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Is There a Career and Technical Education Coursetaking Pipeline Between High School and College?


by Jay Stratte Plasman, Michael A. Gottfried & Cameron Sublett - 2019

Background: Previous studies have explored the relationship between career and technical education (CTE) on numerous secondary and college outcomes. However, a key oversight in the literature is the examination of the CTE coursetaking pipeline as it makes a direct connection between high school and college.

Research Questions: We asked the following research questions to address the gap in CTE literature around secondary to postsecondary pipelines: 1. Does taking CTE courses in high school predict taking CTE courses in college? 2. Does this relationship differ between students who attend 2- and 4-year colleges? 3. Does the relationship differ by different areas of CTE?

Research Design: To respond to these questions, we used the Education Longitudinal Study of 2002 (ELS:2002), a nationally representative dataset. We employed basic logistic regression, school fixed effects, and instrumental variable estimations to reduce biases in our estimations in the relationship between high school and college CTE coursetaking.

Results: We found that CTE coursetaking in high school linked to overall CTE coursetaking across all years of college. When examining 2- and 4-year college coursetaking independently, only the relationship between high school and 4-year college CTE coursetaking was significant. We also found that there existed differential linking based on type of institution in which the courses were completed and area of CTE—specifically, applied STEM, business, trade and industry, and health.

Conclusions: A first implication from these findings is that CTE in high school, which is itself funded through the current iteration of the Perkins legislation, appears to be having a noticeable link to CTE participation in college. From the second research question, there could very well be a strong connection between high school CTE and 2-year enrollment that is not reflected in first year CTE coursetaking at the 2-year level. Finally, the implications from the third research question speak to the need to focus on CTE as a group of individual categories as opposed to a single overarching group.



An increasing number of jobs available to recent college graduates require more technical skills and expertise than required in previous generations (Brand, Valent, & Browning, 2013). This change has been driven by the improvement of tools and technologies that require additional training (Bureau of Labor Statistics, 2013). At present, recent forecasts expect this trend to continue through the middle of the next decade (President’s Council of Advisors on Science and Technology, 2012). Healthcare, business, computer, and mathematical occupations—in which many of the individual professions require at least some postsecondary training—are all expected to grow by more than double digits into the next decade (Bureau of Labor Statistics, 2013). If graduating college students are not prepared with the appropriate skillsets to match the needs of the labor market, there are concerns that a “skills gap” will emerge in the United States (Carnevale, Smith, & Strohl, 2010). More specifically, students educated in postsecondary institutions from abroad rather than from the United States might be more equipped for U.S. employment opportunities (Borjas, 2004; Hossain & Robinson, 2012; Kuenzi, 2008; National Center for Education Statistics, 2009).


Given these changes in the labor market, U.S. education systems responded accordingly and have recently been reconsidering ways to more effectively link education and employment. For instance, in the U.S. Department of Education’s (2012) Blueprint for Transforming Career and Technical Education, former secretary Arne Duncan claimed “students need a more rigorous, better tailored education to acquire the skills they need to compete, to follow a clear pathway into the middle class and to continue to prosper” (p. IV). To meet this request, the federal government is currently considering a reauthorization of the Carl D. Perkins Career and Technical Education Act of 2006, through which career and technical education (CTE) courses were originally designed to combine the competency-based applied learning of technical- and occupation-specific skills with academic skills such as higher order reasoning and problem-solving.


The fact is, a vast majority of students are already taking CTE courses in high school. It is estimated that roughly 90% of high school students complete at least one CTE course (Bersudskaya & Chen, 2011; Dougherty, 2016). Therefore, the impending reauthorization of the Perkins Act would continue supporting CTE coursetaking that is fairly ubiquitous throughout the United States  Such a widespread movement, however, comes with a large financial cost. In a reauthorization, the federal government would allocate some $1.13 billion in FY 2017 to revising the funding, instruction, and evaluation of CTE throughout the United States (Strengthening Career and Technical Education for the 21st Century Act, 2016).


