Fighting gender stereotypes through narratives in gender roles and growth mindset- a RCT in Uruguay

Last registered on April 26, 2024


Trial Information

General Information

Fighting gender stereotypes through narratives in gender roles and growth mindset- a RCT in Uruguay
Initial registration date
April 21, 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
April 26, 2024, 11:47 AM EDT

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


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Primary Investigator

Universitat Autónoma de Barcelona

Other Primary Investigator(s)

PI Affiliation
Universitat Autónoma de Barcelona
PI Affiliation
Universitat de Barcelona
PI Affiliation
Universitat Autónoma de Barcelona

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This research project investigates how the exposure to different role models impact children’s interest in STEM fields. We design a field experiment integrated within a Computational Thinking (CT) teaching proposal in Uruguay to explore two critical hurdles in children’s interest in STEM: gender and growth mindset beliefs. We will manipulate a teaching module called ‘Write your own adventure’ - provided in the initial level of CT - and randomly assigned classes to one of four different biographies of accomplished scientists. These biographies will manipulate (i) either the gender (male or female) scientist, or (ii) the extent of growth mindset (whether they succeeded or they had to overcome academic struggles since the young age). We will assess the impact on children’s interest in STEM across the 4 biographies and a control group exposed to another teaching module unrelated to the previous biographies. Finally, we will shed light on the underlying mechanisms by analyzing how children gender stereotypes and norms, and beliefs about growth mindset change when exposed to different role models. Our results will contribute to better understand how to foster an environment where all children can pursue and reach their full potential.
External Link(s)

Registration Citation

Brun, Martin et al. 2024. "Fighting gender stereotypes through narratives in gender roles and growth mindset- a RCT in Uruguay." AEA RCT Registry. April 26.
Experimental Details


Our intervention introduces four different treatments within the framework of the "Write Your Own Adventure" proposal to investigate the impact of gender stereotypes and growth mindset on students’ academic perceptions. To achieve this, we will manipulate the biographies used in the proposal and the narratives embedded in the biographies. Specifically, two treatments will present biographies of male scientists, while the remaining two will present biographies of female scientists. Within each gender category, one biography will provide a general narrative over the scientist’s life and achievements, while the other will provide a narrative of scientists with growth mind-set. The latter implies that the scientists are portrayed in terms of their academic struggles, detailing the challenges faced during their formative years, and illustrating how they overcame these obstacles through effort, perseverance, and daily diligence to ultimately attain success in the field of science. We choose an active control group compose by classes engaging in a completely unrelated proposal within the CT program called "Animociones".

The script related to the four manipulations of the "Write Your Own Adventure" will be collaboratively designed by the researchers and extensively discussed with the CT’s team. The inclusion of this content in the curricula needs mutual agreement between both parties. The script for the "Animociones" proposal in the control group was designed by Ceibal for this project.

For a successfully implementation of the intervention, teachers will be trained. Ceibal will provide materials to support teachers in effectively incorporating these treatments into their classroom practices and facilitating the translation of these concepts to students. For example, it is important for teachers to emphasize the notion that failures should not be interpreted as a deficiency in innate ability or intelligence, but rather as powerful stimulus that propels individuals toward the achievements of their goals. By conveying the message that perseverance, effort and regularity play a pivotal role in the learning process, teachers can empower students to embrace challenges, develop a growth mindset, and cultivate a resilient approach to achieving their objectives.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Interest in STEM jobs
Primary Outcomes (explanation)
We propose using a set of questions derived from Grosch et al. (2022) to assess children’s interest in STEM and their self-perceived competence in science-related careers. Participants will be asked to indicate their level of interest in specific professions and express their belief in their ability to excel in them. These professions range from engineering, social work, computer science and programming, language and culture, mathematics, and art and design. Also, we collect information about whether working in these professions is perceived as difficult.

Secondary Outcomes

Secondary Outcomes (end points)
Confidence / Stereotypical thinking / Growth mindset / Maths preferences / Language Preferences / Maths performance
Secondary Outcomes (explanation)
Confidence: We measure confidence using the questions and methodology proposed in Grosch et al. (2022). Students are asked whether they believe they have the ability to perform well in several professions - the same proposed above - related to STEM and non-STEM fields. Additionally, we will include a variable that captures the number of questions individuals believe they answered correctly after a maths quiz.

Stereotypical thinking: We propose three measurements to capture explicit, implicit stereotypical thinking, and social stereotypical thinking. Explicit measures are borrowed from the Grosch et al. (2022)’s questionnaire. Implicit measures have gained recognition for their capacity to predict outcomes related to maths achievement and engagement, surpassing the predictive capacity of explicit measures. These implicit measures are sensitive to constructs beyond the gender-science stereotype, making them valuable tools for uncovering additional factors that influence outcomes in STEM fields. The implicit stereotypical thinking is generally assessed by means of the Implicit Association Test (IAT) (Greenwald et al., 1998) and will be administrated to both classroom and remote teachers. We also capture this implicit stereotypical thinking for children with the same IAT but in a adapted version from Grosch et al. (2022) and Cvencek et al. (2011). Third, we will incorporate explicit questions about gender stereotypes in science, focusing on the perspective of peers. For instance, we will ask to children whether according to their classmates, males or female are more talented in mathematics?

Growth mindset: We suggest using the measurement approach developed by Bettinger et al. (2018). This instrument consists of several questions that assess fixed/growth mindset. First, students will be asked whether they believe intelligence can be changed. Second, they will be questioned about their perception of their own ability to improve their maths skills. Lastly, a question will be included that correlates a fixed mindset with the level of effort required. All these questions will be administered at the individual level but will be also specific to the gender (i.e., "Do you believe girls/boys can change their level of intelligence?").

Maths preferences: We propose to measure maths preferences using nine questions employed in the HTHT project carried out in 2021. These questions capture children’s preference for maths. To create a comprehensive measure, we will use Principal Component Analysis (PCA) to extract primary factors.

Language Preferences: We suggest measuring this variable by employing the same nine questions we use for mathematics but adapted to language. This approach enables us to assess diverse preferences in language and mitigates the potential influence of children perceiving the experiment as solely maths-related, which might alter their behavior. To create a comprehensive measure, we will use PCA and extract primary factors.

Maths performance: To examine whether interest in STEM is enhanced among individuals with lower maths performance, we require baseline information on maths performance. In this regard, it is important for us to discuss with Ceibal’s team the feasibility of creating a quiz consisting of no more than 10 questions that assesses maths skills.

Experimental Design

Experimental Design
This study will exclusively target 5th and 6th-grade teachers and their students from urban, public schools in Uruguay (i.e children aged around 10 and 11 years). Participant teachers will be randomly assigned to 5 different arms, resulting in five distinct groups. Additionally, remote teachers will be randomly assigned to specific classrooms, allowing us to investigate potential variations in gender stereotypes associated with the gender of the remote teacher (male/female).
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
School, clustered by socio-demographic characteristics
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
60 schools, clustered by socio-demographic characteristics
Sample size: planned number of observations
2640 students
Sample size (or number of clusters) by treatment arms
528 students per treatment arm
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Comisión de Ética en la Recerca (CERec) of the Universitat Autonoma de Barcelona
IRB Approval Date
IRB Approval Number