Informal STEM learning experiences (ISLEs), such as participating in science, computing, and engineering clubs and camps, have been associated with the development of youth’s science, technology, engineering, and mathematics interests and career aspirations. However, research on ISLEs predominantly focuses on institutional settings such as museums and science centers, which are often discursively inaccessible to youth who identify with minoritized demographic groups. Using latent class analysis, we identify five general profiles (i.e., classes) of childhood participation in ISLEs from data
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TEAM MEMBERS:
Remy DouHeidi CianZahra HazariPhilip SadlerGerhard Sonnert
This AISL Pilots and Feasibility project will study the data science learning that takes place as members of the public explore and analyze open civic data related to their everyday lives. Government services, such as education, transportation, and non-emergency municipal requests, are becoming increasingly digital. Generally, program workshops and events may be able to support participants in using such data to answer their own questions, such as: "How do City agencies respond to noise in my neighborhood?" and "How do waste and recycling services in my neighborhood compare with others?" This project seeks to understanding how such programs are designed and facilitated to support diverse communities in accessing and meaningfully analyzing data will promote innovation and knowledge building in informal data science education. The team will begin by summarizing best practices in data science education from a variety of fields. Next they will explore the design and impacts of two programs in New York City, a leader in publicly available Open Data initiatives. This phase will explore activities and facilitation approaches, participants' objectives and data literacy skills practice, and begin to identify potential barriers to entry and levels of participation. Finally, the team will build capacity for other similar organizations to explore and understand their impacts on community members' engagement with civic data. This pilot study will establish preliminary evidence of the effectiveness of these programs, and in turn, inform future research into the identifying and amplifying best practices to support public engagement with data.
This research team will begin by synthesizing data science learning best practices based on varied literatures and surveys with academic and practitioner experts.
Synthesis results will be applied as a lens to gather preliminary evidence regarding the impacts of two programs on participants' data science practices and understanding of the nature of data in the context of civics. The programs include one offered by the Mayor's Office of Data Analytics (MODA), which is the NYC agency with overall responsibility for the City's Open Data programs, and BetaNYC, a leading nonprofit organization working to improve lives through civic design, technology, and engagement with government open data. The research design triangulates ethnographic observations and artifacts, pre and post adapted surveys, and interviews with participants and facilitators. Researchers will identify programmatic metrics and adapts existing measures to assess various outcomes related to public engagement with data, including: question formulation, data set selection and manipulation, the use of data to make inferences, and understanding variability, sampling and context. These metrics will be shared through an initial assessment framework for data science learning in the context of community engagement with civic open data. Researchers will also begin to identify barriers to broader participation through literature synthesis, interviews with participants and facilitators, and conversations with other organizations in our networks, such as NYC Community Boards. Findings will determine the suitability of the programs under study and inform future research to identify and amplify best practices in supporting public engagement with data.
This project is funded by the NSF Advancing Informal STEM Learning 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.
This Pilots and Feasibility Studies 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.
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
In this NSF INCLUDES Design and Development Launch Pilot the institutions of "Building on Strengths" propose to build and pilot the infrastructure, induction process, and early implementation of the Mathematician Affiliates of Color network. This network will consist of mathematicians of color from across academia and industry who want to invest time in, share their expertise with, and learn from students of color and their teachers. Building on Strengths will draw on basic needs cognitive theory to support these interactions and will focus narrowly on short and moderate term collaborations (from one month to a semester) between visiting mathematicians, students, and collaborating teachers that will involve three specific types of interactions: doing mathematics together as a habits-of-mind practice, talking about the discipline of mathematics and the experiences of mathematicians of color in that discipline, and relationship-building activities. The foundational infrastructure developed in the project will include systems for recruitment, selection and induction, a process for pairing affiliate mathematicians with classrooms, and support structures for the collaborations. To support the goals of the network a prototype virtual space will be developed in which real-time artifacts can be collected and shared from the classroom interactions. While Building on Strengths will pilot this program in the secondary context, once a viable model is established, scaling to K-16, as well as to other STEM fields, will be possible.
The research study in the project uses an exploratory sequential mixed-methods design and will be conducted in two phases. In the first, quantitative, phase of the study the following questions will be addressed: (1) Is the teacher-mathematician collaboration associated with a change for students in perception of basic human needs being met, mathematical or racial identities, or beliefs about mathematics or who can do mathematics? (2) Is the teacher-mathematician collaboration associated with a change for adults in perceptions of the role of basic needs or in adults' identities or beliefs about mathematics or who can do mathematics? In the second, qualitative, phase of the study, two types of interactions will be selected for in-depth qualitative study, identifying cases where groups of students experienced changes in their needs, identity, and beliefs. In this qualitative case-centered phase, the following questions will be explored: (1) What is the nature of the mentor-student interaction? (2) What aspects of the intervention do students feel are most relevant to them? (3) How did the implementation of the intervention differ from the anticipated intervention? The results of the study will help improve the infrastructure for, and better support the interactions between, mathematicians of color, students of color and their mathematics teachers; the outcomes will also shed light on how students experience their interactions.
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TEAM MEMBERS:
Michael YoungMaisha MosesAlbert CuocoEden Badertscher
The Sustainability Teams Empower and Amplify Membership in STEM (S-TEAMS), an NSF INCLUDES Design and Development Launch Pilot project, will tackle the problem of persistent underrepresentation by low-income, minority, and women students in STEM disciplines and careers through transdisciplinary teamwork. As science is increasingly done in teams, collaborations bring diversity to research. Diverse interactions can support critical thinking, problem-solving, and is a priority among STEM disciplines. By exploring a set of individual contributors that can be effect change through collective impact, this project will explore alternative approaches to broadly enhance diversity in STEM, such as sense of community and perceived program benefit. The S-TEAMS project relies on the use of sustainability as the organizing frame for the deployment of learning communities (teams) that engage deeply with active learning. Studies on the issue of underrepresentation often cite a feeling of isolation and lack of academically supportive networks with other students like themselves as major reasons for a disinclination to pursue education and careers in STEM, even as the numbers of underrepresented groups are increasing in colleges and universities across the country. The growth of sustainability science provides an excellent opportunity to include students from underrepresented groups in supportive teams working together on problems that require expertise in multiple disciplines. Participating students will develop professional skills and strengthen STEM- and sustainability-specific skills through real-world experience in problem solving and team science. Ultimately this project is expected to help increase the number of qualified professionals in the field of sustainability and the number of minorities in the STEM professions.
While there is certainly a clear need to improve engagement and retention of underrepresented groups across the entire spectrum of STEM education - from K-12 through graduate education, and on through career choices - the explicit focus here is on the undergraduate piece of this critical issue. This approach to teamwork makes STEM socialization integral to the active learning process. Five-member transdisciplinary teams, from disciplines such as biology, chemistry, computer and information sciences, geography, geology, mathematics, physics, and sustainability science, will work together for ten weeks in summer 2018 on real-world projects with corporations, government organizations, and nongovernment organizations. Sustainability teams with low participation by underrepresented groups will be compared to those with high representation to gather insights regarding individual and collective engagement, productivity, and ongoing interest in STEM. Such insights will be used to scale up the effort through partnership with New Jersey Higher Education Partnership for Sustainability (NJHEPS).
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TEAM MEMBERS:
Amy TuiningaAshwani VasishthPankaj Lai