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For the growing worldwide economy to be successful, science, technology, engineering, or math (STEM) workers are needed. Once recruited to pursue a STEM major, the challenge is keeping these students on track. A large diverse workforce is needed in these fields, but past research has shown students from rural settings are disadvantaged when attending college. It is difficult to look at differences of rural vs. urban to determine whether these settings have any impact on a students’ decisions to declare and persist in a STEM major. Many states have large portions considered rural, Maine (61.3 percent), Vermont (61.1 percent), West Virginia (51.3 percent) (World Population Review, 2022). In states like these, it is hard to differentiate rural and urban settings since much of the state is rural. This study attempts to look at locales in a way that classifies them, not by population or proximity to urban settings, but by other factors that may affect students related to STEM persistence. This case study is the state of West Virginia and cluster analysis is used to develop Locale Codes (LC) to differentiate counties based on a variety of factors, including declaring and persisting in a STEM major. The findings show some counties have a higher percentage of students declaring STEM, but these students are less successful in college than other counties that have proportionally fewer students declaring STEM. The factors related to the locale that contribute to these differences are examined. 

For the growing worldwide economy to be successful, science, technology, engineering,or math (STEM) workers are needed. Once recruited to pursue a STEM major, the challenge is keeping these students on track. A large diverse workforce is needed in these fields, but past research has shown students from rural settings are disadvantaged when attending college. It is difficult to look at differences of rural vs. urban to determine whether these settings have any impact on a students’ decisions to declare and persist in a STEM major. Many states have large portions considered rural, Maine (61.3 percent), Vermont (61.1 percent), West Virginia (51.3 percent) (World Population Review, 2022). In states like these, it is hard to differentiate rural and urban settings since much of the state is rural. This study attempts to look at locales in a way that classifies them, not by population or proximity to urban settings, but by other factors that may affect students related to STEM persistence. This case study is the state of West Virginia and cluster analysis is used to develop Locale Codes (LC) to differentiate counties based on a variety of factors, including declaring and persisting in a STEM major. The findings show some counties have a higher percentage of students declaring STEM, but these students are less successful in college than other counties that have proportionally fewer students declaring STEM. The factors related to the locale that contribute to these differences are examined. 

Abstract The First2 Network is a collection of people from K–12, higher education, government, and industry who are coming together to ensure that students of West Virginia, a rural Appalachian state, will be prepared to choose science, technology, engineering, and mathematics (STEM) majors and persist in them. This project—funded by the National Science Foundation—combines many features, including semi-annual conferences, structured working groups, summer immersive experiences for students, a student ambassador program, and network improvement communities. The growth of the First2 Network is vital to make sure that these activities and programs are disseminated and sustained statewide. This article uses social network analysis to examine participation of people around the state during the first three years of the project. Findings indicate that the network is growing in number of people and in strength of connections. Network leadership members are playing key roles in the network, and student participants who persist in their STEM majors have stronger ties to the network. Social network indicators suggest that the network has manifested positive changes in the first three years of the project, which will lead to increased communication and collaboration among state agencies related to STEM persistence within the state.