Teaching gender equity through science (T-GEtS).

Unequal inclusion of women and girls in STEM fields starts in early childhood. From early childhood, children think about gender in terms of narrow gender stereotypes and mistaken assumptions about gender differences. Stereotypes are mental constructs about physical and social categories, including gender, that shape how people think about their own and others’ potential. This learning begins in early childhood and continues through adulthood. Boys and girls think about gender in terms of narrow gender categories and mistaken assumptions about gender differences. Young children’s ideas about gender are formed by beliefs about between-category differences (e.g., that boys and girls differ from each other in important ways) and within-category similarities (e.g., that girls are similar to each other in important ways). These beliefs shape how children learn about their own and others’ potential throughout childhood development. 

Our proposed solution T-GEtS will interrupt these patterns by developing a novel, scalable curriculum that uses the scientific method to help youth of all ages build more equitable gender concepts, with structured active learning activities focused on data literacy, statistical reasoning, and drawing inferences from group-relevant information. Our curriculum will ultimately be widely available and scaled for broad use by teachers, students, and stakeholders. 

The  T-GEtS project will consist of three phases: (1) Testing the effectiveness of several prototypes of the curriculum to maximize impact on students’ development of equitable gender concepts; (2) Scaling up the most promising prototype to a large-scale field study implemented in daily classroom settings, through close collaboration with schools, principals, educators, and teachers; and (3) training educators/teachers through personalized professional development and coaching modules to help them effectively engage their students and implement the curriculum.

Our  T-GEtS solution - in its growth phase - is thus a data-based, novel curriculum that uses the scientific method to teach gender equity. Our solution to address the problem of inaccurate concepts about who is “right” for science begins with teaching children how to analyze data and how to do simple experiments about gender-based misperceptions. Ultimately, the curriculum will be implemented at scale: disseminated across not only K-12 schools, but throughout higher education as well. The team is composed of scientists who  are all tenured/tenure-line faculty with complementary expertise in developmental science, including specialties in education, conceptual change, and gender stereotypes. This allows for the tailoring of the curriculum to be age-appropriate for maximum impact on the development of more equitable gender concepts across developmental ages. The potential scale of  the current project thus begins in early childhood, and extends through adolescents, and into emerging adulthood.

Simply put: the T-GEtS solution is a curriculum that is backed by science.  We use scientific findings and principles to teach science and to teach children about how to form more accurate concepts about other people. Data literacy training leads to the application of statistical reasoning in a variety of different contexts. Thus, what might seem to be an immediate short-term intervention has long-lasting, generalizable effects. Equally important, by replicating simple experiments, like judging heights,  students simultaneously learn how to design good experiments and see first-hand how beliefs about gender differences can lead to errors of judgment.  Students learn by actively engaging a subject.  Our curriculum will help students learn directly about the stereotypes that influence their judgments. 

The T-GEtS solution is a novel, scalable curriculum that teaches gender equity through data literacy and hands-on experimentation. Our strategy is supported by research suggesting that: (1) data training enhances awareness that seemingly obvious inferences might be wrong; that is, individuals become more skeptical and cautious before drawing a conclusion or drawing a generalization, and (2) training in the experimental method on topics of interest - such as judgments of people’s abilities - helps develop an understanding of how to control for confounding variables before drawing a conclusion about group differences.

Our T-GEtS solution will have broad impact for children, youth, and emerging adults. By helping youth think more critically about inferences about gender differences and similarities, our curriculum will interrupt the development of narrow gender concepts that shape how people reason about their own potential and the potential of those around them.

Dr. Virginia Valian (PhD, Northeastern University) is an expert in gender equity research, intervention, and dissemination. Dr. Valian is a Distinguished Professor at Hunter College, where she directs the Gender Equity Project, and at the City University of New York Graduate Center.  Her books (Why so slow? The advancement of women, 1998, MIT Press; An inclusive academy:  Achieving diversity and excellence, with Abigail Stewart, 2018, MIT Press) bring a science-based approach to gender equity.   Dr. Valian is a Fellow of the Psychonomic Society, a Fellow of the Association for Psychological Science, a Fellow of the Armenian Society of Fellows, and a member of the American Academy of Arts and Sciences.  She has been honored by WEPAN (Women in Engineering ProActive Network) and AWIS (American Women in Science). Valian’s work on gender stereotypes informs the solution developed in this proposal.

