Abstract
Although research has investigated teacher labor markets over decades, there remains a notable gap in our understanding of staffing challenges in rural schools. Using longitudinal vacancy and application data in Wisconsin, we explore teachers’ job application and hiring patterns between rural and non-rural schools and within rural locales. Our investigation revealed that as the proximity to urban areas decreases, the applicant pool for rural positions diminishes, with applicants originating from more distant locations. Female applicants, candidates of Color, and individuals with elevated qualifications demonstrated a reduced inclination to seek employment in rural schools. Conversely, individuals with prior rural teaching experience and graduates of rural-based teacher preparation programs exhibited substantial proclivities toward both applying for and securing positions within rural educational settings. Our findings have significant implications for policymakers endeavoring to design and implement targeted programs for addressing the persistent staffing challenges confronting rural schools.
Scholars have underscored the importance of recognizing teacher staffing challenges through the lenses of subject diversity, geographical location, policy implications, and school typology (Edwards et al., 2022; Guarino et al., 2006, 2011). For example, educational institutions serving high-poverty communities and historically marginalized groups often face significant challenges in recruiting and retaining qualified teachers. As a result, students in these settings frequently receive instruction from educators who may have less experience, lack certification, or teach outside their areas of expertise (Evans & Acosta, 2023; Jackson, 2009; Lankford et al., 2002). Nevertheless, it is important to note that the majority of research in this domain has predominantly focused on urbanized regions (Goldhaber et al., 2020; Rodriguez et al., 2023). This emphasis can be attributed partly to the challenges associated with acquiring comprehensive data and the relatively limited attention devoted to rural educational settings, which has created a substantial void in our understanding of the unique staffing challenges confronting rural communities (Yang et al., 2021).
In recent research, scholars have made significant contributions to our understanding of labor markets for rural teachers. Goldhaber et al. (2020) conducted a study focusing on rural schools in California, revealing that these schools are more likely to grapple with staffing difficulties compared to their non-rural counterparts. These challenges include higher rates of teacher vacancies and a greater reliance on emergency credentialed teachers. Goff and Bruecker (2017) found that rural student teaching experiences and the proximity of rural districts to educator preparation programs (EPPs) can enhance applicants’ interest in rural vacancies. In a national context, Ingersoll and Tran (2023) also shed light on the formidable staffing obstacles that rural schools across the United States encounter. Meanwhile, Tran et al. (2023) underscored the crucial role of school principals and administrative support in mitigating teacher turnover within rural schools. Recognizing the urgency of addressing these issues, the University Council for Educational Administration (UCEA, 2018) issued a compelling recommendation in 2018, advocating for the implementation of suitable incentives to stabilize the rural educator workforce.
Despite the wealth of insights gained from prior work, it is important to note that rural teacher labor markets have not received the same level of attention in both scholarly inquiry and policy discourse. This relative neglect is evident, as Rhinesmith et al. (2023) reviewed, in the limited exploration of the challenges associated with attracting and retaining teachers in remote and isolated geographical regions. Consequently, there exists a compelling need to refocus scholarly and policy attention on this vital aspect of education, as highlighted by Burton et al. (2013).
This study builds on previous studies by exploring the application and hiring patterns of teachers across rural communities. We employed statewide job vacancy and application information alongside administrative staffing records in Wisconsin from 2014 and 2016 to examine the rural teacher labor market comprehensively. Specifically, this study investigates not only those who ultimately secured teaching positions but also the demographics and attributes of those who applied. This dual perspective enables us to gain deeper insights into the composition of the applicant pool in rural areas and provides valuable context for understanding the dynamics within the rural teacher labor market. Notably, this study expands upon Goff and Bruecker’s (2017) work 1 by adopting a longitudinal approach and examining how application and applicant factors influence actual hiring outcomes. By advancing the scope of data, the depth of analysis, and incorporating hiring information, this study provides a more comprehensive understanding of the rural teacher labor market, ultimately contributing to workforce stability in rural schools.
Although the existing research notes the challenges faced by rural schools in recruiting and retaining educators when compared to their more affluent suburban counterparts, there is a noticeable scarcity of empirical evidence exploring the relationship between school locations and teachers’ patterns of job applications and hiring outcomes. Given that the distribution of teachers across schools is influenced by both supply and demand sides (Engel et al., 2014), a similar trend observed in other countries as well (Luschei et al., 2013), it is essential to examine the supply side (e.g., applicant decisions to apply for rural positions) and demand side (e.g., school hiring preferences) in rural teacher labor markets. In addition, research on rural educators tends to oversimplify rural schools as a homogeneous community, masking considerable variation in student composition, teacher qualifications, and school structure (Holme et al., 2018; Tieken, 2017). Notably, the degree of proximity to urbanized areas is intricately linked to the accessibility of educational resources, implying the existence of nuanced and consequential variations in the labor dynamics experienced by rural teachers, contingent upon their geographic contexts (Yang et al., 2021). Policymakers have been increasingly trying to address staffing challenges in rural schools through measures such as emergency and probationary certificates (Goldhaber et al., 2020) and the implementation of a 4-day school week (Anglum & Park, 2021). Therefore, our examination of application and hiring patterns in rural educational settings not only facilitates a deeper comprehension of the labor dynamics among teacher applicants across diverse rural communities but also furnishes evidence-based insights that can inform policy decisions tailored to the unique needs and challenges encountered in rural areas (Johnson et al., 2021). Our research questions are as follows:
What are the differences in job application patterns between rural schools and other locations?
What are the characteristics of the applicants who apply to rural schools?
What individual characteristics relate to being hired in rural schools?
We found sizable differences in the application and hiring patterns between rural and non-rural schools and within rural locales. Rural schools receive a diminished volume of job applications, attract candidates from more distant locations, and typically encounter a higher prevalence of novice applicants in comparison to other geographical areas, notably suburban districts. This trend was especially noticeable in rural schools located at greater distances from urban areas. This pattern remained consistent even when examining subjects with recruitment challenges, such as mathematics and SPED. It is worth noting that female applicants, people from diverse racial or ethnic backgrounds, and those with higher qualifications, including advanced degrees, high grade point averages (GPAs), and graduation from selective colleges, were less inclined to submit job applications to rural schools. Conversely, candidates who had completed teacher preparation programs (TPPs) in rural or town settings, as well as those with previous teaching experience in rural contexts, were more likely to seek employment in rural educational settings. Furthermore, our findings show that female and novice applicants, candidates with advanced degrees and rural teaching experience, and applicants originating from the same school districts and rural TPPs were more likely to be hired in rural schools. These findings are consistent with the conclusions drawn by Goldhaber et al. (2020), who state that “the mere geographical placement of rural schools, situated far from urban centers, likely contributes significantly to the staffing challenges faced by schools in rural districts” (p. 9). Our study contributes to the existing literature by shedding light on differential patterns of job applications and hiring outcomes across various school district locales.
Literature Review
Rurality
The word “rural” has often been narrowly defined, primarily as a negation of “urban” (Gagnon & Mattingly, 2015b; Miller, 2013). This urban-centric perspective is notably reflected in the criteria employed by the U.S. Census Bureau (2011), where population thresholds serve as the basis for categorizing urban cities, clusters, and areas, with everything falling outside the urban classification being automatically designated as rural. Consequently, rural areas are characterized not by inherent rural attributes but rather by the absence of defining urban characteristics.