Given its prominence throughout the country as well as the significant cost of supporting and implementing these courses, a growing body of research has examined whether taking CTE in high school is, in fact, an efficacious way to support the growth of students’ skillsets and tighten the K–12–16-employment pipeline. What we know thus far is promising. With regard to taking CTE in high school and high school outcomes, high school students who take CTE courses have lower chances of dropping out compared to those who did not take CTE courses (Bishop & Mane, 2004; Plank, DeLuca, & Estacion, 2008; Rumberger, 1987). Students who took CTE courses in high school also had higher math achievement scores by 12th grade, particularly for those at lower math ability levels (Gottfried, Bozick, & Srinivasan, 2014; Stone, Alfeld, & Pearson, 2008). Finally, research identified that high school students who participated in CTE courses were more likely to take more advanced math and science coursework by high school graduation (Bozick & Dalton, 2013; Gottfried, 2015).


As for taking CTE in high school and college outcomes, CTE coursetaking in high school is associated with increased odds of enrollment in college, especially 2-year postsecondary institutions (Plank et al., 2008). Taking CTE in high school is also linked to increased odds of declaring a STEM major in college, specifically for those students who completed STEM CTE coursework in high school (Association of Career and Technical Education, 2009; Gottfried & Bozick, 2016; McCharen & High, 2008).


While previous studies examined the link between high school CTE coursetaking and high school outcomes or between high school CTE coursetaking and enrolling in college or declaring a major, there remains a critical gap. Specifically, missing from our understanding of the efficacy of high school CTE coursetaking is the role these courses may play in connecting CTE coursework in high school to CTE coursework in college. Understanding this link in more depth will help provide a richer portrait of the CTE pipeline: how to build skills from K–12 to college and, ultimately, to career.   


Considering the sizable public resources that would be required to fund the reauthorization of Perkins and the relative lack of understanding of the link between CTE coursework in high school and CTE coursetaking in college, the current study seeks to answer the following research questions:


RQ1: Does taking CTE courses in high school predict taking CTE courses in college?

RQ2: Does this relationship differ between students who attend 2- and 4-year colleges?

RQ3: Does the relationship differ by different areas of CTE?


The first research question looks broadly to understand the CTE “coursework pipeline” between high school and college. The second research question looks to dissect the pipeline a bit further to observe differences in the overall CTE pipeline between 2-year and 4-year colleges. Our third research question brings further clarity to where differences in the CTE pipeline may exist through examining differences in coursetaking in specified CTE categories.


LINKING HIGH SCHOOL AND COLLEGE CTE COURSETAKING


The lack of empirical investigation into the link between high school CTE and college CTE coursetaking is unfortunate. As the federal government has made clear, an integral component of gaining relevant skills for the labor force is CTE coursetaking in both high school and college (U.S. Department of Education, 2012). Though a body of literature exists on high school CTE coursetaking on high school and college outcomes, we do not have evidence regarding the ways that high school CTE coursetaking links to college CTE coursetaking.


The link between high school and college CTE coursetaking represents an important mode in the CTE pipeline from high school to college and to career (Dougherty, 2016). In order for students to successfully progress from high school and ultimately into a career, the middle “node” on that pipeline represents the knowledge and skills garnered in college—i.e., college-level coursework (Bragg & Ruud, 2007). That is, we need to be concerned not simply whether students enrolled in a postsecondary institution or what students had majored in, but rather with the actual skills learned throughout college. As mentioned above, the development of skills via this pipeline is particularly relevant today; jobs in the future are projected to require higher levels of skill and technical expertise beyond what high school course training alone can provide (Bureau of Labor Statistics, 2013). However, as of yet, no study has examined the CTE coursetaking pipeline and as a result, our understanding of the long-term efficacy of enrolling in high school CTE coursework has remained incomplete. For legislators in Congress, this lack of knowledge is problematic as they weigh the benefits and costs of reauthorizing Perkins for the next generation of students.


Establishing a link between high school and college CTE coursetaking is relevant to policy and practice in three key ways, as reflective of our three research questions. First, it is critical to understand if taking more CTE courses in high school is associated with taking more CTE courses in college, merely for the fact that more postsecondary units earned might improve skill building opportunities as well as the chances of certificate or degree completion. Motivating the reauthorization of the Perkins Act is, among other things, the desire to strengthen the transition from high school to college to career. Therefore, if coursetaking in high school predicts more coursetaking in college, this would give a better sense of the efficacy of a federal policy whose goal is to strengthen the educational pipeline. Today’s CTE high school coursework may accomplish this by illustrating the accessibility and relevance of CTE concepts to college and career in addition to skill building (Brand et al., 2013; Plank et al., 2008). If, in fact, CTE courses in high school successfully motivate students to appreciate the role of technical skill in their lives by increasing the relevance and rigor of the subject matter, it seems warranted to examine whether students who take CTE courses in high school would do so in college.


