Data is increasingly important in all aspects of people’s lives, from the day-to-day, to careers and to civic engagement. Preparing youth to use data to answer questions and solve problems empowers them to participate in society as informed citizens and opens doors to 21st century career opportunities. Ensuring equitable representation in data literacy and data science careers is critical. For many girls underrepresented in STEM, developing a "data science identity" requires personally meaningful experiences working with data. This project aims to promote middle school-aged girls’ interest and aspirations in data science through an identity-aligned, social game-based learning approach. The goals are to create a more diverse and inclusive generation of data scientists who see data as a resource and who are equipped with the skills and dispositions necessary to work with data in order to solve practical problems. The research team will run 10 social clubs and 10 data science clubs mentored by women in data science recruited through the University of Miami’s Institute for Data Science and Computing. Participants will be 250 middle school-aged girls recruited in Miami, FL, and Yolo County, CA, through local and national girls’ organizations. Youth will participate in a data science club and will learn key data science concepts and skills, including data structures, storage, exploration, analysis, and visualization. These concepts will be learned from working with their own data collected in personally meaningful ways in addition to working with data collected by others in the same social game eco-system. The project will also develop facilitator materials to allow adult volunteers to create game-based informal data science learning experiences for youth in their areas. The project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments and is co-funded by the Innovative Technology Experiences for Students and Teachers (ITEST), which seeks to engage underrepresented students in technology-rich learning environments, including skills in data literacy, and increase students’ knowledge and interest in information and communication technology (ICT) careers.
Researchers will focus on two primary research questions: 1) Across gameplay and club experiences, in what ways do participants engage with data to pursue personal or social goals? 2) How do gameplay and club experiences shape girls’ perceptions of data, data science, and their fit with data and data science? The project will use design-based research methods to iteratively design the game and social club experiences. To ensure that uses of data feel personally and socially meaningful to young girls, the virtual world’s goals, narratives, and activities will be co-designed with girls from groups underrepresented in data science. The project will research engagement with game data in two informal, game-based learning scenarios: organic, self-directed, social play club, and structured, adult-facilitated data science clubs. The research will use a combination of quantitative and qualitative methods including surveys, focus groups, interviews, and gameplay and club observations. Project evaluation will determine how gameplay and club experiences impact participants' attitudes toward and interest in data-rich futures. The project holds the potential for broadening participation and promoting interest in data science by blending game-based learning with the rich social and adult mentoring through club participation. The results will be disseminated through conference presentations, scholarly publications, and social media. The game and facilitator materials will be designed for dissemination and made freely available to the public.
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TEAM MEMBERS:
Lisa HardyGary GoldbergerJennifer Kahn
This poster was presented at the 2021 NSF AISL Awardee Meeting.
Collaborative robots – cobots – are designed to work with humans, not replace them. What learning affordances are created in educational games when learners program robots to assist them in a game instead of being the game? What game designs work best?
This award takes an innovative approach to an ongoing, pervasive, and persistent societal issue: women are still drastically underrepresented in computing careers. This project targets middle school-aged girls because it is a time when many of them lose interest and confidence in pursuing technical education and computing careers. This project will design, develop, and deploy a one-week experience focused on middle school girls that targets this issue with a novel combination of teaching techniques and technology. The project will use wearable computing devices to support girls' social interactions as they learn computing and solve technical challenges together. The goals of the project are to raise interest, perceived competence, and involvement in the computational ability of girls. Additionally, the project aims to increase a sense of computational community for girls that makes pursuing computational skills more relevant to their identities and lives, and that helps continued participation in computing. The project will deploy a one-week experience four times per year with a socioeconomically diverse range of campers. The project will also develop a 'program in a box' kit that can be broadly used by others wishing to deliver a similar experience for girls.
The planned research will determine if a one-week experience that uses social wearable construction in the context of live-action role play can use the mediating process of computational community formation to positively impact middle school girls' engagement with and interest in computation. Computational community is defined as girls engaging together in the process of learning computation, trading resources and knowledge, and supporting growth. Research participants will include 100 6th to 9th-grade girls. At least 75% of the participants will be either low income, first-generation college-bound, or underrepresented in higher education. Students will be recruited through the longstanding partnerships with title one schools in the Salinas Valley, the Educational Partnership Center, and in the Pajaro Valley Unified School district, where 82% of the students are Hispanic/Latinx, 42% are English Learners, and 73% are eligible for free or reduced lunch. The research questions are: 1) Does the proposed experience increase girls' self-reported competence, self-efficacy, and interest in computational skills and careers? and 2) Will the proposed experience lead to activity-based evidence of learning and integration of computational skills at the group social level? The project will use a mixed-methods, design-based research approach which is an iterative design process to rapidly collect and analyze data, and regularly discuss the implications for practice with the design team. Data will be collected using observations, interviews, focus groups, surveys, and staff logs. Quantitative data will be analyzed using frequencies, means, and measures of dispersion will be applied to survey data from both time points. Pearson correlation coefficients will be used to describe the bivariate relationship between continuous factors. ANOVAs will assess whether there are significant differences in continuous measures across groups. Qualitative data will be analyzed using a constant comparison method.
This Innovations in Development award is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
We found that the learners seeking out resources to teach themselves to code were generally college educated women who were motived either by the desire to be able to read and understand the code written by hired developers or the desire to become developers themselves. The importance of a female-focused learning setting was mixed; while most women acknowledged a more comfortable atmosphere created by such a setting, very few cited that as a primary reason for joining the group.
All learner participants in this study persisted through the ten weeks of the Women’s Coaching and Learning
In 2016, ETR received a National Science Foundation grant to study, under Principal Investigator Louise Ann (“Lou Ann”) Lyon, PhD, a newly formed, real-world organization dedicated to helping women in the workforce learn to write computer code. This project formed a partnership between a research team with experience in computer science (CS) education and learning sciences research and a newly fashioned practitioner team focused on building a grassroots, informal, volunteer group created to help women help themselves and others learn to write computer code. This research-practitioner
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
Participants in this study reported a variety of resources used in the past to learn to code in Apex, including online tutorials, one-day classes sponsored by Salesforce, and meet-up groups focused on learning. They reported various difficulties in learning through these resources, including what they viewed as the gendered nature of classes where the men already seemed to know how to code—which set a fast pace for the class, difficulty in knowing “where to start” in their learning, and a lack of time to practice learning due to work and family responsibilities. The Coaching and Learning Group
Grassroots women's learn-to-code groups are springing up in many places. This infographic a study of one such group, in which more-knowledgeable "coaches" lead novice "learners" in learning software programming on the Salesforce platform. This study found that women create such groups to have supportive, non-threatening environments that nuture their learning to build confidence before entering male-dominated software development communities.
The goal of this three-year project is to leverage NSF’s investment in both SciGirls and computer science education by engaging 8-13 year-old girls in computational thinking and coding through innovative transmedia programming which inspires and prepares them for future computer science studies and careers.