Addressing this gap, the regional planning literature has suggested that rural areas could be more appropriately categorized based on “natural features and economic use” (Miller, 2013). However, within the educational research community, there exists a notable dearth of frameworks for assessing or delineating rurality (Ryan et al., 2019), and the existing body of literature lacks consensus regarding the defining characteristics that distinguish rural from other areas (Nelson et al., 2014; Thiede et al., 2018).
Despite the prevailing definition of rural as simply non-urban, prior research has illuminated the substantial diversity that exists among schools and communities categorized as rural. Scholars have underscored that rural communities are far from homogeneous, given the disparities both between and within the communities. In fact, the definition of rural should not be confined solely to criteria such as population density and distance, a limitation noted by Longhurst (2021). This approach fails to account for the nuanced realities of rural areas, which are often shaped by ongoing industrial transformations and rapid demographic shifts (Smith, 2007). Consequently, using such narrow parameters has been criticized for its tendency to oversimplify and homogenize the complex diversity of rural communities.
To address this diversity, the Common Core of Data (CCD), compiled by the National Center for Education Statistics (NCES) following U.S. Census definitions, has classified local education agencies into three distinct categories—rural fringe, rural distant, and rural remote—based on their proximity to urbanized areas (Geverdt, 2015). This categorization system was instrumental in highlighting the considerable differences among students, schools, and school districts within these rural categories. For instance, Greenough and Nelson (2015) revealed that over three-fifths of students in rural schools fall under the rural fringe category, indicating that a majority of rural district students reside within 2.5 miles of a larger town or 5 miles of an urbanized area. Furthermore, Greenough and Nelson (2015) demonstrated substantial discrepancies among these rural school categories concerning remoteness, student enrollment size, racial and ethnic composition, poverty rates, and enrollment growth or decline.
Koziol et al. (2015) echoed the importance of recognizing this internal diversity within the broader category of rural schools, emphasizing the need to carefully define and operationalize rural in quantitative research (Longhurst, 2021). Indeed, the absence of a universally accepted definition for what constitutes a rural context poses a formidable challenge due to the multifaceted and evolving nature of rural communities, schools, and student populations. This complexity underscores the necessity of nuanced approaches when studying and addressing issues related to rural education. Nonetheless, the category of the NCES is commonly used in public education data and serves as the most practical way to define rural and differentiate within rural areas (Showalter et al., 2023).
Rural School Teacher Labor Market
The teacher labor market literature has extensively explored the substantial disparities in teacher qualifications across various districts and schools (Boyd et al., 2005). Findings within this body of research indicate that teachers who serve students from low-income backgrounds and students of diverse racial and ethnic backgrounds tend to have higher probabilities of being inexperienced (Bacolod, 2007; Lankford et al., 2002), lacking proper certification (Maier & Youngs, 2009), and teaching subjects outside their field of expertise (Ingersoll, 2003). Additionally, studies have observed a tendency among teachers to depart from low-performing, economically disadvantaged schools (Cowen et al., 2012) and seek employment in schools with fewer minority and disadvantaged students or those with higher-achieving student populations (Boyd et al., 2005; Scafidi et al., 2007). Furthermore, it has been noted that teachers who switch schools often possess stronger qualifications compared to those who remain in their current positions (Boyd et al., 2005; Goldhaber et al., 2007), thereby leading to a situation where disadvantaged school districts are left with less qualified and less experienced educators (Cowen et al., 2012).
A growing body of research has provided compelling evidence that various school and district attributes play a pivotal role in shaping teachers’ decisions as they navigate the labor market and make choices about where to pursue employment (Cannata, 2010; Engel & Cannata, 2015). Notably, teachers exhibit distinct preferences when considering job applications based on the geographic location of the school and the characteristics of its student body (Engel et al., 2014; Imazeki, 2005). For instance, Engel et al. (2014), in a study analyzing data on job fair applications in Chicago, demonstrated that, even after accounting for school-specific factors, the geographic proximity of a school remains a significant predictor of the number of applications received from prospective teachers. Goff and Bruecker (2017) also noted that teachers tend to show averse to rural posting. These findings underscore the inclination of teachers to seek positions close to their places of residence, emphasizing the importance of location in their employment decisions. Furthermore, as highlighted in previous research conducted in New York City (Lankford et al., 2002), there is a consistent pattern whereby urban schools tend to employ teachers with less experience and no certifications, compared to their suburban counterparts. This leads to a concerning situation where students from racially diverse backgrounds and those from low-income households are more likely to be instructed by teachers with less experience and lower levels of expertise over successive academic years, perpetuating educational disparities.
This pattern of less qualified teachers in urban schools is not unique to New York City but is observed across various states, including Texas (Hanushek et al., 2004), Wisconsin (Imazeki, 2005), and Illinois (DeAngelis & Presley, 2011; Jacob, 2007). Moreover, though limited, rigorous studies have leveraged work history and application datasets to provide valuable insights into teacher labor markets. Previous research has revealed that employers tend to favor teacher applicants with stronger pre-service qualifications (Boyd et al., 2011) and those who reside close to the school (Boyd et al., 2013). Additionally, studies have delved into application datasets to gain a more comprehensive understanding of the teacher hiring process, exploring whether screening tools can enhance teacher recruitment and subsequent job performance (Bruno & Strunk, 2019; Chi & Lenard, 2023; Goldhaber et al., 2017; Jacob et al., 2018). D’Amico et al. (2017) contributed to this body of knowledge by presenting evidence of discriminatory hiring practices. Their research demonstrated that Black teacher applicants were significantly less likely to receive job offers compared to their White counterparts, highlighting issues of equity in the teacher hiring process. Disturbingly, research also revealed that rural schools serving a large portion of Black students experience higher teacher turnover. Black teachers in rural areas tend to have higher mobility rates and are more likely to leave rural communities for teaching positions in urban or suburban areas (Williams et al., 2021).
In a similar vein, Goldhaber et al. (2020) conducted a study using application data, concluding that rural school districts face considerably higher staffing challenges and tend to hire a larger number of emergency-credentialed teachers in comparison to districts located in other geographic areas. These findings have raised concerns about the impact of teacher preferences for where to apply or work, suggesting that certain districts may endure persistent recruiting difficulties, ultimately detrimentally affecting student learning outcomes (Ronfeldt et al., 2013). While the discussion has largely been situated in urban and suburban school districts, recruiting and retaining high-quality teachers in rural schools is a nationwide issue (Beesley et al., 2008; Ingersoll & Tran, 2023; UCEA, 2018).
Schools and districts in rural areas are less likely to have highly qualified teachers than their urban and suburban counterparts. Specifically, rural school teachers are, on average, less likely to be graduates from top-ranked colleges (Gibbs, 2000; Goodpaster et al., 2012; Monk, 2007) and are more likely to be novice teachers (Gagnon & Mattingly, 2015a; Miller, 2012). Miller (2012) conducted an extensive analysis of 20 years’ worth of data from New York State and discovered that rural schools exhibit a substantial reliance on inexperienced teachers to address staffing vacancies, surpassing the reliance observed in schools situated in other community types. Specifically, approximately 30% of the vacant positions in rural schools are filled by novice teachers. This prevalence of novice educators places added demand on induction services and amplifies the associated burdens and costs experienced by rural schools. Furthermore, research by Gagnon and Mattingly (2015a) has consistently indicated that rural districts exhibit higher concentrations of novice teachers in comparison to all other school locales nationwide.
