Contrary to trends in most rural communities, which are shrinking and aging, many rural Midwestern communities have experienced rapid population growth since the 1980s, as migrants and refugees have been moving there to meet growing labor demand in the agroindustrial sector such as meat and poultry processing. The school-aged residents of these growing Midwestern communities, who are primarily the U.S.-born children of low-skilled workers, represent a significant untapped population of future STEM workers and entrepreneurs who are growing up in, and want to stay in, rural America. There is a lack of research on workforce development in rural communities with large migrant and refugee populations. Thus, there is a critical need to study strategies to both train, and also keep, this skilled workforce local to rural communities where expanded employment opportunities (e.g., industries building state-of-the-art factories) can limit out-migration of technical and entrepreneurial talent. The goal of this planning grant is to pilot new Extended Reality (XR)-enabled STEM educational delivery models developed in collaboration with youth and adults in rural communities with large numbers of low-skilled workers. XR-enabled solutions can support active and experiential learning by enhancing hands-on activities, creating simulations of objects and experiences that may not be accessible in the physical world, and promoting learners' engagement with complex real-life problems.

The planning research consists of three main activities: 1) identify stakeholder needs and aspirations for new place-based educational curricula in STEM fields and entrepreneurship in partnership with the Storm Lake community via workshops, interviews, and focus groups; 2) use workshops to co-design (designing with as opposed to designing for) innovative XR-enabled technology delivery models to meet these needs; and 3) assess the outcomes of the pilot project via surveys. These activities will help address two research questions: 1) How can inclusive and place-based educational delivery models for rural workforce development benefit communities with large numbers of low-skilled workers? 2) Which XR-enabled smart and connected technology solutions will improve inclusive and place-based STEM educational delivery models in a rural community with a large number of low-skilled workers? This project is a partnership between Iowa State University, Iowa 4-H Youth Development, and the Storm Lake Community School District. The City of Storm Lake (pop. 10,600) was chosen as the site for these pilot activities because it is a rural Iowa community with a large low-skilled workforce employed in the agroindustrial sector and a K-12 student population that is 64% English Language Learners and 85% students of color. The results of the planning grant will yield new insights into the educational needs of rural communities, and the opportunities and barriers that place-based technologies can offer for supporting those educational needs, which is an underexplored area in the literature. Thus, this work is aligned with the Smart and Connected Communities program, which endeavors to integrate community stakeholders into smart and connected community projects to co-create and pilot solutions that are directly informed by the needs, challenges, and opportunities of present and future communities. This project is also being funded via the NSF Improving Undergraduate STEM Education Program, which seeks to support projects that have high potential for broader societal impacts, including improved diversity of students and instructors participating in STEM education, professional development for instructors to ensure adoption of new and effective pedagogical techniques that meet the changing needs of students, and projects that promote institutional partnerships for collaborative research and development.

In the age of the self-driving car, what role can autonomous technologies play in improving water systems? Floods are the leading cause of severe weather fatalities across the United States. Furthermore, large quantities of metals, nutrients, and other pollutants are washed off during storm events, making their way via streams and rivers to lakes and costal zones. To contend with these concerns, most communities across the United States maintain dedicated infrastructure (pipes, ponds, basins, wetlands, etc.) to convey and treat water during storm events. Much of this stormwater infrastructure is approaching the end of its design life, which results in more flooding and degraded water quality. Instead of building new and bigger stormwater infrastructure, which is cost prohibitive for many communities, it is possible to use existing infrastructure more effectively. The goal of this proposal is to enable the next generation of smart and connected stormwater systems, which use sensors to anticipate changes in weather and the urban landscape, and adapt their operation using active flow controls (e.g., gates, valves, pumps). This will drastically improve community resilience to floods and water quality. Equipping stormwater systems with low-cost sensors and controllers will provide a cost-effective solution to transform infrastructure from static to adaptive, permitting it to be automated and instantly reconfigured to respond to changing community needs and preferences. This research will address a truly national-scale infrastructure challenge and will lay the foundation upon which to empower and educate communities to adopt smart and autonomous stormwater solutions.

The research to enable "smart" stormwater systems will be conducted by a team of engineers, social scientists, computer scientist and environmental experts in tight collaboration with decision makers and citizens across four communities in the United States. The team will close fundamental knowledge gaps to explain (1) to what extent real-time control can improve the hydraulic and water quality performance of individual stormwater sites, (2) how to identify and overcome the barriers that public perception poses to the adoption of smart stormwater systems, and (3) how system-level interoperability can be achieved to guarantee safe and effective performance at the scale of entire communities (100s to 1000s of controlled sites). This will be achieved through three closely coupled scientific objectives, which will include testing of laboratory models of control sites, field-scale water quality studies, the formation of community advisory groups, the analysis of residential surveys in each community, and the stability analysis of system-level control algorithms under various sources of uncertainty. The approach is thus fundamentally motivated around the goal of scalability, as the results will be relevant to many communities across the United States, regardless of their size. By open-sourcing the efforts on Open-Storm.org and other public forums, the project will also support research capacity-building by reducing the overhead required by others to deploy smart and connected stormwater systems.