4

National Trends in Rural STEM Education and Workforce Development

The previous chapter outlined policies related to rural science, technology, engineering, and mathematics (STEM) education, including students’ access to K–12 STEM courses. Rural students generally have less awareness of and access to STEM programming and courses than their urban or suburban peers, and these opportunity gaps translate into disparities in achievement and aspiration as these students move through STEM education and workforce development pathways. However, there are a multitude of unrecognized assets in rural communities that can support STEM education in rural places. In this chapter, we examine the consequences for rural students of having less access to quality STEM education in K–12 schools, as well as some inherent local assets that should be recognized and nurtured to help them move beyond the challenges.

STEM ACHIEVEMENT AND ASPIRATIONS AMONG RURAL STUDENTS

Inequities in formal preK–12 STEM education structures, including fewer STEM teachers and learning opportunities, lead to gaps in both achievement and aspiration between rural and nonrural students enrolled in STEM and among rural students in different subpopulations. Differences emerge as early as kindergarten.

Achievement

Geographical gaps in STEM abilities and achievement, as measured by standardized testing, by rurality and remoteness can be observed in children as young as kindergarten age, and the gaps grow as students progress through the K–12 education system (Graham & Provost, 2012; Johnson et al., 2021; Saw & Agger, 2021). For example, a working paper analyzing National Assessment of Educational Progress (NAEP) data from 2007 to 2022 reports that, while there were generally no significant differences in mathematics scores at grades 4 and 8 between students who attended a school in rural-fringe areas and their peers in large suburban areas, those who attended school in rural-distant and rural-remote areas consistently scored lower in math than their counterparts in large suburban areas (Saw & Longstreet, 2024). The paper similarly reports that in the NAEP science assessment for 4th and 8th graders from 2009 to 2019, geographical gaps were primarily observed between rural-remote and large suburban groups, and that achievement gaps in math and science scores between rural and suburban students appeared to be wider at grade 12. These patterns of geographical achievement gaps largely reflect gaps in opportunity to learn and can also explain rural-nonrural disparities in STEM college enrollment (Saw & Agger, 2021).

Rural students outperform their town and urban peers in NAEP 8th grade math scores (Gagnon, 2022), but by 9th and 11th grade they score lower on math assessment tests compared to their suburban peers (Saw & Agger, 2021). Researchers also find U.S. regional and sociodemographic differences in assessment results (Drescher et al., 2022; Gagnon, 2022). For example, achievement on standardized assessments in 8th grade mathematics is higher in rural New England school districts compared to other U.S. regions; rural students who receive a free or reduced-price lunch perform worse on the math NAEP assessment than their rural peers who do not receive this lunch; and rural White students perform better on the NAEP math assessment than their Black, Latine, and American Indian/Alaska Native peers (Drescher et al., 2022). These disparities may reflect structural inequities rather than individual achievement deficiencies (Drescher et al., 2022).

Using data from the Early Childhood Longitudinal Study, researchers found that rural kindergarten students have lower math scores than their suburban peers but perform at the same level as students from urban school locales. The gap is larger for Asian and Native American students at rural schools, less pronounced for Black, Latine, and White students. The gap between rural and nonrural students increases over time: mathematics achievement for nonrural students improves at a faster rate than for rural students as they move from kindergarten to 8th grade (Graham & Provost, 2012). The discrepancies were not fully explainable by socioeconomic status (SES) or other observed factors in the study. This widening achievement

gap continued into high school, indicating that 9th grade students from rural and town locales scored “0.094 and 0.247 standard deviations lower than their suburban counterparts on math assessment tests” (Saw & Agger, 2021, p. 599) and that this gap widened by the end of 11th grade to 0.134 and 0.283 standard deviations.

A study of 4th grade NAEP assessments in science and math that also disaggregated students by English-language learner (ELL) status found that rural students score slightly lower than their suburban peers in math and science, and these gaps followed similar patterns for ELL and non-ELL students (Showalter et al., 2017). Interestingly, the report also found that, while averages were similar, math scores were more evenly distributed in rural communities. In nonrural areas there was more variability, with many high and low scores, whereas in rural communities scores tended to be clustered around the average. While some might interpret this to mean that rural areas are more homogeneous in terms of population characteristics such as race or SES (which in some instances may be true), research indicates that the socioeconomic achievement gap is smaller at rural schools (Stanford, 2023).