While experiencing many of the same staffing challenges as their urban and suburban counterparts, rural schools have additional obstacles in the teacher labor market, particularly due to geographical isolation (Curran & Kitchin, 2019). Given studies have indicated a preference among teachers for working in the geographic regions where they grew up (Boyd et al., 2005; Reininger, 2012), it follows that teacher supply in rural areas faces constraints due to the relatively smaller pool of potential educators. The situation is compounded by the fact that approximately half of the teachers who embark on their careers in rural schools ultimately opt to transfer to different schools or exit the teaching profession altogether within the initial 3 years of their teaching journey. This phenomenon diverts valuable efforts and resources away from other critical educational needs in rural districts (Miller, 2012). In addition to these challenges, it is worth noting that rural schools and remote school districts tend to offer lower salaries to teachers (Monk, 2007). According to the National Rural Education Association’s report, Why Rural Matters 2023: Centering Equity and Opportunity, the average adjusted salary for teachers in rural districts is $76,374. While this figure reflects some improvement, it still lags behind the $81,645 average salary in non-rural districts, even after adjusting for local wage differences. This pay gap highlights the ongoing financial difficulties rural schools face in attracting and retaining qualified educators. This further exacerbates the already arduous circumstances confronting rural schools.
Several states, including California, New York, Utah, and Wisconsin, have started to ease their licensing rules to alleviate teacher shortage problems in disadvantaged schools and districts (Felton, 2016; Goldhaber et al., 2020). In 2016, New York dropped the requirement for teachers to pass New York’s certification exams for more out-of-state educators to get licensed (Felton, 2016). Utah allowed college graduates to attain a teaching license without practice teaching or experience (Knox, 2016). Similarly, based in part on claims that rural districts were suffering from teacher shortages, Wisconsin passed legislation to loosen the certification requirements for some teaching positions (Beck, 2016). These policies assume that current license requirements negatively impact the applicant pool in rural schools and that making such requirements less restrictive helps attract potential teachers. Nonetheless, it is essential to acknowledge the limited empirical evidence available to validate the existence or magnitude of a labor supply issue in rural schools when compared to other geographical areas. In certain instances, such as in Wisconsin, policy solutions have been proposed before a thorough and meticulous diagnosis of the staffing problem has been undertaken.
Despite the increasing attention directed toward the distinctive staffing challenges encountered by rural schools, our current knowledge remains limited regarding the variations in application preferences and hiring patterns across different school locales and within rural communities. This knowledge gap is, in part, due to our incomplete understanding of the composition of the teacher labor supply pool. For instance, when examining administrative staffing records, researchers can infer that every individual who changed teaching positions, especially between school districts, was actively part of the labor pool. However, it is crucial to recognize that these individuals did not express equal interest in all available positions and, as a result, did not apply to every vacant teaching position. Similarly, from the demand side, schools did not hire teachers from the entire pool of available applicants but rather selected candidates exclusively from those who had submitted applications for specific positions. Consequently, in many studies focusing on teacher labor markets, essential counterfactual information, such as who applied for particular positions and potentially could have been hired, is either absent or relies on unrealistic assumptions. Our research seeks to address this gap in knowledge by investigating the patterns of teacher job applications and hiring across various rural communities. Through this exploration, we aim to gain a deeper understanding of the dynamic nature of teacher labor markets and provide policymakers with valuable insights for making informed decisions that are attuned to the unique needs and challenges faced by rural schools.
Method
Wisconsin Context
Wisconsin has a population of about 5.8 million and 30% of the population lives in rural areas accounting for 97% of the state’s land area (Jones & Ewald, 2017). More than half of the school districts are classified as rural districts (234 out of 424), and 25% of teachers and 23% of students in the state are in rural schools (Yang et al., 2021). In Wisconsin, approximately 53% of school districts are classified as rural, distributed across various geographic categories: 13% as rural fringe, 24% as rural distant, and 16% as rural remote (Guarino et al., 2006). This diverse distribution highlights the varied geographic settings within the state’s educational landscape, each presenting unique challenges and opportunities for educational delivery and resource allocation. The student composition is comparable to the national statistic that one in five students attend rural schools (Showalter et al., 2023). In addition, Wisconsin’s staffing challenges align with experiences faced by other states and reflect broader national trends. Recent statistics underscore the severity of the issue, with one in every three new teachers leaving the profession within their first 5 years (Kammerud et al., 2023). Furthermore, data reveal that the average annual teacher turnover rate from 2009 to 2023 stood at 11.5% (Hamidu, 2023), highlighting the persistent nature of this concern in the state.
While Wisconsin’s educational context—encompassing student composition, staff, expenditures, and policy—may differ from other states (Showalter et al., 2023), it shares similarities with many Midwest and Southern states, where over half of school districts are rural (Glander, 2016). A key commonality is the widespread issue of teacher shortages in rural areas, a challenge observed nationwide. Studying labor dynamics in Wisconsin’s rural schools provides valuable insights into the spatial inequities and challenges faced by these communities. However, the high proportion of rural districts and the predominantly White student population in Wisconsin reflect regional trends in the Midwest but differ from some Southern states, where the number of Black, Hispanic, and other minority students is rising. Caution should, therefore, be exercised in generalizing these findings and interpreting their broader implications.
Wisconsin Education Career Access Network Data
Our study used statewide vacancy and application data spanning from 2014 to 2016, sourced from the Wisconsin Education Career Access Network (WECAN), an online platform where school districts in Wisconsin post teacher vacancies and candidates submit their applications. Educators can use the platform to search for and apply to jobs, uploading necessary application materials such as teaching statements, certifications, and educational/work background information. With all documents uploaded to WECAN, applicants can efficiently apply to multiple positions, saving time and energy. While some districts may require additional documents, applying through this centralized platform is generally easier than submitting applications to individual districts or using different platforms.
Since WECAN is widely used by most districts and educators as their primary job market platform, the data encompass a comprehensive range of job market information, covering both supply-side factors such as years of teaching experience and certification records, as well as demand-side factors including vacancy descriptions and application numbers. Given that 95.3% of Wisconsin school districts utilized the WECAN system for posting job vacancies, our dataset effectively captures the majority of educator job market activities within the state.
Table 1 illustrates the demographics of students, teachers, schools, and communities across locales in Wisconsin. Rural districts have the second largest portion of low-achieving and high-poverty students after urban districts, while having the lowest portion of students of Color and English language learner students. The number of teachers in rural districts is less than half that in town districts, though pupil–teacher ratio is the lowest among four locales. The number of schools in a rural district is roughly three, suggesting many rural districts in Wisconsin are organized with one elementary, middle, and high school each. Rural communities show the lowest proportion of the population with college degree or above and the second highest poverty rates following urban communities. These characteristics provide insights of how our findings are contextualized in rural Wisconsin and further translated to other states and rural contexts. It is also worth noting that the locale distributions of the school districts using the WECAN system are quite similar to the general distribution of the total districts, suggesting that the over- or under-representation of rural districts in the missing group is not a major concern.
Characteristics of School Districts Across Locales in Wisconsin
Note. Means and standard deviations are for the year 2016. Standard deviations are in parenthesis. Data sources are the Common Core Data and the SEDA. Student achievement is standardized score from third grade through eighth grade across the states. ELL = English language learners; FRL = free or reduced-price lunch; SEDA = Stanford Education Data Archive; SPED = special education; WECAN = Wisconsin Education Career Access Network.
