African American and Latinx youth are often socialized towards athletic activity and sports participation, sometimes at the expense of their exploration of the range of potential career paths including those in the science, technology, engineering, and mathematics (STEM) fields. This project will immerse middle school youth in the rapidly growing world of sports data analytics and build their knowledge of statistics concepts and the data science process. The project will focus on the STEM interests and knowledge development of African American and Latinx youth, an underrepresented and underserved group in STEM. Researchers will explore the ways youths' social identities can and should serve as bridges towards future productive academic and professional identities including those associated with STEM learning and the STEM professions. The outcomes of the project will advance knowledge in promoting elements of informal learning experiences that build adolescents' motivation and persistence for productive participation in STEM courses and careers. This project is funded by the Advancing Informal STEM Learning program (AISL), which seeks to advance new approaches to and evidence-based understanding of the design and development of STEM learning opportunities for the public in informal environments, and the Innovative Technology Experiences for Students and Teachers program (ITEST), which funds projects that leverage innovative uses of technologies to prepare diverse youth for the STEM workforce, with a focus on broadening participation among underrepresented and underserved groups in STEM fields.
Over a three-year period, 250 middle school learners in the West Baltimore, Maryland and Hyattsville, Maryland areas will engage in three main learning activities: Summer Camp (three weeks), Sports Day Saturdays, and a Spring Summit. Through a partnership between the University of Maryland and Coppin State University, the project will utilize resources in multiple departments and units across both universities, and engage with youth sports leagues such as the American Athletic Union (AAU) to support participants' engagement in the data science process including collection of raw data, exploration of data, development of models, visualization, communication, and reporting of data, and data-driven decision making. Furthermore, youth participants will attend local AAU, college, and professional sporting events, and interact with members of coaching staffs to better understand the ways performance data technologies are utilized to inform recruitment and team performance. The mixed-methods research agenda for this project is guided by three main questions: (1) What elements of the project's model are most successful at supporting congruence of adolescents' academic identity, including STEM identity and social identity including athletic identity? (2) What elements support adolescents' motivation, and persistence for productive participation in current and future STEM courses? (3) To what extent did the project appear to influence participants' perceptions of their future professions? At multiple points throughout the experience, participants will complete surveys designed to document and assess statistics and data science knowledge; interest in STEM careers; academic, social and athletic identity development; and STEM course taking patterns. Researchers will also observe project activities, interview a focal group of participants, and survey participants' parents to identify elements of learning experiences that encourage and support adolescents' interest in STEM disciplines and STEM professions. The project team will develop conceptual and pedagogical frameworks that support middle school youth' engagement and interest in science, engineering, technology, and mathematics through repurposing spaces where these youths frequent. A major outcome of the project will be workforce preparation and offers a promising approach for encouraging youth to persist along STEM pathways, which may ultimately result in broadened participation in STEM workforces.
This project is funded by the National Science Foundation's (NSF's) Advancing Informal STEM Learning (AISL) program, which supports innovative research, approaches, and resources for use in a variety of learning settings.
AHA! Island is a new project that uses animation, live-action videos, and hands-on activities to support joint engagement of children and caregivers around computational thinking concepts and practices. This research is intended to examine the extent to which the prototyped media and activity sets support the project’s learning goals. Education Development Center (EDC), WGBH’s research partner for the project, conducted a small formative study with 16 English-speaking families (children and their caregivers) to test out these media and activity set prototypes. During the in-person video
Improving retention rates in postsecondary engineering degree programs is the single most effective approach for addressing the national shortage of skilled engineers. Both mathematics course placement and performance are strong graduation predictors in engineering, even after controlling for demographic characteristics. Underrepresented students (e.g., rural students, low-income students, first-generation students, and students of color) are disproportionately represented in cohorts that enter engineering programs not yet calculus-ready. Frequently, the time and cost of obtaining an engineering degree is increased, and the likelihood of obtaining the degree is also reduced. This educational problem is particularly acute for African American students who attended select high schools in South Carolina, with extremely high-poverty rates. As a result, the investigators proposed an NSF INCLUDES Launch Pilot project to develop a statewide consortium in South Carolina - comprising all of the public four-year institutions with ABET-approved engineering degree programs, all of the technical colleges, and 118 high schools with 70% or higher poverty rates, to pinpoint and address the barriers that prevent these students from being calculus ready in engineering.
This NSF INCLUDES Launch Pilot project will map completion/attrition pathways of students by collecting robust cross-sectional data to identify and understand the complex linkages between and behind critical decisions. Such data have not been available to this extent, especially focused on diverse populations. Further, by developing structural equation models (SEMs), the investigators will be able to build on extant research, contributing directly to understanding the relative impact of a range of latent variables on the development of engineering identity, particularly among African American, rural, low-income, and first-generation engineering students. Results of the pilot interventions are likely to contribute to the empirical and theoretical literature that focus on engineering persistence among underrepresented populations. Project plans also include developing a centralized database compatible to the Multiple Institution Database for Investigation of Engineering Longitudinal Development (MIDFIELD) project to share institutional data with K-12 and postsecondary administrators, engineering educators, and education researchers with NSF INCLUDES projects and beyond.
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TEAM MEMBERS:
Anand GramopadhyeDerek BrownEliza GallagherKristin Frady