To further examine NAEP scores across different student subpopulations and locales, Rush-Marlowe (2024) looked at the percentage of students scoring “below basic” in the grade 4 math NAEP based on data from 2022. In addition to looking at performance based on student locale, Rush-Marlowe disaggregated the data by ELL status, disability status, race, and gender. The percentage of students performing below basic varied by locale,¹ with rural-remote students showing the lowest scores and large suburban areas showing the highest across almost all subgroups. Other locales fell in between on a spectrum between these two groups, with those in more rural areas trending toward lower performance, suburbs performing the best, and mixed results in urban locales.

Figure 4-1 shows the data for rural-remote and large suburban locales across the aforementioned disaggregated groups. In all instances the numbers of rural students performing “below basic” in grade 4 math are significantly greater than in large suburban areas, with the exception of Hispanic/Latine students, where a slightly lower percentage of students in rural-remote locales scored “below basic” compared to their peers in large suburban areas.

The 2022 NAEP tests showed no difference in average math scores between 4th grade students attending school in a rural-fringe area and their peers in large suburban areas (240 for both), whereas students who attended school in a rural-distant (236) or rural-remote (233) area scored somewhat lower (Saw & Longstreet, 2024). A similar pattern was observed

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¹ Throughout this chapter, Rush-Marlowe’s analysis uses the expanded National Center for Education Statistics (NCES) categories for locale, available at https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries.

in the 2022 NAEP 8th grade math assessment: There was no significant difference in average math scores between 8th grade students attending school in a rural-fringe area and their peers in large suburban areas (277 vs. 279), but those who attended school in a rural-distant (272) or rural-remote (268) area scored lower than their counterparts in large suburban areas. The gaps in math scores between rural and suburban students are wider among high school seniors: In the 2019 NAEP math test, 12th grade students attending a rural school, whether in fringe (148), distant (146), or remote (146) areas, scored lower than their counterparts attending school in a large suburban area (154; Saw & Longstreet, 2024).

Aspirations

Rural communities have lower rates of college enrollment, which may be part of the reason that rural students are less likely than their peers in urban and suburban areas to have family members or neighbors who pursued careers in STEM fields (Lakin et al., 2021). Rural schools also receive less outreach (relative to suburban and urban schools) from organizations and businesses that can provide students with exposure to STEM career options and mentorship (Harris & Hodges, 2018), and this may negatively affect students’ perceptions of the accessibility of STEM careers. One study of

rural students’ perceptions of STEM found that, even among students who believed that math and science skills were needed “everywhere,” when one student was asked where in his rural community he could study calculus he responded, “you [have] to go to a big city to find calculus” (Showalter et al., 2017, p. 40). This is problematic because barriers, real or perceived, can hamper student aspirations. Research shows that “people are less likely to translate their career interests into goals, and their goals into actions, when they perceive their efforts to be impeded by adverse environmental factors” (Lent et al., 2000, p. 38).

Motivational factors such as STEM identity and career aspirations are important individual aspects of a STEM pathway and can be strong predictors of future behavior and success. “Intent to major in STEM while in high school—a proxy of STEM career aspirations—has a larger effect on STEM major enrollment than achievement scores” (Saw & Agger, 2021, p. 596). It is important that these aspirations be formed and nurtured early in educational pathways, as studies show that exposure to STEM experiences before high school increase both student interest in STEM pathways and the likelihood that students will form intentions to pursue further education in STEM fields (Kaggwa et al., 2023). Children can recognize science as a career area and be motivated toward it as early as preschool (Dilek et al., 2020). An emerging body of evidence indicates that preK and elementary school–aged children benefit from early exposure to and engagement in STEM activities, such as engineering design applications and robotics programs, that can cultivate curiosity in scientific discovery and stimulate interest in STEM careers (Akpinar & Akgunduz, 2022; Caspi et al., 2023; Ha et al., 2023).

