. Material comprehension and credibility measures will also be used for descriptive checks and robustness analyses.

Experimental Design

Experimental Design
This study uses a two-arm cluster-randomized information experiment with high school students in China. Forty participating classrooms across two high schools will be randomly assigned to one of two information materials. Students first complete consent and baseline questions, receive the information material assigned to their classroom, complete comprehension checks, and then answer follow-up outcome questions. The study compares outcomes between students in classrooms assigned to the AI information group and students in classrooms assigned to the general college-major information group.
Experimental Design Details
Not available
Randomization Method
Randomization will be implemented at the classroom level using a pre-specified computer-based random assignment procedure, preferably stratified by high school. Each participating classroom will be assigned to either the control group or the AI information group before survey implementation.
Randomization Unit
Classroom.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
40 classrooms across two high schools
Sample size: planned number of observations
Approximately 1,500 high school students
Sample size (or number of clusters) by treatment arms
Approximately 20 classrooms assigned to the control group and 20 classrooms assigned to the AI information group, with approximately 750 students in each arm. The exact number of students may vary depending on classroom size, school implementation, and student participation.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
No formal power calculation has been finalized. The planned sample size is based on expected access to 40 participating classrooms across two high schools. The analysis will account for classroom-level randomization and clustering. If the final number of students or participating classrooms is smaller than planned, the study will report statistical power limitations and interpret results accordingly.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Xi'an Jiaotong University Social Science Research Ethics Review
IRB Approval Date
2026-06-03
IRB Approval Number
N/A
Analysis Plan