The Geography of California's Teacher Education Programs

This post was written by Michael Lloydhauser and Christopher Ozuna, both PhD candidates in UC Santa Barbara's Gevirtz Graduate School of Education

Teacher retention and teacher turnover have long captured the attention of researchers (e.g., Lachman & Diamont, 1987). Despite the overwhelming amount of research that has been done in this area, the problem of high rates of teacher turnover remains and in some specific contexts, is getting worse (Carver-Thomas & Darling-Hammond, 2017). Carver-Thomas and Darling-Hammond (2017) reported that between the 2011-2012 and 2012-2013 school years, the teacher turnover rate was about 16%, and about more than two-thirds of teacher turnover was voluntary. California is no exception to this problem, where research suggests that teacher shortages are worsening, especially for vulnerable student populations (Podolsky & Sutcher, 2016). The Covid-19 pandemic is expected to exacerbate this problem (Wojcikiewicz & Darling-Hammond, 2020).

Simultaneously, the number of people enrolling in teacher education programs has decreased over time, further contributing to increased demand for teachers (Connelly & Graham, 2009; Cooley & Yovanoff, 1996; Partelow, 2019). Reasons for this decrease in enrollment include: the financial barrier for entry and low salaries once in the profession (Podolsk et al., 2016). Recently, the Learning Policy Institute published a map, which highlights key factors associated with teacher shortages across California’s school districts and counties (published in December 2019 and available here). This map highlights the extreme variation that exists with regards to teacher supply and demand, which is not surprising given the wide range of population densities seen in California. 

Our aim was to see how the geographical distribution of teacher education programs interacted with the distribution of well-qualified teachers in California. Previous research has shown that teaching candidates (individuals in pre-service teacher education programs) tend to work closer to where they grew up and the location of their teacher education program (TEP) (Goldhaber, 2019; Killeen, et al., 2015; Reininger, 2012). Student teaching placement is also known to contribute to teacher hiring (Krieg, Thobald & Goldhaber, 2016). Furthermore, we know that applicants are less likely to apply to a job as travel distance increases and employers are more likely to hire more proximal applicants (Killeen et al., 2015). The localized nature of the teaching labor force has specific implications for the location of TEPs and how it relates to teacher supply and demand, specifically in highly urban and rural areas.

In conducting this research, we have faced multiple challenges, including limited existing literature, an imperfect theoretical framework as well as a patchworked data set that does not provide the information we want. Here, we describe the applicability and shortfalls of human capital theory, summarize relevant literature and discuss the implications of findings we have generated and findings we hope to generate with future data sets.

Theoretical Framework

We believe it is important to ground this work in a theoretical framework. Basing work in an existing theoretical framework allows researchers to build on existing literature and shows how various constructs are related (Billingsley & Bettini, 2019). Much of the research in this area does not utilize a theoretical or conceptual framework, although there were some exceptions (Boyd et al., 2005; Krieg et al., 2020a; Krieg et al., 2020b). If we are to categorize education, specifically teacher education as an economic good, Human Capital Theory (HCT) is a logical framework. It is essential to account for the skills and knowledge of workers so that the social and economic value can be fully comprehended (Shultz, 1972). As we experience a high demand for teachers in California, it is possible that teachers who attended a rigorous TEP are paid the same as teachers who attended a less rigorous TEP or an alternative credential pathway. This incentivizes less teacher preparation which is connected to various undesirable outcomes such as higher teacher turnover (Carver-Thomas & Darling-Hammond, 2017). More recently, Gillies (2017) posited that teaching quality is correlated with an ability to develop the human capital of their students. We extend this thought in that educational investments for teacher preparation will yield benefits for teachers as well as their future students.

This theory has certain limitations and caution must be used when interpreting findings with this lens. Literature has explained that a human capital approach to education policy is over-simplified and undermines democratic education (Cochran-Smith et al., 2017; Gillies, 2017). Additionally, HCT fails to account for wage stagnation and professional social status (Marginson, 2019), all of which is quite relevant for the teaching profession. We are uncertain of the degree to which these criticisms apply to a geography perspective and have yet to find a theoretical or conceptual framework suitable enough to use in place of HCT.

What We’ve Learned

We used multiple publicly available data sets in an attempt to see how the geographical location related to teacher shortages in California. First, we used the directory data from the CTC to obtain the basic information for all TEPs in California such as address, institution type and accreditation status. Secondly, we used the county-level information from the Learning Policy Institute, to incorporate information regarding the teacher workforce in that county. This dataset included information such as the percentage of turnover and attrition, the number of TEPs located in the county, some demographic information on the teacher workforce, as well as the percentage of teachers hired in that county with a substandard credential. Additionally, we retrieved other county-level demographic information available from the US Census Bureau to help give context to these data. This patchworking of data revealed certain findings, although not exactly what we intended to discover. The rate of unemployment in a county is positively correlated with the percentage of teachers lacking a proper credential and the correlation is of great practical significance: for every percentage point the unemployment rate in a county increases, the level of underqualified teachers increases by 2.8 percentage points, all else held equal. Additionally, the percentage of beginning teachers in a county, defined as those in their first or second year of teaching, is also positively correlated with underqualified teachers. For each percentage point increase in beginning teachers as a share of the teaching workforce, the level of underqualified teachers increases by 1.8 percentage points, all else held equal.