Few studies have examined geographical differences in STEM identity and career interest among young children, although one found that rural students have a lower science identity compared to urban students (Alhadabi, 2023). Research on STEM aspirations among rural youth is very limited and sometimes contradictory, and studies of subpopulations of rural youth are even more limited, though a case study in rural Appalachia found that young women were more likely than young men to have STEM career aspirations, at 73 percent and 54 percent, respectively (Rosecrance et al., 2019).

Two 2021 studies used the High School Longitudinal Study (HSLS) 2009 data, but defined student groups differently. Crain and Webber (2021) separated students into two categories, metropolitan and nonmetropolitan, while Saw and Agger (2021) used NCES school locales classified in the traditional four categories. Both studies found that rural students have interest in STEM careers at the same rate as their nonrural peers when they enter high school, but Saw and Agger found that a “rural-suburban gap in STEM career aspirations emerged by the end of 11th grade” (p. 598).

Crain and Webber (2021) also examined the percentage of students who expected to have a job in a STEM field by age 30. Surveys were distributed to respondents in 9th grade and again in 11th grade. The results showed that nonmetropolitan students’ belief that they would be employed in STEM grew faster than that of their peers from metropolitan areas. This seems to demonstrate that, despite barriers, rural students are interested in STEM fields and aspire to STEM careers.

HSLS data also show that 9th grade students reported their favorite subject as math or science at relatively the same rates in rural, town, urban, and suburban locales (Rush-Marlowe, 2024), although female students in rural and town locales were slightly less likely to say they were interested in pursuing STEM compared to their female peers in urban and suburban locales, with town locales being the lowest, at 10 percent, followed by rural at 14 percent, urban at 15 percent, and suburban at 16 percent. Male students in rural and town locales were also somewhat less likely to pursue STEM than their counterparts in urban and suburban locales: 29 percent of those in rural locales reported interest in a STEM major compared to 31 percent in town locales, 34 percent in suburban, and 36 percent in urban locales. Additionally, the gap between men and women is slightly more pronounced in town locales compared to urban locales: In the latter men are 2.4 times as likely to say they are interested in pursuing STEM compared to women, and in town locales men are 3.1 times as likely. In suburban and rural locales men are 2.1 times as likely to report interest in pursuing STEM compared to women (Rush-Marlowe, 2024).

Analysis of the data disaggregated by race showed that the standard error represented more than 30 percent of the estimate for Black, Latine, Native Hawaiian or Other Pacific Islander, and American Indian or Alaska Native students. This meant it was not possible to graphically show these demographics in Figure 4-2. For Asian students, the n size was too small to be reported for rural locales, but in town locales 19 percent reported an interest in pursuing a STEM major, compared to 38 percent in urban locales and 42 percent in suburban locales. Among multiracial students, 18 percent in rural locales reported interest in pursuing a STEM major, compared to 17 percent in town, 23 percent suburban, and 25 percent urban. For White students, 21 percent in rural locales reported interest compared to 23 percent in town, 27 percent in suburban, and 30 percent in urban locales. The data also indicate that White students in rural and town locales are more likely than their Asian or multiracial peers to be interested in pursuing STEM majors. Aspirations are important predictors of future student behavior and success, but are not the only important factor, and may be less predictive in rural contexts where students face unique barriers to pursue their dreams (Rush-Marlowe, 2024).

COURSE TAKING AND PERSISTENCE INTO POSTSECONDARY STEM EDUCATION

Given the lower numbers of advanced math, science, and other STEM courses offered in rural schools, it is unsurprising that rural students enroll in STEM courses at lower rates than their nonrural peers. These differences begin as early as kindergarten and continue through the end of high school (Graham & Provost, 2012). In addition, adults in rural communities tend to have lower education levels, nearly half of students in rural communities are in the low socioeconomic status category, and the community culture can discourage students from moving away from home for postsecondary educational opportunities (Peterson et al., 2015). All of these factors affect enrollment and persistence in STEM educational pathways.