Our sample was refined to include teacher candidates applying exclusively for public K–12 schools in Wisconsin, excluding those pursuing leadership, administrative, or noninstructional roles. Moreover, our analysis focused on full-time teaching positions and their respective candidates. Consequently, our study sample encompasses 390,095 application-year observations, representing 41,373 teacher candidates who applied for 26,635 teaching vacancies across 404 school districts within the state over 3 years, forming the basis for our comprehensive analysis of teacher job application patterns and hiring outcomes during the specified timeframe in Wisconsin. The WECAN system has recorded 25,036 unique applicants, which is fewer than the 41,373 teacher candidates noted above. This discrepancy is natural since many applicants appear in the job market in multiple years. For instance, the number of applicants was 14,650 in 2014, dropped slightly to 13,839 in 2015, and further to 12,884 in 2016. Each annual figure represents distinct application counts within those years. To enhance the dataset’s depth, we integrated it with staffing records from the Wisconsin Department of Public Instruction to ascertain hiring outcomes and candidates’ prior work details, including their previous teaching locations.
Notably, in our sample, a significant observation is that a substantial portion, specifically 62% of applicants, did not submit applications for any vacancies in rural schools. Conversely, a small fraction, amounting to 6% of applicants, exclusively applied to rural vacancies. Notably, 32% of applicants displayed geographical flexibility, as they applied to teaching positions in multiple geographic contexts, which encompassed rural districts among others. Those who are geographical flexible tend to submit more applications to positions available, as shown in Table A1 in the Appendix. For example, the average number of applications for those who submitted their application to rural distant positions at least once is 30, which is two times greater than the total number of applications by applicants who had applied to urban positions at least once (15 on average). This diversity in application behavior highlights the varied preferences and choices made by teacher applicants regarding the types of schools and locations they are willing to consider for employment.
Variables
To investigate the first research question, which centers on understanding job application patterns in rural schools compared to other locales, we employed two distinct measures. First, we examined the overall number of job applications submitted per vacancy across different locale categories (e.g., rural, town, suburban, and urban), with further analysis conducted within rural subtypes (rural fringe, rural distant, and rural remote). Second, we measured the distance between applicants’ home addresses and the location of the school districts for which they applied. This particular facet of our measure sought to unravel the geographic reach and mobility patterns exhibited by the applicants. Additionally, our investigation honed in on the fields of mathematics and SPED, which have historically grappled with acute staffing challenges, as underscored by prior research (Malkus et al., 2015; Palermo et al., 2022).
To address our second research question concerning applicants’ preferences for rural teaching positions, we employed the proportion of applications directed toward rural teaching vacancies as a key measure. For instance, a value of 0.3 indicates that a teacher applied to three rural positions out of 10 total applications during the job market period, thereby illustrating a preference for rural schools.
Finally, for our third research question—examining individual factors associated with candidates’ hiring outcomes—we created a binary hiring results variable, assigning a value of one to candidates successfully hired in the following school year and zero to those not hired. These measures collectively enable a comprehensive analysis of teacher job application patterns and hiring outcomes across diverse locales, subject areas, and applicant preferences.
In our second and third research questions, we incorporated candidate-level variables to examine their influence on job application patterns and hiring outcomes. These variables encompassed the following factors: gender (where female candidates were assigned a binary value of one); race/ethnicity (candidates belonging to underrepresented ethnic groups were dummy-coded as one); candidates with less than 3 years of teaching experience (indicated as one); candidates holding a master’s degree or higher (indicated as one); college selectivity (as per Barron’s ranking); candidates’ GPA; candidates’ work history, specifically whether they had worked in urban, suburban, town, or rural schools for the previous 3 years; whether candidates applied for positions within the same school district where they had worked for the past 3 years; the total number of job applications submitted by candidates; and whether candidates had graduated from EPPs situated in rural or town areas.
Table 2 offers a summary of descriptive statistics at the application level, segmented by different geographical locales. We used geographic locale codes derived from the NCES, which classify locales into city, suburban, town, and rural categories. These NCES locale codes are based on whether an area is situated within or outside of a principal city, an urbanized area, or an urban cluster. To maintain consistency with previous research (Goldhaber et al., 2020; Yang et al., 2021), we employed the term “urban” instead of “city” in our categorization. Additionally, the NCES further refines sub-categories within these four primary locales, based on population size and proximity to urban-centric areas, as outlined by Geverdt (2015). For instance, “rural fringe districts” are situated within a 5-mile radius of an urbanized area, “rural distant districts” are located more than 5 miles but less than or equal to 25 miles away from an urbanized area, and “rural remote districts” are positioned more than 25 miles from an urbanized area.
Application-Level Summary Statistics
Note. Parentheses are standard deviations. Novice applicants: less than 3 years of teaching experience. EPP = educator preparation program; GPA = grade point average.
Table 2 shows the significant disparities in application pools across different types of school locales, with rural schools exhibiting distinct patterns compared to other settings. The first through fourth columns indicate descriptive summaries for all sample, urban, suburban, and town, respectively, for comparison, followed by rural and rural sub-categories. Notably, rural job vacancies attract a lower proportion of female applicants in comparison to other locales, and this proportion further diminishes as the vacancies become more distant from urban areas. A similar trend is observed in applications from individuals belonging to underrepresented ethnic groups (people of Color), with a mere 1.8% representation in the application pool for rural remote positions, while urban areas see a higher proportion of 5.1%. Furthermore, rural schools tend to receive a higher volume of applications from novice teachers, indicating a greater interest from candidates with less than 3 years of teaching experience. Conversely, rural application pools demonstrate a lower presence of candidates with advanced qualifications, such as master’s degrees, college selectivity, and high GPAs, when compared to their counterparts in other locales.
Applicants aimed at rural positions have taught from various locales, but 23% of them are from rural districts. Among rural vacancies, districts in rural remote have the highest applicants from rural (30%), while rural fringe and rural distant receive 20% and 24% of applicants from rural, respectively. Another interesting finding is that rural vacancies have a lower share of internal candidates, with rural remote positions having only 2.4% of applicants from within the same district. This stands in contrast to urban areas, which witness a higher proportion of internal candidates at 14.4%. Additionally, rural job openings tend to attract a larger percentage of applicants who graduated from EPPs situated in rural or town areas. This suggests a potential alignment between the geographic origin of candidates’ education and their choice of job location. These disparities in application pools across various school locales underscore the nuanced dynamics at play in the teacher hiring process, with implications for the recruitment and selection of educators in rural schools.
In addition to the descriptive statistics at the application level as shown in Table 2, we further present the summary statistics at the applicant level in the Appendix, given that applicants could apply for multiple positions and thus they are represented multiple times in Table 2 depending on the number of their applications to particular areas. However, we found that descriptive values of the candidate characteristics are quite similar between the application-level and applicant-level results, suggesting that differential application patterns depending on candidate backgrounds are not a major concern. Additionally, we confirmed that the patterns of descriptive statistics are comparable over years (2014 through 2016), which is available upon request. In the applicant-level results, we found that the number of applications was 19 for applicants who submitted their application to rural positions at least once, which was greater for those who applied for positions in rural remote areas (30). The findings need to be interpreted with caution that one applicant can be represented in multiple locations if they applied for positions in various locations.
Analysis
To investigate the application and hiring patterns of rural teachers, we used a combination of descriptive statistics and regression modeling.
For the first research question—job application patterns in rural teacher labor markets—we employed descriptive analysis. Descriptive analyses yield valuable insights and contribute to foundational knowledge (Loeb et al., 2017) while serving as a basis for future research (Klasik & Zahran, 2022). We presented descriptive graphs for rural, town, suburban, and urban districts, with further differentiation of rural into three sub-categories—rural fringe, rural distant, and rural remote. We used box plots to illustrate median values, dispersion, and skewness, aiming to mitigate the impact of outliers, such as a few vacancies receiving an exceptionally high number of applications.