Second, we might expect to find the association between high school CTE coursetaking and college CTE coursetaking to be stronger among students who attend 2-year colleges after high school than students who attend 4-year colleges. This expectation stands to reason because 2-year colleges have a longer history of providing CTE coursework to students relative to the 4-year schools (Bragg & Ruud, 2007). Furthermore, many 2-year schools also have a history of partnering with local high schools in CTE-funded programs. For example, the state of California launched the California Partnership Academies (CPA) program in 1984 in order to provide high school students with expressed interests in career and technical fields and community college attendance with smaller class sizes and learning communities with a career theme or focus. As of 2009–10, there were 467 CPAs in the state (California Department of Education, 2011). The latest reauthorization of Perkins calls for even greater collaboration between high school and 2-year colleges in particular (U.S. Department of Education, 2012). Therefore, we hypothesize that the link between high school and college CTE coursetaking will be strongest for students transitioning into 2-year colleges, given the history of courses and partnerships.


Third, to more fully understand the link between CTE coursetaking in high school and college, it is important to also assess any potential differences attributable to CTE concentration area in high school. While there exists little to no research on the CTE pipeline by category, it would stand to reason that there may be differences. First, Gottfried and Bozick (2016) found that STEM CTE coursework in high school predicted students’ majoring in STEM in college, which corroborates the main findings of You and Rumberger (2012), namely that the type of courses students take in high school predicts the courses students will take in college. Also, there do exist specific standards for each CTE category, which focus on learning different skills (California Department of Education, 2015). Dougherty (2016) found that students who have a CTE concentration in high school—defined as completing three courses in a specific career pathway—exhibit an added bonus in numerous end-of-high-school outcomes, including increased odds of enrolling in a 2-year college. Through breaking out the concentrations by category, it becomes possible to observe the differential connections across these separate categories of CTE, which we argue will not just provide greater insight into any potential CTE coursetaking link but will be informative for policymakers as they consider a reauthorization of Perkins.


METHOD


DATASET


The current study examined data from the Educational Longitudinal Study of 2002 (ELS:2002) produced by the National Center for Education Statistics (NCES) at the U.S. Department of Education. The ELS:2002 dataset followed a cohort of students enrolled in the 10th grade in 2002 as they completed high school and entered the labor force or postsecondary study. Spring 2002 was the base year for the study, at which point students, teachers, parents, and administrators were all asked to complete questionnaires. Follow-up interviews took place in the spring of 2004 (first follow-up), and again in the spring of 2006 (second follow-up) when they should have been in their second year after high school. Finally, a 2012 update included postsecondary transcript data.


A crucial aspect to a study on coursetaking was the work completed by the NCES to collect and aggregate both high school and postsecondary transcript data (Ingels et al., 2014). The NCES collected high school transcript data in 2005 when a majority of students had finished high school and degree verification was completed. In this study, we merged transcript data with the aforementioned survey data. Transcript data included full coursetaking histories for the students, as well as grades and credits earned in those courses. Coursetaking files were included for a vast majority (91%) of students who participated in the baseline survey in 2002. Credits were standardized across schools to a common Carnegie unit—recognized as a course that is taken for one period every day throughout an entire school year. A similar process ensured postsecondary credits were standardized as well. These postsecondary transcript data were released in 2015, ensuring this analysis makes use of the most up-to-date data available in order to observe postsecondary coursetaking patterns.


The final cleaned and coded data provided a comprehensive view of each student in the ELS:2002 dataset. In order to be included in the analysis, each case needed to include valid transcript information at both the public high school and postsecondary levels, as well as non-missing outcomes. As our analysis focused on coursetaking patterns in high school and college, students with missing transcripts at either the high school or postsecondary level were excluded, resulting in a final analytic sample of approximately N = 6,000 student observations in public schools. Per NCES rules, all sample sizes of four digits have been rounded to the nearest ten. Note that the ELS:2002 dataset includes probability weights to ensure estimates obtained from subsamples are appropriately representative of the broader student population in the United States. Finally, our analyses focused on public school students for a number of reasons: attending private school may operate as a proxy for unobserved variables about which we may be concerned; public schools serve a majority of students in the United States; and public schools have been supported as presenting a more similar sample of students based on social, cultural, and economic factors (Wang, 2015).