Dr. Anahid S. Modrek (PhD, Columbia University) is an expert in the research, application, and dissemination of science informed curricula in classroom settings. Dr. Modrek also has expertise in tailoring learning modules by age bandwidth, echoing the scalability of this project by creating elementary-aged, middle-school aged, high-school aged, and college-aged appropriate material. Dr. Modrek is a 2023 Provost’s Early Career Faculty Achievement Awardee, a 2022 Jefferson Emerging Medical Scholars (JEMS) Awardee, a 2021 Deeper Learning Fellow with the American Education Research Association (AERA) and is currently funded by the William & Flora Hewlett Foundation in collaboration with the American Institutes for Research (AIR).

Dr. Emily Foster-Hanson (PhD, NYU) is an expert in providing online, high-impact implementation of scientific research with children (see https://pubmed.ncbi.nlm.nih.gov/32982602/). Dr. Foster-Hanson is an established scholar with expertise in the development of narrow gender concepts across childhood.

The T-GEtS solution has been devised as a curriculum serving multiple school sites. The approximate number of students in pilot work thus far is almost at 200, with the team now looking to further scale these efforts.

Preliminary findings from the pilot study in Fall 2022 support anticipated results. Participants were adolescents ages 13-17 (54% female: age M = 15.58, range SD = 1.69) in 7th - 10th grades from a metropolitan school district in a large city in the Northeastern US. Study procedures were approved by the sponsoring university’s institutional review board and the school district prior to participant recruitment and data collection. A multi-phased design (resembling the one proposed here) yielded expected results and some new insights.

Adolescent participants were prompted to construct and elaborate explanations to support the recognition and interpretation of new data related to a causal claim, based on data made available to them. Based on their investigations, they were asked to conclude which features were effective v. irrelevant in predicting the outcome of interest. Some of the data confirmed their own initial beliefs, while other initial beliefs were not supported by the data. Participants who indicated an initial belief that a particular factor would be effective reacted in different ways upon seeing this belief disconfirmed. Cass [pseudonym] quickly abandoned an initial belief in favor of the conclusion the data indicated. In a concluding statement the next day, Cass elaborated by carefully weighing the two alternatives and adding a mechanistic explanation that helped him to make sense of and hence support a revised conclusion. Not everyone fully learns.  Terry [pseudonym], for example, interpreted the data as showing that the two levels of the factor are “about the same” in the outcomes they produce (despite a difference appearing in the data), saying neither alternative was “adding anything ....” He thus partially revised his initial mistaken belief in response to the data, but was unprepared to fully accept the superiority of the other level of the factor in the outcome it produced.  This is an example of the type of experimentation we will use. It shows partial or full belief change in participants, specifically in how they draw conclusions.

By joining a diverse community of entrepreneurs, professionals, and advocates of equity in STEM, we hope to share ways to scale efforts for developing a science-based approach to teaching gender equity  and beyond.  That will expand our network so that we can better scale our solution and target education policy.  We also look forward to collaborating with members of a diverse network.

Being part of the Solve Challenge will support our growth of collaborations both in the U.S. and abroad and ease some of the challenges associated with scaling up new, research-based solutions at international sites, as well as create collaborations across disciplines and sites (i.e., K-12 schools, Universities, etc.). The Solve Challenge will also provide the support and resources to initiate more rigorous and applied work, allowing for more diverse sampling (across cultures and ethnicities, as well as across different socioeconomic brackets). Most importantly, this fellowship will provide access to a network across different disciplines interested in translating solutions to inform long-term goals for gender equity.

Dr. Valian is a leading expert on gender equity.  Given the range of her network in the sciences, the solution we develop would receive widespread attention. Dr. Valian directs the Gender Equity Project (GEP) at Hunter College, where the solution would be incorporated as a focal project.  As a fellow of major societies in the field of psychology and as a member of the American Academy of Arts and Sciences, Dr. Valian’s work on our solution would have a wide audience. Dr. Valian’s work is considered a leading example in understanding how gender stereotypes develop and how they change.

Our solution applies a rigorous data science curriculum that will be age-appropriate to the user and established as a reliable method to change inaccurate generalizations - specifically those that engender inaccurate ideas about gender differences and human potential. 

Despite many efforts to identify and mitigate the negative effects of gender stereotypes, little has been done to alter the development of those stereotypes.  Our proposed solutions simultaneously teaches children about how to understand and collect data - in short, how to do science - and about using experiments to understand where inaccuracies exist in generalizations about gender.

Data science can be used to illustrate the process of generalizing sample information to a target population and the consequent formation of stereotypes. Our solution will show that the reliability of sample information influences the scope for generalization.  The proposed curriculum is designed to alter generalization errors.  For instance, a well-known statistical principle is that large samples yield more reliable population estimates than small samples. There are indications that this can be understood by laypeople - even young children.  

