Job Seekers’ Preferences for Educational Requirements and Their Perception of AI Cognitive Ability

Last registered on December 09, 2025
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Pre-Trial

Trial Information

General Information

Title
Job Seekers’ Preferences for Educational Requirements and Their Perception of AI Cognitive Ability
RCT ID
AEARCTR-0017409
Initial registration date
December 05, 2025

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
December 09, 2025, 7:46 AM EST

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
Zeyang Chen
Affiliation
Renmin University of China
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Other Primary Investigator(s)

PI Name
Lin Lin
PI Affiliation
Renmin University of China
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PI Name
Kai Liu
PI Affiliation
Renmin University of China
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PI Name
Fei Wang
PI Affiliation
Renmin University of China
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PI Name
Zhong Zhao
PI Affiliation
Renmin University of China
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PI Name
Xianqiang Zou
PI Affiliation
Renmin University of China
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Additional Trial Information

Status
On going
Start date
2025-12-02
End date
2026-03-31
Keywords
Behavior, Education, Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study uses an online information-intervention experiment to examine whether bachelor’s degree holders exhibit a systematic preference for jobs with higher educational requirements, and whether perceptions of AI cognitive ability can alter such preferences. Participants are randomly assigned to treatment and control groups, with the treatment group receiving information about the high cognitive performance of a state-of-the-art AI model. All participants then complete a series of job-choice tasks in which they evaluate paired job positions using a seven-point preference scale. By comparing choices across conditions, the study identifies how perceived AI capability and non-educational job attributes influence graduates’ willingness to consider positions requiring only an associate degree. The findings shed light on the behavioral roots of educational-requirement mismatch in the labor market and the potential of information interventions to mitigate it.
External Link(s)

Registration Citation

Citation
Chen, Zeyang et al. 2025. "Job Seekers’ Preferences for Educational Requirements and Their Perception of AI Cognitive Ability." AEA RCT Registry. December 09. https://doi.org/10.1257/rct.17409-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-12-02
Intervention End Date
2026-03-31

Primary Outcomes

Primary Outcomes (end points)
Job Preference Score: A 7-point scale measuring participants’ preference between two job postings (1 = strongly prefer Job A; 7 = strongly prefer Job B; 4 = no preference). Captures the central behavioral outcome—avoidance or acceptance of jobs requiring only an associate degree.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment consists of two core modules—AI cognition intervention and job-preference elicitation—supplemented by additional survey items on participant characteristics.

(1) AI Cognition Intervention (Between-subjects randomization): Participants are randomly assigned to treatment or control groups based on the odd–even status of their birth date. Initial AI cognition is measured using “AI model college entrance examination score predictions.” The treatment group receives information stating that “the Doubao large language model achieved a Gaokao-equivalent score close to 700 points,” while the control group receives no such information.

(2) Job Preference Measurement (Within-subjects randomization): Baseline comparison condition: Job A requires “associate degree or above,” Job B requires “bachelor’s degree or above,” with all other attributes held constant. Non-educational attribute treatments: Additional attributes are added only to Job A—such as career development potential, skill-training opportunities, wage premiums, job stability, and employee feedback—while Job B remains unchanged. Participants rate their preferences on a 7-point scale (1 = strongly prefer A; 4 = no preference; 7 = strongly prefer B).
Experimental Design Details
Not available
Randomization Method
Randomization done by the server of the survey platform
Randomization Unit
The AI Cognition Intervention is a between-subject randomization at individual level. The Job Preference Measurement is a within-subject randomization where the sequence of choice questions are randomized.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
4800 individuals
Sample size: planned number of observations
4800 individuals
Sample size (or number of clusters) by treatment arms
2400 individuals receive the AI Cognition Intervention, and 2400 do not.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
School of Labor and Human Resources, Renmin University of China
IRB Approval Date
2025-12-02
IRB Approval Number
SLHR20250012
Analysis Plan