OUTCOMES


From the 2012 postsecondary transcript files, we determined every course an individual completed throughout postsecondary education. Therefore, we were able to examine a number of dependent variables in this study. We looked at three specific areas of postsecondary education (PSE) CTE coursetaking: number of units completed, number of units attempted, and GPA. For each of these areas, we examined PSE as a whole, 2-year PSE independently, and 4-year PSE independently. CTE courses at the postsecondary level were identified in the 2010 College Course Map (CCM), and we coded PSE CTE based on this taxonomy (Bryan & Simone, 2012).


We further broke down these outcomes into a few previously researched CTE categories in an effort to discern the role CTE plays across these different areas. The four specific categories we chose to look at were applied STEM, business, trade and industry, and health. The applied STEM category included courses in computer and information sciences, and engineering and technology as previously identified (Gottfried, 2015; Gottfried & Bozick, 2016; Gottfried, Bozick, & Srinivasan, 2014). The business category included courses in business support, business management, business finance, and marketing as defined in the 2004 National Assessment of Vocational Education (NAVE) report to Congress and the CCM (Bryan & Simone, 2012; Silverberg, Warner, Fong, & Goodwin, 2004). The trade and industry category included courses in construction, manufacturing, and transportation also defined in the NAVE report and the CCM. Finally, the health category included credits completed in the health professions field. We also looked at the number of math units completed and math GPA in PSE. All of these outcome variables were constructed as continuous variables. Table 1 presents each of our outcome variables broken down by 2-year and 4-year college enrollment.



Table 1

   
          

Postsecondary Outcomes

 

 

 

 

 

 

 

 

 

     

First-Year Totals

  

Cumulative Totals

 

2-year

 

4-year

  

Mean

Std Dev

 

Mean

Std Dev

 

Mean

Std Dev

Total CTE units (completed)

 

35.47

32.50

 

--a

--

 

--

--

Total CTE attempted

 

39.39

33.90

 

--

--

 

--

--

College CTE GPA

 

2.89

0.91

 

--

--

 

--

--

First year CTE units b

 

3.89

6.02

 

3.61

6.43

 

3.91

5.34

First year CTE GPA

 

--

--

 

2.64

1.23

 

2.97

0.97

Total applied STEM units

 

5.39

15.21

 

--

--

 

--

--

First year applied STEM units

 

0.82

2.48

 

0.74

2.39

 

0.89

2.56

Business units

 

8.82

19.56

 

--

--

 

--

--

First year business units

 

0.53

1.97

 

0.50

1.86

 

0.55

2.05

Trade units

 

1.70

9.70

 

--

--

 

--

--

First year trade units

 

0.32

2.64

 

0.58

3.47

 

0.09

1.52

Health units

 

8.18

24.06

 

--

--

 

--

--

First year health units

 

0.37

2.54

 

0.48

3.57

 

0.25

1.43

          

nc

 

6,000

 

 

2,750

 

 

3,070

 

a - A double dash in a given cell indicates that outcome is not presented in our tables

   

b - Examining first year unit completion allows both for a more accurate comparison between 2- and 4-year colleges, as well as providing a clearer picture regarding the momentum experienced by a student moving from high school to PSE

c - Sample size in the first column represents students who took CTE courses at any point in college. Those in the latter two columns represent only first-year coursetaking



Of note, all outcomes examining PSE in general terms look only at the first institution in which a student was enrolled. This includes the analyses in Table 3, Table 4, as well as the first two columns in Table 6. Accounting for only the first institution units earned allows for a more direct examination of the high school to college pipeline as it is quite possible that students proceed to graduate school and complete additional CTE units, which is not the focus of this study. In the analyses that separate 2-year and 4-year coursetaking patterns, we examine only the first year at the first institution. By nature, students attending 4-year colleges have more time to complete additional coursework, including CTE courses, than they would in a 2-year college. By focusing solely on the first year of enrollment in, we gain a clearer view of the high school to PSE CTE pipeline. This is the focus of our analyses in Table 5, Table 6 columns 3–6, and Table 7.  


