An Evaluation of Expanding Work Study Opportunities with Internships

Last registered on May 02, 2025
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Pre-Trial

Trial Information

General Information

Title
An Evaluation of Expanding Work Study Opportunities with Internships
RCT ID
AEARCTR-0015784
Initial registration date
April 29, 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
May 02, 2025, 5:52 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
Eric Bettinger
Affiliation
Stanford University
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Other Primary Investigator(s)

PI Name
Nichole Torpey-Saboe
PI Affiliation
Strada Foundation
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Additional Trial Information

Status
In development
Start date
2025-04-21
End date
2029-04-01
Keywords
Education
Additional Keywords
Work Study, financial aid, internship, college outcomes
JEL code(s)
I22, I23
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The federal work study program provides financial incentives to encourage low-income students to work during their university studies and to enable universities to create jobs for them. However, often university jobs do not provide substantial opportunities for students to gain work experience relevant to their future employment. While the majority of work study funds are used for on-campus employment, in some cases federal work-study can also be used to support off-campus roles as a way to provide students with more career-relevant work experiences in professional settings. In addition, many states have added their own work-study programs, some of which also allow for students to be placed in private sector employment. Expanding work-study opportunities at private sector employers could transform the impact of the program on post-college success.

We partner with Folio Works, a company that works as an intermediary between universities and firms providing internships. Folio helps university students who are eligible for work study to acquire internships with private companies. Students are paid with work study funds, and they gain professional experience that is often distinct from the typical campus-based work-study jobs.

We examine the impact of these internships on students educational and vocational outcomes.
External Link(s)

Registration Citation

Citation
Bettinger, Eric and Nichole Torpey-Saboe. 2025. "An Evaluation of Expanding Work Study Opportunities with Internships." AEA RCT Registry. May 02. https://doi.org/10.1257/rct.15784-1.0
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Experimental Details

Interventions

Intervention(s)
Folio Works has more applicants than internships. They will offer qualified applicants internships using a randomized ordering to allow for a research. Students who are offered an internship can choose to accept it or not. During students' internship, Folio provides additional coaching on soft skills and workplace etiquette. The internships vary according to the firms that offer them.
Intervention Start Date
2025-04-21
Intervention End Date
2027-04-01

Primary Outcomes

Primary Outcomes (end points)
Job trajectories after the internship
Primary Outcomes (explanation)
The goal is to understand if the internships affect students' subsequent job trajectories. For some students, the most proximal outcome involves course choice and major field of study. However, many students are using Folio Works at the end of their academic careers. In these cases, job interests and jobs are the key outcomes. In some partner states, we hope to be able to measure employment after graduation through administrative sources. We will also conduct a survey of treatment/control students.

Specific outcomes related to "job trajectories":
Subsequent coursework related to internship
Major choice related to internship
Employment after graduation
Employment related to internship after graduation

Secondary Outcomes

Secondary Outcomes (end points)
Soft skills and job etiquette
Secondary Outcomes (explanation)
Folio also uses a curriculum that includes some soft skill training and some training on job etiquette. We will amend this registry with a more detailed list of outcomes and variables that we will measure to capture these concepts.

Experimental Design

Experimental Design
This is a stratified random experiment. Based on the applications and supply, Folio will create bins. For example, one bin might be applicants from a particular college related to computer science. The supply for that bin would be internships that relate to computer science for that area. Applicants receive an application number. This number is randomly assigned and creates a randomized ordering of applicants in each bin. Since applications are submitted on a rolling basis, Folio will then, once they are ready to assign, make the offers based on the randomized ordering. Randomization occurs whenever the number of applicants exceeds the number of internships in that bin. Folio determines the window to keep a bin open depending on the deadlines that the industry partners have. Randomization will continue for at least 18 months.
Experimental Design Details
Not available
Randomization Method
Randomization will be based on random numbered ordering within bins. Random number is assigned at the time of application. Bins will vary in size, and the ordering dictates offers and the waitlist.
Randomization Unit
This is a stratified randomized experiment at the student level. Each bin is a separate experiment.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
None.
Sample size: planned number of observations
The target is to have 800 treatment and 800 control students.
Sample size (or number of clusters) by treatment arms
There is only one treatment -- receiving an internship offer. We anticipate 800 treated students.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We aim for a sample of 1600 observations with half being selected through the randomization process. We are hoping for 40 students in each of 40 bins. If onboarding survey covariates and stratification controls for the bins explain 40 percent of the variation in students’ outcomes, we calculate that with 80 percent power (the probability of rejecting the null hypothesis of zero effect), the minimum detectable effect (MDE) is 0.11 standard deviations. To contextualize, consider the outcome “choosing a major related to the internship.” If 20 percent of students in the control group select a related major, the standard deviation for this variable is 0.4. An effect size of 0.11 standard deviations corresponds to a 4.4 percentage point increase in the likelihood of choosing a related major.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Stanford University
IRB Approval Date
2025-04-18
IRB Approval Number
N/A
Analysis Plan