STEM Course Taking in K–12

A postsecondary degree is one route to STEM workforce development, but high school graduates who attend school in a rural area earn fewer credits in STEM subjects overall and in advanced STEM courses specifically than their peers in suburban or urban locales (National Center for Education Statistics [NCES], 2024). Multiple studies have focused on rural and nonrural enrollment in STEM courses (mostly mathematics) and across grade levels. Findings show that rural students are less likely to be enrolled

in an advanced science or math course in 8th grade compared to their suburban peers (Saw & Agger, 2021) and more likely than their nonrural peers to enroll in lower-level math courses beginning in 9th grade, and that more than a third of rural students do not take a math course in their senior year, a rate much lower than their suburban peers (Anderson & Chang, 2011). Further, although students at rural, urban, and suburban schools tend to have similar enrollment rates in algebra II, fewer rural students go on to take precalculus and calculus (NCES, 2022; Table 4-1).

While much of the research discussed focuses on math, there are also gaps in the number of rural high school students enrolled in advanced science and engineering (S&E) courses (NCES, 2022). Rates of enrollment in any advanced S&E course are comparable among students in rural, urban, and suburban schools, although more students in rural areas (38.8%) enroll in advanced biology courses compared to urban (33.7%) and suburban (34.8%) schools. Table 4-2 shows gaps for rural student enrollment in chemistry, earth science, and physics.

Table 4-3 shows that enrollment rates for high school students in technology courses are fairly comparable across courses, with slightly higher enrollment in some courses for rural compared to urban students. While this may seem promising for rural students, one important factor not shown in the data is the general lack of technology courses available in different types of schools. As technology courses gain in popularity and importance for students, there should be greater effort to ensure that rural students are considered in efforts to provide more courses, especially given the known gaps in availability of broadband and other technological resources.

Rural high school students complete calculus and the combination of biology, chemistry, and physics courses at lower rates than students in

urban and suburban schools (NCES, 2022). They also earn fewer Advanced Placement (AP) and International Baccalaureate math and science credits compared to suburban students (Saw & Agger, 2021). In middle school, fewer rural students take algebra compared to their urban and suburban peers, and fewer take geometry compared to suburban middle school students (Banilower et al., 2018).

Using 2019 data from the High School Transcript Study (HSTS), Rush-Marlowe (2024) examined the percentage of K–12 students enrolled in STEM courses (any STEM course, any advanced science or engineering course, any advanced mathematics course, or any technology course) disaggregated by school locale. The rates of enrollment were fairly consistent across locales, with students in town locales marginally less likely to be enrolled in any of the first three categories and rural and town schools showing slightly higher enrollment in “any technology course” than urban and suburban locales (Figure 4-3).

Rush-Marlowe (2024) also compared the percentage of rural students enrolled in five STEM courses with the highest enrollment levels. The data reveal the largest gaps between rural-remote and large suburban locales, with the former enrolling at significantly lower rates in the five most common STEM courses: chemistry, precalculus/analysis, physics, advanced environmental/earth science, and calculus (Figure 4-4). Of the 12 STEM courses in the HSTS data, rural students had lower enrollment levels in 10 (the exceptions were advanced biology and health).

Dual Enrollment, Advanced Placement, and Career and Technical Education

Dual enrollment, AP courses, and Career and Technical Education (CTE) all offer rural students opportunities to pursue STEM courses at similar rates to urban and suburban students, but there are unique challenges for rural students in terms of access to and completion of these courses. Dual enrollment programs enable high school students to earn postsecondary credit and are available in about 90 percent of all rural high schools (NCES, 2020). Rural high school juniors and seniors are more likely to take dual enrollment courses than students in other locales (Showalter et al., 2019). This is despite the fact that rural districts face greater challenges than their counterparts in other locales in finding qualified dual enrollment instructors and providing transportation for students enrolled in such programs (Zinth, 2014). In most states, dual enrollment instructors need to meet requirements such as a master’s degree or the same qualifications as faculty in the partner postsecondary institution. In most cases, dual enrollment courses are offered online or at the postsecondary institution campuses (Thomas et al., 2013).

As noted in Chapter 3, rural schools offer fewer AP courses than those in urban and suburban areas (Mann et al., 2017): 73 percent of rural schools offer at least one AP course in any subject, compared to more than 92 percent of suburban and urban schools. Further, only 62 percent of students in rural schools had access to AP STEM courses and just 11 percent of them took the corresponding exam, a marked difference between both urban and suburban schools (Mann et al., 2017).