The second research question examines the individual factors associated with the proportion of job applications submitted to rural teaching positions. We ran the regression model at the applicant level as follows:
where the outcome (
For the third research question, in which candidate factors are relevant for them to be hired, we estimated the following regression via linear probability models:
where the outcome (Y ivt ) represents a dichotomous indicator for whether candidate i was hired in vacancy v in year t. In addition to individual factors that explain the probability of being hired, we calculated linear Distance from the candidate’s home address to the district address that posted the vacancy to examine whether the distance predicts hiring probabilities, even after accounting for a host of candidate characteristics. One would raise concern that rural schools may be more spread out from the district office than other areas, so our measure may not capture the influence of the distance in the hiring decision. We confirm that the average distance between a rural district office and schools is less than 2.8 miles; thus, rural schools in Wisconsin are closely located around the central office. Rural district offices often share the same building or are located within 5 minutes of driving distance. We used district information because some postings identify subjects and job details in the district but not the school’s name. However, this study is limited as we did not use the school address to applicant’s home address and the distance is not driving distance but a linear one. μv and τ t indicate vacancy fixed effects and year fixed effects, respectively. e ivt is the random error.
The inclusion of vacancy fixed effects allows us to constrain the variance to only that within vacancies, which reflects the labor market dynamics where a teacher candidate competes with other candidates applying to the same vacancy, and hiring is decided on a candidate’s qualifications relative to other candidates in the applicant pool. Vacancy fixed effects are also used to mitigate the influences from (un)observed vacancy-level characteristics (e.g., what subject areas are sought, whether the vacancy is unexpected or planned) and district-level factors (e.g., personnel policies or climate in districts). Standard errors are clustered at the vacancy level because multiple applications are nested in a vacancy.
To explore which individual factors are notable and whether the estimated magnitudes differ by location, we applied the same regression model to multiple sub-groups, including rural, town, suburban, and urban. Additionally, we divided the rural groups into three rural communities (rural fringe, rural distant, and rural remote) to identify whether the main results are consistent across locales.
Findings
Although rural schools, when compared to urban and town schools, attract a similar number of job applications, they do receive a notably smaller number of applications in comparison to vacancies observed in suburban areas. Specifically, rural schools receive approximately 35% fewer applications than their suburban counterparts, as demonstrated in Figure 1, left side. The median number of applications received per teacher vacancy in rural districts is 9, while suburban districts receive approximately 14 applications. Urban districts, on the other hand, receive an average of eight applications, and town districts receive around 10 applications. Though the number of applications in each locale does reflect population differences, it is not always the case. We find urban districts that tend to be much larger than any other districts but have a smaller volume of applications compared to other locales, suggesting that the district size alone could not explain the observed variations.
Size of application pool by locale and rural subtype.
To gain a deeper understanding of the relationship between the geographic classification of rural areas and the size of the application pool, we investigated three rural subcategories—rural fringe, rural distant, and rural remote. As depicted in Figure 1, right side, the number of applications tends to decrease as a teacher vacancy is situated farther from urban areas. Specifically, teacher vacancies in rural fringe districts, which are located within 5 miles of urban areas, receive an average of 10 applications. Meanwhile, rural distant districts receive an average of nine applications, and rural remote districts receive approximately eight applications.
For comprehensive comparative analysis, we have included mean and standard deviation values alongside median values for all geographic locations in Appendix Table A2. Three subcategories of “town”—town fringe, town distant, and town remote—are also presented to show how their magnitudes of job applications are comparable with those in rural locales. These statistics provide a more detailed perspective on the distribution and variability of job applications across different types of school locales.
Our analysis extends to examining whether the patterns in the size of the application pool exhibit variations across subject areas, with a particular focus on mathematics and SPED positions, which are recognized as areas facing substantial staffing challenges. It is noteworthy that our data provide information on particular subjects of the vacancies but do not show whether applicants are dual certified or temporary/emergency license holders.
Figure 2 provides insights into the number of applications received for these subject-specific vacancies. Notably, mathematics job vacancies in rural districts tend to attract fewer applications (median of seven) compared to their counterparts in suburban districts, which receive a median of 11 applications. Meanwhile, both town and urban districts receive approximately eight applications on average for mathematics positions. Delving deeper into the distinctions within rural locations, mathematics job vacancies that are situated farther away from urban areas receive fewer job applications. Specifically, rural remote vacancies garner only five applications, in contrast to rural fringe vacancies, which receive nine applications, and rural distant vacancies, with an average of seven applications.
Size of application pool by locales and rural subtypes (mathematics and SPED).
Furthermore, our analysis reveals that SPED positions receive the fewest applications in comparison to other subject areas, as indicated by the median values. In rural districts, the median number of applications for a SPED vacancy is six, while suburban districts receive an average of around 11.5 applications for SPED positions. Town and urban districts both have an average of seven applications per SPED vacancy. When examining specific rural classifications, rural fringe areas exhibit a slightly higher average of seven applications for SPED vacancies, whereas rural remote and rural distant communities receive around six applications.
These findings shed light on the variations in application patterns across subject areas, with mathematics and SPED positions experiencing distinct levels of interest among job seekers in different geographic locale.
To investigate the variability in job search radius among applicants based on the locale where vacancies are posted, we employed geographic distance measurements in miles, specifically examining the linear distance between teacher applicants’ home addresses and the addresses of the districts where vacancies were located. Our findings reveal that rural job vacancies tend to attract applicants from more distant locations when compared to application pools in other geographical areas. It is important to note that the actual driving distance and travel time would likely be much longer, as routes are rarely linear, further underscoring the challenges applicants face when pursuing positions in rural districts.
Figure 3 visually represents these findings. The median distance between applicants and rural vacancies is notably extensive, measuring approximately 39 miles. In contrast, the median distance for applicants applying to suburban vacancies is 14 miles, which is approximately three times shorter than the distance observed for rural vacancies. Town and urban districts show median distances of 32 and 14 miles, respectively.
Distance between applicants and vacancies by locales and rural subtypes.
Furthermore, our analysis uncovered considerable heterogeneity in distance within the rural sub-classifications. Specifically, rural fringe and rural distant vacancies receive applicants who reside less than 23 and 38 miles away from the job postings, respectively. In contrast, applicants for rural remote vacancies have a notably greater median distance of 74 miles, indicating that individuals applying for positions in remote rural areas are willing to travel considerable distances for employment opportunities.
These findings underscore the willingness of candidates to pursue teaching positions in rural locales despite the greater geographic distances involved, highlighting the unique dynamics of teacher recruitment in rural areas compared to other geographic settings.
Additionally, Figure 4 shows consistent patterns in the geographical distribution of job applicants concerning mathematics and SPED. Specifically, when considering mathematics positions, we noted that rural regions attract applicants from an average distance of 46 miles, while suburban areas receive applicants from an average distance of 15 miles. Meanwhile, in town and urban areas, the average distances are 41 and 19 miles, respectively. Our analysis also revealed a correlation between the distance of a job vacancy from an urban area and the willingness of applicants to travel for rural positions. In cases of mathematics positions, rural remote applicants were found to originate from an average distance of 79 miles, while rural fringe and rural distant applicants came from distances of 24 and 48 miles, respectively.
Distance between applicants and vacancies by locales and rural subtypes (mathematics and SPED).
Turning our attention to SPED positions, we observed that rural districts received applicants from an average distance of 28 miles, while suburban applicants originated from an average distance of 13 miles. Within the rural classification, there were notable variations in distance. For instance, rural remote applicants for SPED positions were located at an average distance of 54 miles, whereas rural fringe and rural distant applicants came from distances of 22 and 29 miles, respectively.
