Gender-STEM Stereotypes and College Major Choice

Last registered on November 19, 2024

Pre-Trial

Trial Information

General Information

Title
Gender-STEM Stereotypes and College Major Choice
RCT ID
AEARCTR-0014221
Initial registration date
September 06, 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
September 12, 2024, 5:51 PM EDT

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

Last updated
November 19, 2024, 3:22 PM EST

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

Locations

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Primary Investigator

Affiliation
Colby College

Other Primary Investigator(s)

PI Affiliation
University of Chicago

Additional Trial Information

Status
In development
Start date
2024-09-09
End date
2025-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project investigates the role of gendered stereotypes about STEM in perpetuating gender gaps in college major choice. We will study a population of undergraduate students at a large research university. To measure implicit gender stereotypes, we will administer a gender-science Implicit Association Test (IAT). We will combine IAT results with administrative transcript data and with original survey data to measure outcomes such as STEM course-taking, intended and declared major, and academic performance. To obtain causal evidence, we will administer an experimental treatment to assess how much college students’ gender stereotypes can be altered and how their observed, real-world academic choices (e.g., major selection) are affected as a result. Specifically, we will show a random subset of students their IAT results, making implicit stereotypes explicit. All students will take the IAT a second time, so we can observe whether and how implicit stereotypes are altered by the treatment. We hypothesize that in the absence of any intervention, women (men) with stronger implicit bias against women in STEM will be less (more) likely to take courses in or declare a major in a STEM subject. We also hypothesize that students being confronted with their own unconscious biases may cause them to question those implicit associations and make academic choices better in line with their explicit goals, thus closing gender gaps in STEM persistence.
External Link(s)

Registration Citation

Citation
Owen, Stephanie and Derek Rury. 2024. "Gender-STEM Stereotypes and College Major Choice." AEA RCT Registry. November 19. https://doi.org/10.1257/rct.14221-2.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Treated students will be informed of the results of the Implicit Association Test they took, revealing to them the extent of their gender bias (e.g., a strong/moderate/slight implicit association between male and STEM and female and humanities, or vice versa, or no gender association). These results will be accompanied with basic information about what the IAT measures. We will emphasize that implicit associations are not the same as explicit behaviors; holding a certain implicit attitude does not necessarily mean someone will behave in a certain way. The message will include the following statement, emphasizing that the link between stereotypes and behavior is not determinative:
"Research shows that making people aware of their implicit attitudes (stereotypes) may help them change their behavior to be less in line with the stereotype. We're hoping that by seeing your results, it will help you make a more objective and unbiased decision about your own academic path, without the influence of unconscious stereotypes."
The message will conclude with a link to learn more about the IAT.

Treated students will receive this information twice. First, as a debrief page immediately after the completion of the first IAT. Second, in an email sent around the time of next semester course selection.
Intervention Start Date
2024-09-09
Intervention End Date
2024-12-31

Primary Outcomes

Primary Outcomes (end points)
Implicit gender-STEM stereotype measured at baseline (September) and endline (December); performance in STEM courses; intended STEM major; declared STEM major; any STEM course-taking; STEM credits
Primary Outcomes (explanation)
Primary outcomes will come from the following sources:

Implicit gender-STEM stereotype: gender-science IAT score
Performance in STEM courses: university transcript data and learning management system data
Intended STEM major: student survey item (most likely major)
Declared STEM major: university transcript data
Any STEM course-taking: university transcript data
STEM credits: university transcript data

Secondary Outcomes

Secondary Outcomes (end points)
Explicit gender stereotypes
Secondary Outcomes (explanation)
Explicit gender stereotypes - student survey, measured as student's beliefs about gender representation in STEM and humanities

Note that our hypothesis involves testing for differential treatment effects by gender for all outcomes. We will also perform secondary heterogeneity analysis (all interacted with gender): prior academic preparation, race, socioeconomic status, gender of high school STEM role models, gender of college STEM instructors.

Experimental Design

Experimental Design
In early fall 2024, we will recruit a sample of eligible students to take a short survey about academic preferences, and to take a gender-science IAT. Upon immediate completion of the IAT, half of participants will randomly be assigned to see a debrief page revealing the extent of their gender bias (i.e., how strongly they associate men with STEM and women with humanities, or vice versa). The other half will receive no debrief. In the second half of the semester, all participants will take another short survey and take the IAT a second time. All survey and IAT responses will be linked to administrative transcript data using unique identifiers.
Experimental Design Details
Not available
Randomization Method
Randomization will be done within Qualtrics survey software, randomly assigning each survey respondent to take an IAT with or without the debrief page. We will do stratified randomization within gender.
Randomization Unit
Individual student
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
400-1000 students
Sample size: planned number of observations
400-1000 students (pending recruitment)
Sample size (or number of clusters) by treatment arms
200-500 (50%) treatment, 200-500 (50%) control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Colby College Institutional Review Board
IRB Approval Date
2024-08-14
IRB Approval Number
2023-80
IRB Name
University of Chicago Social and Behavioral Sciences Institutional Review Board
IRB Approval Date
2024-07-25
IRB Approval Number
IRB23-1230
IRB Name
University of Michigan Health Sciences and Behavioral Sciences Institutional Review Board
IRB Approval Date
2024-08-22
IRB Approval Number
HUM00240215
Analysis Plan

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