Engineering is arguably one of the most critical skills in any society, from building bridges and homes, to designing cell phones and life-saving medical devices. Yet many Americans do not consider engineering to be essential or relevant to their everyday lives, and may even question its positive impact on society. While there have been gains in the number of women and underrepresented minorities in STEM professions over the past few decades, their numbers in the field remain disproportionately low. The Built World integrated multimedia and research project therefore aims to expand access to engineering content through the lens of “inclusive engineering,” which highlights how problem-solvers of all ages, genders, backgrounds, and perspectives approach and overcome challenges to innovate. The project applies this concept through the creation of Built World, a three-hour documentary series for broadcast on PBS stations nationwide, and a complementary interactive escape game streamed live on Twitch, where individuals of all ages and backgrounds can play and solve engineering challenges together. There is a need for effective remote and virtual interaction to support informal STEM learning, and live streaming game platforms present a promising approach to filling this need. Built World is poised to advance the field through: (1) content - creating high-quality inclusive engineering content across multiple platforms to reach a wide audience (Built World documentary, digital reporting and short form videos, community outreach campaign); (2) applied research - designing and studying how live-streaming, collaborative platforms can serve as safe and inclusive spaces for engineering learning; and (3) best practices - exploring how audiences engage with inclusive engineering on different platforms—a traditional documentary format (Built World) versus an interactive, collaborative space (Twitch game)—and identifying what learning outcomes might be expected on each.
A three-phase research design aims to understand what motivates users to engage with STEM content on Twitch; how to define and measure learning outcomes associated with the platform; and how to mitigate the risk of toxic environments in online communities by fostering safe spaces for a diversity of gamers. Phase 1 informs the initial design of the Twitch game and audience interaction strategies and seeks to answer: What is the best way to measure informal learning on Twitch? What is the best way to design a Twitch channel to create an inclusive space while optimizing learner engagement? Phase 2 is the core focus of the research and uses a semi-experimental design to answer questions such as: Is there evidence of learning on Twitch, and what type of learning is happening? What is the digital culture that emerges? Phase 3 assesses the pairing of the documentary series with the Twitch game to maximize informal STEM learning and is guided by questions such as: How does inclusive engineering content presented on two platforms (Twitch game and Built World series) mediate learning outcomes? How does inclusive engineering content presented on two platforms shape learners’ experiences of inclusivity and belonging? Knowledge generated through the Built World project will offer tools and best practices to other STEM media producers so that they may also leverage live streaming platforms for learning.
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