Although rural students had fewer opportunities to take STEM courses and engage in STEM out-of-school learning opportunities, data from NCES (2023) indicate that they were more likely to take CTE courses compared to urban and suburban students. CTE programs are designed to help students develop technical, academic, and workforce skills that can be applied to employment and postsecondary education. In 2019, 91.6 percent of rural high school graduates had taken any CTE courses, higher than students in towns (91.3%), suburban areas (83%), and cities (79.6%; NCES, 2023; Table 4-4). The rural students were more likely to earn CTE credits in information technology (34% compared with 29% nationally) and agriculture, food, and natural resources (25% compared with 11% nationally; NCES, 2023).

One common way rural students attend CTE courses is through area technical centers, which serve students from multiple institutions at the same time (Advance CTE, 2017), provide diverse course offerings, and can make up for limited availability at a student’s home institution. While these centers are not available in all states, they have the potential to build strong partnerships with business and industry, which could ultimately lead to more STEM-related courses and work in rural communities. Partnerships that provide experiential learning, including internships, are discussed in Chapter 5.

Another component critical to STEM education and workforce pathways is ensuring that students graduate academically ready for both college and careers (Southern Regional Education Board, 2015). This is a challenge on multiple levels, including in terms of expectations, availability of quality teachers and counselors, limited resources, and course offerings (Peterson et al., 2015). In advising rural students about STEM college and career pathways, school counselors are hampered by limited STEM career advising resources, a lack of local STEM role models (i.e., individuals known to the students who engage in STEM disciplines in life and work in ways that inspire and inform those students), and inadequate financial resources and learning activities for students to explore STEM college majors and careers (Grimes et al., 2019).

Enrollment and Persistence in Postsecondary Education

Rural students graduate from high school at higher rates than their peers from nonrural areas, but they are less likely to pursue postsecondary education (Koricich et al., 2018); in 2022 54.6 percent of rural high school

graduates immediately enrolled in college compared to 63.7 percent of suburban and 58.6 percent of urban high school graduates (Postsecondary National Policy Institute, 2024). Many rural students who do decide to attend college are first-generation students who did not receive sufficient college preparation in high school and are unfamiliar with key tasks like the application process and how to finance a college education (Bright, 2018; Scott et al., 2016). In rural communities, only 21 percent of residents have a bachelor’s degree, which, combined with fewer rural teachers and school counselors, can contribute to misunderstandings about the benefits and expectations of pursuing higher education (Chambers & Freeman, 2020; McNamee, 2019).

A minority—between one fourth and one third—of rural students attending two-year colleges transfer to a four-year institution, and almost half (49%) of rural community college students who transfer ultimately earn a bachelor’s degree² (McNamee & Ganss, 2023).

For the class of 2022, the immediate college enrollment rate of rural high school graduates was 54.6 percent, which was lower compared to their counterparts from urban (58.6%) and suburban (63.7%) high schools (National Student Clearinghouse, 2023). Rural students also enroll in postsecondary STEM degree programs at lower rates than suburban students (12.6% vs. 16.6%; Saw & Agger, 2021).

Two case studies (Felder et al., 1994; Versypt & Versypt, 2013) focused on rural student enrollment in chemical engineering programs. The first, conducted at North Carolina State University, found that students from rural high schools had lower GPAs and persisted and graduated from chemical engineering programs at significantly lower rates than their urban and suburban peers (Felder et al., 1994). The second case study looked at enrollment in chemical engineering majors at six universities in Illinois and Kansas and found that none of the six institutions met or exceeded proportional parity based on students’ geographic background, and three of the six did not have a single student from a rural high school enrolled in a chemical engineering program (Versypt & Versypt, 2013).

An additional case study (Darrah et al., 2023) took a unique approach to defining rurality to examine how many rural and nonrural students declared STEM majors and graduated with a STEM degree within five years from an (unnamed) large public university in West Virginia. To define rurality the authors created county-level classifications that included high school enrollment, percentage of rural high schools (based on NCES locale codes), median high school size, number of libraries, and number of museums, among other factors. This allowed them to reclassify their area of study into three locale codes, of which locale code 3 was the “most rural:” defined as having the fewest resources, smallest high schools, and highest percentage of rural high schools. As shown in other research, locale code 3 had the highest high school

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² https://nscresearchcenter.org/tracking-transfer/

graduation rates but the lowest college attendance rates. This study also found that these students had the highest percentage of STEM majors but the lowest levels of STEM graduation within five years (Darrah et al., 2023).

