NSF Award
2314089
In dozens of ways, youths' lives are shaped by data. Yet, youth seldom have the opportunity to pull back the curtain on data science to experience how data are collected, prepared, analyzed, and presented into the final, neatly packaged statistics and figures they see every day. This lack of first-hand data science experience not only limits youths' data science skills - key to their educational and career pathways - but also limits their skills as civically engaged decision-makers capable of critically analyzing data-based claims. This project investigates how youth can use low-cost sensors to collect data from their communities and engage in data science practices to explore and tell stories about community-relevant phenomena (e.g., climate change, urban segregation, public transportation, pollution). These museum-based camps are week-long, immersive experiences that focus on question formulation, data collection, analysis, visualization, and interpretation. The informal camp setting offers a mix of both high-contact instructional time (i.e., working with other students and facilitators during the day) and independent exploration time (i.e., taking the hardware home each afternoon and evening) through which youth can both learn new skills and apply them in their homes and communities. <br/><br/>In this collaborative project, a university research lab and children's science museum work together to design, implement, study, and revise a week-long data science camp for middle school age students, data science learning assessment items and a facilitator training curriculum. Camps will be implemented during Winter, Spring, and Summer school breaks over a two year period. The project will investigate two primary questions: What data science knowledge and practices do learners gain in the course of designing, carrying out and interpreting a scientific data collection effort relevant to their community? And what ways can museums serve as springboards and touchstones for broader informal STEM learning experiences that expand into learners' homes and communities? Potential contributions include learning theory and design heuristics for informal STEM education programming that positions STEM inquiry and learning within participants' broader communities and sparks youth's recognition of the relevance of a data-oriented approach to understanding their day-to-day environments, spaces, and lives. As camp programming includes four diverse informal data contexts of increasing independence and complexity - (1) guided explorations; (2) 1-day projects; (3) multi-day projects; and (4) longitudinal, at-home, extension projects for a subset of participants (who take the hardware home) - anticipated contributions include comparisons of the varied settings in which informal data science learning occurs. The project uses a mixed-methods research approach that includes: 1) quantitative analyses of paired pre- and post-camp assessments to identify shifts in data science practices and perspectives; 2) qualitative thematic analyses of pre-, post-camp, and delayed interviews triangulated with interaction analysis of in-camp observations; and 3), and log file analyses identifying patterns in learners' data gathering behavior. Additionally, longitudinal analyses of assessment and interview data over the 2.5-year project timeframe will gauge the efficacy of camp curriculum and assessment revisions over the 6 implementations. The project centers equity and belonging in two primary ways: curriculum development efforts focus on inclusive and equitable informal science learning and a focus on Latine populations who are often underserved in STEM education.<br/><br/>This 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. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.<br/><br/>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.