For a comprehensive comparison, we have included mean and standard deviation values as well as median values for all geographic locations and subject areas in Appendix Table A3.
Our second research question considers the characteristics of teacher applicants who apply to rural school districts. In our investigation, we examined an array of personal and professional attributes to identify factors associated with applicants’ interest in seeking employment in rural educational settings. The findings presented in Table 3, Column 1, reveal that several individual characteristics are closely linked to applicants’ preferences for rural locations.
Relationships Between Applicant Characteristics and Proportion of Applications in Rural Schools
Note. Novice applicants: less than 3 years of teaching experience. All specifications include year fixed effects. We also control for the total number of applications an applicant has submitted and indicator for whether an applicant applies to the school district where they worked. Standard errors clustered at the applicant level are in parenthesis. EPP = educator preparation program; GPA = grade point average; SPED = special education.
p < .1. *p < .05. **p < .01. ***p < .001.
To begin, female applicants and applicants of Color tend to submit fewer job applications for positions in rural areas. Specifically, applications from female candidates are 1.4 percentage points lower compared to their male counterparts, while applicants of Color submit 4.1 percentage points fewer applications for rural vacancies compared to White applicants.
Second, a set of proxies reflecting teacher quality, including teaching experience, educational degrees, the selectivity of undergraduate institutions, and GPA, exhibited correlations with patterns of applying to rural positions. Notably, applicants with less than 3 years of teaching experience submitted 1.6 percentage points more applications for rural vacancies than experienced counterparts. Conversely, applicants holding master’s degrees or higher submitted 0.7 percentage points fewer applications for rural positions. Additionally, applicants from less selective colleges tended to apply more frequently to rural positions, and a one-point increase in GPA corresponded to a 1-percentage-point decrease in applications for rural vacancies.
Third, applicants with prior experience of teaching in rural schools displayed a higher likelihood of applying for rural vacancies. Those with prior experience in rural schools submitted 14.3 percentage points more applications to rural positions, indicating that prior rural teaching experience emerged as the most significant factor explaining applicants’ preference for working in rural schools. Conversely, urban and suburban applicants tended to apply less frequently to rural job postings, with a reduction of 4 and 3.6 percentage points in applications, respectively. Furthermore, applicants who graduated from TPPs situated in rural or town areas displayed a 1.5 percentage point higher likelihood of applying for rural vacancies.
We conducted additional sensitivity analyses, as presented in Columns 2 and 3 of Table 3. Even after controlling for applicants’ certification areas, similar results and narratives were observed. We also excluded individuals who applied to only one vacancy, reflecting the possibility that estimates may be influenced by those with strong preferences for specific positions. Column 3 of Table 3 demonstrates that our primary findings remained robust after this exclusion, albeit with slight variations in coefficients. When we narrowed down the sample to mathematics and SPED teachers to account for variations across subject areas, as shown in Columns 4 and 5, some estimates lost statistical significance (e.g., gender, GPA, and rural TPPs); nevertheless, race/ethnicity and the locale of previous teaching experiences remained as influential factors explaining applicants’ preferences for rural positions. Specifically, applicants of Color were significantly less likely to apply for rural vacancies, while applicants with teaching experience in rural or town districts were more inclined to apply for rural positions.
Moving on to our investigation into the characteristics of applicants who are hired in rural schools, the results are presented in Table 4, Column 1. It is crucial to interpret these findings as associations rather than causal relationships, although the inclusion of vacancy fixed effects helps mitigate potential biases stemming from unobservable vacancy-level characteristics.
Applicant Characteristics Related to Being Hired
Note. Novice applicants: less than 3 years of teaching experience. All specifications include vacancy and year fixed effects. Standard errors clustered at the vacancy level are in parenthesis. EPP = educator preparation program; GPA = grade point average.
p < .1. *p < .05. **p < .01. ***p < .001.
First, personal characteristics were observed to influence hiring outcomes. Female applicants were 0.9 percentage points more likely to be hired in rural districts, while applicants of Color were 1.1 percentage points less likely to be hired overall in rural districts, although statistical significance was not observed when separated by rural classification. Applicants of Color exhibited lower hiring probabilities in the overall sample, suburban, and town districts.
Second, teacher quality measures yielded mixed results in terms of the likelihood of being hired. Applicants with less than 3 years of teaching experience were 0.4 percentage points more likely to be hired than experienced teachers in rural districts, a trend that also held for rural distant and rural remote positions. Novice teachers displayed higher hiring probabilities across the overall sample, urban, and town districts. Possessing a higher degree, such as a master’s degree or above, was strongly related to a 4.1 percentage point increase in the likelihood of being hired in rural districts, a pattern consistent across various rural classifications and the overall sample. The selectivity of undergraduate institutions did not significantly impact hiring outcomes in rural districts but held statistical significance in rural fringe and rural remote areas, indicating that applicants from less selective colleges were less likely to be hired. These results were consistent across the overall sample, suburban, and town districts. GPA was not associated with the likelihood of being hired in rural schools or rural sub-classifications; however, a higher GPA was linked to an increased probability of being hired across the overall sample, urban, and suburban districts.
Third, applicants with previous experience working in rural schools were more likely to be hired in rural positions. Specifically, having teaching experience in rural schools within the past 3 years was associated with a 1.1 percentage point increase in the probability of being hired in rural positions. These findings were consistent across rural classifications, with estimates becoming more significant as vacancies were farther from urban areas. Teaching experience in the same locale also strongly influenced the probability of being hired in urban, suburban, and town districts. Additionally, teacher applicants who had previously worked in the same district where they applied demonstrated a substantial advantage in terms of being hired across different locales. In rural districts, internal applicants were 5.9 percentage points more likely to be hired. When focusing on specific rural communities, indicators for internal applicants were consistently positively related to the probability of being hired, albeit with slight variations in the magnitude of estimates.
Finally, the location of applicants’ graduation and the proximity of their residence to school districts were related to the probability of being hired. Applicants graduating from TPPs located in rural or town areas displayed a 0.4 percentage point higher likelihood of being hired in rural positions compared to those from urban or suburban TPPs. Applicants from rural/town TPPs were more likely to be hired in rural distant positions but less likely to be hired in urban vacancies. Additionally, the farther an applicant’s home was from school districts, the greater the reduction in the probability of being hired, except for rural remote positions, which tended to attract applicants from longer distances.
These comprehensive findings shed light on the factors influencing teacher applicants’ choices and hiring outcomes in rural schools, offering valuable insights for educational policymakers and practitioners.
Discussion
This study examines application and hiring patterns of rural teachers by using statewide unique data from Wisconsin on teacher job application and vacancy details. “Rural” has been understood from a deficit perspective such as “not urban,” which culminates in policy and program recommendations without deeper understanding of rural-specific contexts. In addition, “rural” has been often portrayed as homogenous communities (Johnson & Howley, 2015; Yang et al., 2021), masking considerable variation in geographical proximity as well as population composition, structure, and culture (Longhurst, 2021). We often hear struggles of school leaders faced with nationwide staffing challenges (Sutcher et al., 2019), and scholars have been examining rural teacher shortages for the last decade (Hartman et al., 2022). However, little attention has been paid to rural teachers’ application preference and hiring outcomes across specific rural communities. Overall, our findings suggest that rurality is indeed a notable factor in job application and hiring that interacts with teacher applicants’ backgrounds.