At the national level, Saw and Agger (2021) found geographic disparities in STEM enrollment between rural and nonrural students, with 16.6 percent of suburban students reported enrolling in a postsecondary STEM degree program at either a 2- or 4-year college, as opposed to 12.6 percent and 13.1 percent of rural and small-town students, respectively. Other research looked at nonmetropolitan student persistence in STEM programs and found that nonmetropolitan locale was not a significant factor in whether a student persisted in a STEM major (Crain & Webber, 2021), indicating that the definitions used in rural educational research can affect both the results found and their implications.

Disaggregated by locale and no other student characteristics, enrollment data for postsecondary STEM majors differ somewhat (Rush-Marlowe, 2024). Rural locales actually had the highest rates of STEM enrollment, at 47.9 percent, followed by suburban at 45.4 percent and urban at 43.5 percent; students from high schools in towns had the lowest rates of STEM majors, at 37.7 percent. It is unclear why rural locales are so high in this instance and why there is such a large discrepancy between outcomes for rural and town students. Examination of the most common STEM majors by locale showed that students from rural high schools pursued almost every specific STEM major at equivalent or lower rates than their peers from other locales, with the exception of healthcare fields. It is possible that the large number of students from rural locales pursuing health care are skewing the rest of the data, as can be seen in Figure 4-5.

To better understand postsecondary STEM attainment among rural students, Rush-Marlowe (2024) used the 2015–2016 Baccalaureate and Beyond data to examine the percentage of students who attained a bachelor’s degree in a STEM field within six years of enrolling in an undergraduate degree program, disaggregated by high school locale and with locale data broken out into the 12 locale groups rather than the condensed four groups. As shown in Figure 4-6 and Table 4-5, students in all three town locales have the lowest attainment rates after enrolling, followed by rural-distant and then urban. Students from suburban, rural-remote, and rural-fringe locales had similar levels of attainment. Students from town fringe locales had the lowest levels of attainment, at just over 20 percent, and midsize suburban locales had the highest levels, just over 60 percent. Thus, while the rate of enrolling in postsecondary STEM degree programs is lower for rural students (Saw & Agger, 2021), persistence to degree after enrolling is similar across some rural, suburban, and urban populations (Rush-Marlowe, 2024).³

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³ Because of small cell size limitations and error size in estimates, the data could not be disaggregated by gender, race/ethnicity, or other student characteristics.

likely to be represented in STEM careers. A recent National Science Foundation report looks at the geographic distribution of the STEM workforce by education background, but data are displayed only at the state level (Taylor & Arbeit, 2024). All states have at least some rural areas and some have higher levels of rural population than others, so discussing state-level data is not particularly meaningful in this context.

To develop a preliminary understanding of the available data on rural students in the STEM workforce, Rush-Marlowe (2024) analyzed the HSLS, which includes data on employment in STEM fields in students’ first job after high school. Looking at the data by locale alone did not reveal significant differences between rural and other areas. When disaggregated by race and ethnicity, some groups (Native Hawaiian or Other Pacific Islander, American Indian or Alaska Native, and multiracial students) did not have large enough n sizes to be reliable, but the data demonstrated gaps between Asian, Black, Latine, and White students across locales. Estimates for Asian students from rural locales were too small to be reliable, but Asian students from town locale high schools were much less likely to be employed in STEM in their first jobs compared to their peers from suburban and urban locales: 96 percent of Asian students from a town high school were not employed in STEM after high school, compared to 85 percent in suburbs and 87 percent in urban locales. For Black students, rates were similar for rural, town, and suburban locales: 97 percent were not employed in STEM, compared to 93 percent of their peers from urban locales. For Latine students, 96 percent of those from rural locales were not in STEM jobs, compared to 99 percent from town locales, 93 percent from suburban, and 92 percent from urban locales. Among White students, 96 percent of those from rural locales were not employed in STEM fields, compared to 95 percent in town and suburban locales and 93 percent in urban locales. These data show that, across many racial groups, students from rural high schools are less likely to be employed in STEM than their peers in urban and suburban locales after high school graduation.