 

From a spatial perspective, we see a concentration of TEPs in California’s urbanized areas, especially the San Francisco Bay Area and the Greater Los Angeles Area. These areas constitute the bulk of both the state’s population and TEPs. However, these highly urbanized counties also have higher ratios of TEPs to total population. At the same time, 28 of California’s 58 counties have zero TEPs based out of an institute of higher education, and these counties range in population from 1,146 people in Alpine County to 460,774 in Tulare County. So, while the demand for teacher preparation is relatively low, it is not zero and these less densely populated areas still need well prepared teachers. In the above map, we see how the Bay Area and San Jose have access to teacher education programs that is reflective of their population, whereas Modesto and Merced (further east and inland from San Jose) have fewer teacher education options despite dense populations.

We see a similar pattern in southern California. The Los Angeles and San Diego areas have multiple options for people wanting to enroll in a TEP. However, people in Palm Springs and Imperial County have no options for in person teacher education. Given the localized nature of the teacher workforce discussed in previous literature, it is unclear how areas without access to teacher education are able to recruit new teachers. These maps help confirm the findings of Goldhaber et al. (2020), who explained how rural areas in California experience staffing challenges, part of which may be in part due to proximity to teacher education.

To more fully explore the geography of California's teacher education system, please use the web map below. Similar to the featured maps above, darker shades of blue represent more densely populated Census tracts, while the purple circles are sized in proportion to the number of teachers trained by a TEP.

What We Do Not Know

            Broadly speaking, we do not know where teachers are being prepared and where they end up teaching. Although these maps show the location and size of TEPs and the population density of where they are located, we cannot say for sure whether or not there is sufficient access to teacher education for the various regions of California. While we feel confident about teacher education access in high density areas, we are less confident about access in medium and low population density areas.

            Online programs are a potential solution for areas with limited access to in person teacher education. Various programs are used in California, such as National University and Cal State Teach among others. While a physical address for these programs is provided by the California Teaching Commission on Teacher Credentialing, we do not know where these candidates are living or completing a student teaching practicum. Additionally, some of the state’s TEPs may have satellite campuses, where in-place coursework is taking place, but these candidates are still linked to the main campuses’ physical address. For example, this may be the case for some teacher candidates at CSU San Bernardino’s Palm Desert campus.

Implications for Statewide Data Systems

            While the publicly available data in this area does let us see some basic information around the teacher preparation system in California, it is lacking in areas that are needed to make more data-informed decisions or analyses around California’s capacity for teacher education. California’s data, like that of many states, is largely managed by individual agencies or departments, and crossover data systems tend to be around a specific project or issue. As public agencies of all types, not just in teacher education and not just in California, collect more and more data, there is a growing push for states to enact more comprehensive data strategies, including federal input through legislation like the Foundations for Evidence-Based Policymaking Act (2018). These guidelines recommend that Federal agencies implement cohesive data strategies, both in how data is collected, used and stored to benefit Americans. Some states are much further along in reshaping the way data influences agency services and actions (such as Connecticut, although there are many others) who have been building out their data strategies in many areas of state services.

California is in the process of adopting a more clearly outlined statewide data strategy, and this approach could be beneficial to the field of teacher education. In particular, there are two new data systems in the works that could help answer questions raised in this post. The first is through CTERIN’s own goals in its Aim 1 work, which seeks to create a statewide teacher education data system by linking CTC and CDE records. Such a dataset would include where teachers are teaching, where they earned their teaching credential and where their pre-service TEP was located.  The second system is the proposed data Cradle-to-Career system that would allow agencies to observe how Californians interact with a range of state agencies throughout their lives.

Both of these data systems would create some of the sorely needed links between California’s public agencies. However, the linkages are only as useful as the information they are linking. In the work we have outlined here, new data collection procedures would need to be introduced so that the state’s TEPs are sharing useful information with the state that may not have been previously requested, such as the location of a teacher candidate’s student teaching. It is important that these elements are carefully considered so that TEPs have time to prepare. While it may be tempting to collect only the most quantifiable data (such as edTPA scores or pass-rates, or student-level standardized test scores), these new data systems present an opportunity for our field to ask ourselves what are our most pressing questions, and what information would we need to answer them. Knowing where California’s teachers are being trained would be useful information to the CTC and CDE in determining how the current teacher preparation system should be adjusted to meet the state’s needs. This information would enable more robust findings that would be beneficial to policy makers and school administrators.

Feel free to reach out to Michael (mdannhauser@ucsb.edu) or Chris (christopher_ozuna@ucsb.edu) to talk more about this blog post, or their work in teacher education.

References

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Boyd, D., Lankford, H., Loeb, S., & Wyckoff, J. (2005). The draw of home: How teachers' preferences for proximity disadvantage urban schools. Journal of Policy Analysis and Management: The Journal of the Association for Public Policy Analysis and Management, 24(1), 113-132.

Carver-Thomas, D. & Darling-Hammond, L. (2017). Teacher turnover: Why it matters and what we can do about it. Palo Alto, CA: Learning Policy Institute.

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