This study found that rural schools receive far fewer applications compared to their suburban counterparts, while the number of applications is relatively similar to urban schools, which shows that rural schools share similar staffing challenges as urban schools. Overall, rural schools receive about 35% fewer applications compared to suburban schools, and they receive fewer applications in hard-to-staff subjects such as mathematics and SPED. Importantly, as rural schools are further away from urbanized areas, they seem to receive fewer applications compared to urban schools and rural areas that are close to urbanized areas. In particular, rural remote, which is further away from urbanized areas, receives overall 20% to 50% fewer applications compared to rural fringe, which is only 5 miles away from an urbanized area. In addition, our findings revealed that rural vacancies tend to have applicants from more distant locations in comparison with application pools in other geographical areas. In fact, the median distance (39 miles) between applicants and rural vacancies is roughly three times farther than the median distance in suburban vacancies (14 miles). The discrepancy is more notable within the rural sub-classifications. Applicants for rural fringe vacancies are less than 23 miles away from their home, whereas the distance in rural remote vacancies is greater than 74 miles. This pattern was consistent in cases of mathematics and SPED. Given the sizable variation in the number of applications and the traveling distance depending on locale and rural specific communities, policies and practice for teacher recruitment need to be responsive to their unique geographic contexts. For example, grow-your-own initiatives that develop and recruit teachers from the same community where they grew up (Sutton et al., 2014) can be more effective in geographically isolated rural communities (e.g., rural remote districts) rather than targeting broad rural areas that may show similar labor supply trends with urban or town areas.
Applicant characteristics are significantly related to their application tendency toward rural positions. Female applicants and applicants of Color are less likely to apply for rural vacancies. Previous studies pointed out that, despite increasing efforts to create a more equitable working environment, rural teachers still experienced microaggressions concerning their gender, race/ethnicity, and other qualifications (Brown, 2019). Female teachers and teachers of Color have observed a glass ceiling and lack of role models in rural schools where male and/or White school leaders dominate. Previous research largely found the importance of principals with similar demographic backgrounds for retaining female teachers and teachers of Color (Grissom & Keiser, 2011; Grissom et al., 2012), though there is little evidence concerning the role of the same-race or same-gender principals for teachers’ job application decision (Goff et al., 2018). In addition to the efforts for diversifying school leaders in rural schools, professional development programs and practices are needed for school leaders to be proactive on identifying and reflecting such biases to make the workplace welcoming for teachers from diverse backgrounds.
It is worrisome that applicants with higher qualifications (longer years of experience, higher degree, selective undergraduate institution, and higher GPA) are less likely to apply to rural positions. Although the quality of applicant pool did not necessarily lead rural schools to hiring applicants with lower qualifications, we found that novice applicants with less than 3 years of teaching experience are more likely to be hired in rural schools. Given the higher turnover rates of novice teachers, increasing attention has been paid to teacher induction and onboarding to support their retention (Kim, 2019). However, many rural teachers did not receive on boarding or mentorship programs (Fowles et al., 2014), so they needed to figure out the job on their own (Tran et al., 2023). Because novice teachers frequently leave their schools due to poor leadership, inadequate professional development opportunities, and poor working conditions, rural school leaders need to consider how to exercise their leadership and support for novice teachers, which is a consistently important factor for their retention (Kim, 2019). It is noteworthy that our study could not determine if the hired novice teachers are a rural school’s first choice or last choice after rolling offers. However, our findings show unequal application patterns regarding teacher qualifications in rural schools at least.
What was interesting about the pattern of application and hiring is that candidates who have rural teaching experience and graduate rural TPPs are more likely to apply to and be hired by rural schools. This finding is aligned with the research focused on rural Kentucky that teachers from rural institutions are more likely to obtain first employment within that region (Fowles et al., 2014). Thus, it would be an effective strategy for prospective teachers to be exposed to rural contexts by encouraging student-teaching experience in rural places in partnership with rural TPPs. Rural districts and other local partners may develop rural/remote teaching academies where student teachers gain access and exposure to environments they may not typically encounter. In addition, programs that generate pipelines from rural high schools to TPPs and rural schools will be helpful to build a strong teaching workforce in rural areas. Recently, Carl and Seelig (2023) investigated “grow your own” initiatives in Wisconsin, which involve rural districts working with TPPs and local communities to identify, recruit, and prepare local candidates to become teachers. They found that many participants of the programs completed training and licensure requirements and actually took rural teaching positions. Given the relatively low cost of such programs as well as evidence on job application, hiring, and retention, it is very likely a cost-effective approach for addressing rural staffing challenges.
More attention is needed not only to provide field experiences but also to ensure that these experiences are attuned to the unique contexts of rural schools. As Biddle and Azano (2016) emphasize, “Rural education researchers, as part of a coalescing group, continue to explore the significance of rural field experiences for preservice teachers in shaping and changing their perceptions of rural places” (p. 314). Moreover, research highlights the importance of leadership support (Frahm & Cianca, 2021) and strong connections between rural schools and their communities in retaining teachers (Seelig & McCabe, 2021; Ulferts, 2016). For hard-to-staff areas like STEM, fostering these relationships is particularly crucial. Goodpaster et al. (2012) suggest that rural administrators and community leaders should actively help new STEM teachers integrate into the community, which can reduce isolation and improve retention. Strengthening these ties can create supportive environments that encourage educators to stay long-term.
While additional research is needed to further examine the dynamics of rural teacher labor markets, this study provides meaningful implications for policies, practice, and future research. First, in addition to the efforts for addressing staffing challenges (e.g., grow-your-own, loan forgiveness, and sign-on bonus), rural schools need to focus on diversifying the prospective teacher workforce. In Wisconsin as of 2021, 2.2% of teachers are Hispanic and 2% are Black only, which do not mirror their student populations statewide that 12.8% are Hispanic and 8.9% are Black (Carl & Sim, 2022). What is more problematic is that the ratio of teachers of Color among the teacher workforce has not significantly changed over the last 2 decades. Despite the underrepresentation of teachers of Color in rural areas (Taie & Goldring, 2017) and fewer applications for rural positions shown in this research, rural teachers of Color are neglected and ignored in research and policy decisions (Grooms et al., 2021). Because rural schools could not hire applicants of Color who did not apply for the position, a focus on teacher diversity should be a priority when attracting candidates and developing partnerships with TPPs. Additionally, more research is needed to provide quantitative and qualitative evidence regarding what factors encourage or discourage teachers of Color in applying for rural teaching positions.
Second, while some policy solutions for staffing challenges, such as increased compensation (Cowan & Goldhaber, 2018) and loan forgiveness (Podolsky & Kini, 2016), may apply across locales, other solutions are likely to be more effective when tailored to rural-specific challenges. For instance, grow-your-own initiatives that generate an educator pipeline from rural high schools to TPPs and back to rural schools can be further designed for geographically isolated rural communities such as rural remote districts, rather than targeting broad rural schools with a one-size-fit-all program. Additionally, financial compensation for student teaching is needed for student teachers placed in rural distant or remote districts who often must travel significant distances from their TPPs for a certain period. Prior literature also mentioned that an unpaid student teaching experience creates a significant financial barrier for prospective teachers’ completion of licensure requirements for teaching (Carl & Seelig, 2023). Given the limited budget and resources that rural schools can operate, a series of policy efforts for staffing issues in rural areas can be best addressed through intentional stakeholder engagement and partnership with other rural school districts, local communities, TPPs, policymakers, and researchers (Harrison & Tran, 2020).