Because many STEM professions require more than a high school diploma, Rush-Marlowe (2024) also examined data from the Baccalaureate and Beyond survey, which asks students if their most recent job within four years of their bachelor’s degree was in a STEM field. Disaggregating by both locale and race/ethnicity produced unreliable estimates, but students from “town-distant” high schools were the least likely to be employed in a STEM job (22.9%), rural-remote students were slightly more likely to be employed in STEM (23.8%), and students from midsize suburban locales were the most likely (29.2%). Table 4-6 shows the percentage of students employed in a STEM occupation within four years of earning their bachelor’s degree, broken out by locale. However, these analyses do not account for STEM jobs that require more than a high school diploma but less than a bachelor’s degree (as described in Chapter 1).

TABLE 4-6 Percentage of College Graduates Employed in STEM, by Locale, 2016

SOURCE: Committee generated from Baccalaureate and Beyond (B&B:16/20) data (Henderson et al., 2022).

ASSETS OF RURAL COMMUNITIES RELATED TO STEM EDUCATION AND WORKFORCE DEVELOPMENT

While data indicate that rural communities face many challenges in providing STEM education and workforce development opportunities, leading to achievement and aspiration gaps, these communities also have assets that can enrich and promote STEM learning, such as place-based learning and strong community ties, as will be elaborated in Chapter 5. For example, many rural communities have strong historical and current ties to specific industries such as agriculture, fishing, timber, or mining. From a young age, children growing up in these communities often gain firsthand experiences in these trades, which can give them deep applied knowledge in science, technology, math, and engineering and promote interest in pursuing STEM-related careers. They can also gain knowledge and skills relevant to natural resources. The lived experiences and accumulated insight of rural residents, including those from Indigenous and tribal communities, are untapped assets of expertise that can advance natural resource preservation and conservation work.

The central social, cultural, and economic role that rural schools often hold in their communities (Schafft, 2016) helps students see the relevance of science and engineering to their own lives and futures, by fostering a stronger connection to the subject matter. In addition, due to small class

sizes and increased interactions with families, rural teachers can be seen as the “faces” of their rural school (Hammack et al., 2023) and develop close relationships with their students that result in more individualized instruction and improved student behavior (Tran et al., 2020). In addition, school-community partnerships are often enhanced in rural areas (Schafft, 2016), and community-based programs can leverage local expertise and environmental features such as farms, forests, and rivers to create meaningful learning experiences (Avery, 2013).

Thus, rural areas provide a rich context for learning science and engineering, and with access to the outdoors or work in agricultural industries such as farming or fishing many rural students naturally develop their engineering and science skills in their daily lives (Avery, 2013). Given connections to STEM content in these forms, opportunities for place-based education in rural areas abound and such learning can increase students’ access, engagement, and achievement in science content (Avery, 2013). Moreover, using place to educate creates an informed citizenry ready to advocate for their rural home and its relationship in a global context (Eppley, 2017) and prepares rural youth for local STEM employment opportunities (Starrett et al., 2022).

SUMMARY AND CONCLUSION

This chapter has examined the consequences for rural students of less access to quality STEM education in K–12 schools. Because of opportunity gaps in this education, students in rural areas overall have lower achievement in STEM courses and fewer aspirations to enter a STEM career or college major. They are also less likely to enroll and persist in STEM courses throughout their educational pathway. Despite these challenges, the assets of rural communities support STEM education and workforce development.

Conclusion 4-1: Many rural students lack access to STEM coursework (e.g., computer science classes, Advanced Placement and International Baccalaureate courses in math) and programs (e.g., Talented and Gifted and Career and Technical Education [CTE] programs, dual enrollment, and third- and fourth-year CTE courses) that can better prepare them to pursue diverse STEM-related education and careers. These disparities in STEM learning opportunities translate into STEM achievement and aspiration gaps between rural and nonrural students, and these gaps grow as students move through K–12 schooling.

Chapter 5 further explains how the assets of rural communities can be leveraged to provide engaging and effective STEM learning experiences.

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