This aspect of our solution will show that reliable samples give more certainty when one is asked to generalize to a target population, and  that unreliable samples offer more scope for bias. Moreover, generalization to new samples or the population offers scope for motivational biases. 

Variability is another important concept:  traditional efforts to challenge stereotypes have tended to conceive of them as stereotypes in terms of central tendency, that is, in terms of the mean differences between groups while neglecting variability.  But understanding variability is central to understanding the importance of average difference.

Another novel feature of our solution is teaching children and young people how to conduct experiments where they are perceiving and evaluating others.  By doing these experiments themselves, children learn about threats to validity - confounding variables, heterogeneous samples, and so on.  They also can see the errors people make in judgment, for example, in judging the same performance by a girl as less accomplished than an equal performance by a boy.

As active scientists, scholars, and professors, we aim to make science and its applicability accessible to parents, teachers, educators, and stakeholders. Our team has a range of expertise, from serving on advisory boards (i.e., Digital Promise), to facilitating curriculum re-design and implementation for learning, to participating in initiatives bringing researchers and educators together. We have published with teachers and educators and contributed to broadly disseminated position papers and blogs translating findings for non-academic audiences. We hope to work with the Challenge leaders to develop new outlets for engaging the public in science, with emphasis on this solution reaching underserved communities. We would be interested in organizing workshops and training programs for teachers, parents as well as school districts, emphasizing the exchange of ideas between scientists and practitioners and how to make this solution publicly available with the appropriate tools and resources for individuals to implement them.

We are enthusiastic to initiate new partnerships in the Solve Challenge/MIT community, and  eager to cross-pollinate with members in other programs.

We first aim to provide evidence and data measuring change in students’ change in stereotypes. Within the first year, we will provide cost effective, accurate assessments after administering the curriculum (capable of being administered frequently) demonstrating changes in now only questionnaires surveying knowledge, but also less bias responding in judging competence of participants. 

Next, given significance and applicability of the  T-GEtS solution, we expect to not only have it disseminated widely to K-12 schools and universities - likely reaching thousands of students after one year, but also to publish in top scientific outlets with broad readership. We aim to write empirical papers, co-authored with colleagues, as well as theoretical reviews challenging prevailing conceptions of intervening on gender stereotypes.

In addition to presenting at academic conferences we will work with the Solve Challenge board and current media outlets (i.e., Child Development Series: National Geographic) to ensure findings reach a broad audience. Our past work has been reported in prominent outlets (i.e., InsideHigherEd, Academic Minute, WAMC Radio) and we expect similar coverage.

We are intervening on the development of gender stereotypes. Our curriculum will help teachers, students and stakeholders implement a new curriculum that can be made widely available and scaled for broad use. The curriculum can be implemented at scale - disseminated across not only K-12 schools, but universities as well. The team is composed of scientists who are all tenured/tenure-line faculty with expertise in cognitive science, especially developmental science. This allows for the tailoring of the curriculum to be age-specific, and appropriate to the age bandwidth being targeted. The scalability thus extends from childhood, though adolescence, and into emerging adulthood. Education in complex statistical reasoning is one possible means of proactively intervening on, and changing, the way individuals draw inferences from group-relevant information. Thus, one way the curriculum will develop gender equity is through data literacy.  The other way is through actively conducting small experiments.

Notable is that our solution does not solely target girls - we aim to bring this solution, this new way of thinking, to all genders to create an inclusive and moes sustainable equitable future for all genders.

We will use an easy-to-use web-based data analysis platform: CODAP (i.e., see https://codap.concord.org/releases/latest/static/dg/en/cert/index.html?url=https://concord-consortium.github.io/codap-data/SampleDocs/Social_Science/World/Children_per_Women/Children_per_Women.codap) where we will tailor datasets specifically around gender stereotypes and have participants test their theories, all the while utilizing the statistical, data-science training methods described to have them revise normative judgments. 

Currently, CODAP is publicly available with our solution however having a more tailored, specific dataset to target exactly our core interest here: gender equity.

For another example, based on work by Nobel Prize-winning game theorist, Thomas Schelling, a small demand for diversity can desegregate a neighborhood (see https://ncase.me/polygons/).

Three tenured or tenure track Professors and both graduate and undergraduate student research assistants. (Estimated team total of approximately 10 in the first year, with growth after one year.)

We will be partnered with several schools with dozens of teachers and principals, and respective students (estimated impact is 1,000+ students within the first year). The number of students affected will exponentially grow subsequently.