It is noteworthy that such efforts to develop a rural teacher supply through active engagement with rural communities is accompanied with tradeoffs that all preferences for potential candidates may not be met in terms of qualifications and demographics. For example, the teachers recruited from grow-your-own programs or partnerships with local institutions would likely be White from lower selective TPPs given the context of rural Wisconsin, which would not contribute to diversifying the teacher workforce and increasing teacher qualifications in rural schools. Therefore, targeted policy attention is needed to cultivate and recruit teachers from underrepresented groups and to improve investment and quality of rural EPPs for better-equipped rural teachers. Meanwhile, policymakers may need to consider priorities among human resource management strategies in rural schools given the limited resources.
Third, it is of importance to utilize teacher vacancy and application data to better understand the teacher labor dynamics and inform relevant policymaking. As compared to previous studies that utilized teachers’ final placement only, the statewide vacancy-application data help understand detailed labor market trends from both supply (e.g., application pattern) and demand (e.g., hiring outcomes) sides, making it possible to examine which individual or organizational factors are related to the application pattern and hiring outcomes upon vacancy opening and ensuing application pool. A few influential studies employed application data to explore the teacher recruitment and hiring process in urban areas, including New York City (Boyd et al., 2011), Washington, D.C. (Jacob et al., 2018), Los Angeles (Bruno & Strunk, 2019), and Chicago (Engel et al., 2014). To our knowledge, there is only one study focused on rural teachers and schools with job vacancy data (Goldhaber et al., 2020), which concluded that being located in rural settings contribute to additional staffing challenges in California rural schools. Given the importance of rural schools serving one-fifth of the U.S. students and increasing attention to rural teacher shortages, much more research is needed to investigate dynamics of teacher labor markets using data on teacher job application and vacancy details.
Finally, research underscores the important role of principal–teacher racial congruence in hiring and retaining teachers. Viano et al. (2023) found that race-gender congruence was often associated with better workplace supports, particularly for Black teachers with Black principals and male teachers with male race-congruent principals. Similarly, Bartanen and Grissom (2023) found that Black principals not only increase the likelihood of hiring new Black teachers but also decrease Black teacher mobility. In the same vein, Grissom and Keiser (2011) showed that principal–teacher race congruence is linked to higher job satisfaction, which is positively correlated with teacher retention. However, the conversation around principal–teacher racial congruence in rural areas has been less explored. While states like Wisconsin have less diverse rural populations, Southern states tend to have higher percentages of students and educators of Color in rural schools. Therefore, further research is needed to examine the impact of racial congruence between teachers and principals in rural communities, as this could have significant implications for teacher hiring and retention (Goldhaber et al., 2020) as well as overall school climate (Williams et al., 2021) in these areas.
Although the findings of this research contribute to the literature on rural teacher labor markets, they are not without limitations. First, although we observe who applies and is hired in particular vacancies, our data do not provide information on which applicants received and accepted interview offers, if applicants accepted or declined final offers, and if a hired teacher is a district’s first (or last) choice. The lack of such information makes it difficult to identify the detailed hiring dynamics in both supply and demand sides. For example, given our finding that novice teacher candidates show higher probability of being hired in rural teaching positions, we are uncertain if novice teachers want to teach in rural schools or the rural position is simply the best offer available they can utilize. Similarly, it is unclear whether rural schools prefer novice teachers or are simply constrained by the applicant pool available. Further descriptive analysis of our datasets, which is available upon request, showed that applicants hired into rural schools submitted nearly half (49%) of their applications to rural positions, compared to just 7% among those hired into non-rural schools. This finding was consistent when narrowing down to novice applicants (43% vs. 8%). Although we do not have access to stated preferences such as surveys or screening interviews, this application pattern suggests that, for those hired in rural schools, stated and revealed preferences may align. Research by Cannata (2010) and Engel et al. (2014) suggests that job preferences vary based on applicant characteristics and that teachers tend to favor schools in familiar or preferred locations. While their findings help contextualize our results, our data do not allow for a direct comparison of stated and revealed preferences. Future research should further investigate applicant preferences to improve our understanding of the teacher labor market. In particular, examining the alignment—or misalignment—between stated and revealed preferences, especially among rural applicants, may uncover critical differences between rural and urban application/hiring patterns and support more equitable teacher placement strategies.
Second, our data do not include recent labor market activities because the period 2014 to 2016 is the latest data based on our contract with WECAN. Thus, we could not observe how recent changes such as the COVID-19 pandemic affect the size of application pool, application pattern, and hiring dynamics. Given the recent policies aimed at rural staffing challenges such as 4-day school week (Anglum & Park, 2021) and emergency licenses (Goldhaber et al., 2020), recent data on teacher application and vacancy data would allow us to examine the impact of such policy initiatives on teachers’ labor market responses. Additional research on the job application and hiring patterns that can address the above limitations is necessary to further support rural schools and teachers.
Footnotes
Appendix
Distance Between Applicants and Vacancies
| All subjects | Mathematics | SPED | ||||
|---|---|---|---|---|---|---|
| Location | Mean (SD) | Median | Mean (SD) | Median | Mean (SD) | Median |
| Urban | 19.98 (22.89) | 14.37 | 25.49 (24.50) | 18.65 | 17.24 (20.71) | 12.57 |
| Suburban | 19.20 (20.56) | 13.86 | 21.48 (22.66) | 15.44 | 17.39 (20.01) | 13.25 |
| Town | 43.45 (37.67) | 32.02 | 55.62 (48.54) | 41.36 | 37.18 (33.75) | 29.04 |
| Fringe | 28.86 (31.33) | 20.15 | 40.92 (35.67) | 30.43 | 26.89 (34.73) | 19.21 |
| Distant | 47.28 (34.40) | 36.20 | 61.35 (51.44) | 46.21 | 40.83 (30.54) | 32.35 |
| Remote | 77.89 (66.01) | 55.70 | 80.13 (63.03) | 61.08 | 53.31 (48.07) | 39.41 |
| Rural | 54.58 (46.88) | 38.81 | 60.83 (50.76) | 45.62 | 42.87 (43.58) | 28.39 |
| Fringe | 36.62 (36.55) | 23.06 | 36.31 (37.06) | 24.48 | 28.57 (26.69) | 21.67 |
| Distant | 49.67 (37.30) | 38.17 | 63.86 (50.67) | 48.26 | 37.17 (32.76) | 28.88 |
| Remote | 88.24 (57.49) | 73.54 | 92.29 (50.83) | 79.41 | 78.93 (62.71) | 54.13 |
| Total | 30.81 (34.52) | 19.57 | 36.57 (39.64) | 23.82 | 25.97 (30.71) | 17.75 |
Note. SD = standard deviation; SPED = special education.
Acknowledgements
The authors gratefully acknowledge the staff of the Wisconsin Association of School Personnel Administrators and Dr. Bradley Carl of the Wisconsin Evaluation Collaborative for facilitating access to the WECAN data utilized in this study. Their support was instrumental to the successful completion of this research.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
1.
We acknowledge and appreciate the contributions of 
working paper, The Role of Place: Labor Market Dynamics in Rural and Non-Rural School Districts, which brought attention to critical issues in the teacher labor market within rural school districts and served as a foundational framework for this study.
Authors
SE WOONG LEE, PhD, is an associate professor in the Department of Educational Leadership and Policy Analysis at the University of Missouri. His research examines educational policy and leadership, with a particular focus on equity and Asian American studies.
MINSEOK YANG, PhD, is an assistant professor in the Department of Educational Leadership and Policy Analysis at the University of Missouri. His research explores educators’ career trajectories, school reforms, and teachers’ unions, with a special focus on marginalized populations and communities.