Dr. Valian has been working on this solution for 30 years, while Drs. Modrek and Foster-Hanson have been working on this topic for over a decade. Together, our team brings nearly 50 years of research, science, and scholarship to the development and implementation of this solution.

As scientists, we actively incorporate students, schools, and communities who have not had science easily accessible to them. We actively seek and mentor students from underrepresented populations to create opportunities for learning and developing skills for science. We similarly actively seek out underserved and under resourced schools to bring these opportunities to communities that would otherwise not have them.

Notable is that our solution does not solely target girls - we aim to bring this solution, this new way of thinking, to all genders to create an inclusive and more sustainable equitable future for all genders.

The primary allocation of funds goes directly to the study participants and participating organizations, as well as the research team's time/salary. This ensures the resources for the workload proposed here are not only cost-saving, but also key to ensuring the implementation of T-GEtS.

The workload has been architected to ensure fast, dense turnaround with the implementation of the solution. We find this uses the most cost-effective approach, so that there is no third-party managing these efforts that not only results in longer turnaround time but also additional funds (we are thus reducing costs). Instead, our proposed allocation of resources is the most efficient and monitored approach that will disseminate T-GEtS immediately to the students and youth it is meant to serve. This will have a significant and positive economic and scientific impact on the broader project. 

Given significance and applicability of this work, in addition to the solution's impact and dissemination, we expect to similarly present and publish in top outlets with broad readership. We aim to write empirical papers, co-authored with trainees, as well as theoretical reviews challenging prevailing conceptions of learning.

In addition to presenting at academic conferences, we will work with the Foundations currently funding some of our work (I.e., William & Flora Hewlett Foundation) and affiliated media outlets (i.e., Child Development Series:National Geographic) to ensure findings reach a broad audience.

Our past work has been reported in prominent outlets we expect similar coverage. Moreover, we will use scientific findings and impacts of the solution to secure larger grants with foundations actively looking to support such efforts (i.e., National Science Foundation) to design educational interventions resulting in tools supporting learning for all.

As a team, we aim to build relationships with educators to promote understanding of gender equity in youth and to develop new tools to support that learning. We hope to establish international collaborations within the tech community to continue to explore how diversity in learning contexts impacts learning, and initiate future cross-cultural work.

By increasing public awareness about how variability in learning environments may set children on distinct trajectories towards gender equity, we plan to contribute to designing educational practices that are not only culturally-sensitive, but capitalize on the individual learner’s prior strengths, and prior experiences, to support learning and its development across the lifespan towards a more equitable future.

Drs. Valian, Modrek, and Foster-Hanson have all secured and successfully executed funding to support these projects. For example, Dr. Modrek works as the Principal Investigator (PI) and Director of the Learning to Learn (L2L) Lab where she actively seeks and mentor students from underrepresented populations to create opportunities for learning. Dr. Modrek's lab alone has secured 4 funding awards that are being dispersed this academic year to the end of Summer 2023 (FY23), (with one continuing through FY24). One funding award is from the William and Flora Hewlett Foundation where as PI [$25,000] Modrek is working with the American Institutes for Research (AIR) on a national effort of school development, analyzing 22 matched-pair schools (11 in treatment and 11 in a comparison/control group) across the U.S. looking at teacher instruction.

The second funding award we've received is internal, the Jefferson Faculty Completion Grant [$15,000] extending work as a former National Science Foundation (NSF) fellow studying pedagogy and respective effects on Latina/o youth’s cognitive outcomes in east Los Angeles districts.

The third funding award is internal where we have been awarded the 2022 JEMS (Jefferson Emerging Medical Scholars) Award [$38,193]. 

The fourth award has my graduate students and trainees on these projects as primary recipients. In our supervisory role, these graduate students are recipients of the HRSA Graduate Student CAIPE Award [$20,000] which is the Child / Adolescent Interprofessional Practice and Education (CAIPE) Program funded by the Health Resources & Services Administration (HRSA) to undertake, and implement, social-justice oriented initiatives through their clinical training.

In sum, the total active award amount to Dr. Modrek's L2L Lab alone has for FY23 is $98,193. These funds have also created three new jobs on campus – for lab members who are paid for their time. To date, over $23,000 has been dispersed to L2L students. L2L has not only become a rigorous research hub in the broader field of Psychology, but it is also a training opportunity and job prospect for scientists in training.

Prior to this academic year, in total, Drs. Valian, Modrek, and Foster-Hanson have secured and successfully completed projects with funding totaling over 3 million over the entirety of their careers.