HIGH SCHOOL CTE COURSETAKING


In addition to postsecondary transcript files, the ELS dataset also provides transcript data from high school. In the Secondary School Taxonomy, Bradby and Hudson (2007) organized students’ transcripts into four specific areas: academic, career and technical education (CTE), enrichment/other, and special education. This study focuses on those courses from the CTE category. In this broad range of CTE courses, there are 21 identified occupational course categories included in our analysis. These categories include the following: agriculture and natural resources, communications and design, computer and information sciences, health sciences, marketing, business support, business management, business finance, engineering technologies, architecture, construction, manufacturing, mechanics and repair, transportation, consumer services, culinary arts, education, library science, public administration, legal services, and protective services. Courses are coded as CTE as outlined in the classification of secondary school courses (CSSC) based on the high school transcript study of 2000 (U.S. Department of Education, 2002).


Our course variable is defined as the total number of CTE units completed in high school. Throughout this study, CTE coursetaking refers to the number of units completed. Note that we did examine the potential for a nonlinear relationship through the inclusion of a quadratic term in our models, but we found this term to be nonsignificant, and it did not improve the model fit in our estimations.


CONTROL VARIABLES


Descriptive statistics for all the control variables included in this analysis are presented in Table 2. Selected variables are grounded in previous research in CTE and coursetaking (Adelman, 2006; Bozick & Dalton, 2013; Brody & Benbow, 1990; Gottfried & Bozick, 2016; Lee & Frank, 1990; Long, Conger, & Iatarola, 2012; Riegle-Crumb, 2006; Rose & Betts, 2004; Tyson, Lee, Borman, & Hanson, 2007; Wimberly & Noeth, 2005). The 2002 base year surveys include each of the control variables, except for academic history variables, which were drawn from the 2005 transcript file update.



Table 2

  
   

Descriptive Statistics

 

 

 

Mean

Std Dev

High School CTE units

3.37

2.38

Demographic data

  

  Female

0.55

0.50

  Race/ethnicity

  

    White

0.61

0.49

    Black

0.11

0.31

    Asian/Pacific Islander

0.12

0.33

    Hispanic

0.12

0.32

    More than 1 race

0.04

0.19

    Native American

0.01

0.09

Family data

  

  Family arrangement

  

    Single parent household

0.20

0.40

    Both parents present

0.65

0.48

    Other arrangement

0.15

0.35

  Highest parental education

  

    High school degree or less

0.22

0.42

    Some college

0.35

0.48

    BA degree or higher

0.43

0.49

  Household income

  

    Lowest 25%

0.17

0.37

    Middle 50%

0.55

0.50

    Highest 75%

0.28

0.45

Academic history and attitudes

  

  9th grade GPA

2.88

0.80

CTE units as percent of total

8.59

7.00

Math units

3.39

4.07

  Importance of education

0.91

0.29

  Post-secondary expectations

  

    High school or less

0.02

0.12

    Any college

0.12

0.33

    Complete 4 year degree or more

0.81

0.39

  Math self efficacy

2.62

0.71

  Parent involvement

2.22

0.49

  Employment outside the home

0.32

0.47

  Involved in extracurriculuars

1.64

1.39

   

n

6,000

 



Demographic data included respondent gender and race/ethnicity. Family data included family arrangement, parental education, and family income. The final control variable set included academic history and attitudes. Ninth grade GPA, as noted, was sourced from the transcript files and represents academic history. Ninth grade GPA represents an appropriate proxy for overall achievement because it has been found to be more strongly connected with college success than test scores (Allensworth, Gwynne, Moore, & de la Torre, 2014). We also included a ratio term representing the number of CTE units in high school as a percentage of total units completed in high school, and the number of high school math units completed. Academic attitudes included the following: importance placed on education (binary), postsecondary expectations (binary), math self-efficacy (4-point scale), parental involvement (3-point scale), student employment (binary), and extracurricular involvement (5-point scale).


A key point to note is that only a small percentage of students (5%) did not enroll in a single CTE course. This helps to assuage concerns that only low achieving students enrolled in CTE and clarify that CTE was being accessed across the range of student abilities. This is in line with previous research identifying that high school CTE courses are not geared toward lower versus higher achieving students (Brand et al., 2013). This finding presents compelling evidence that CTE coursetaking is not being used as a means of ability tracking. To further illustrate this point, there was only a minimal correlation (-0.17) between total high school GPA and the number of CTE units completed.


ANALYTIC APPROACH


Baseline Model


In order to address our research questions, we begin with a baseline regression model, expressed as follows:


[39_22592.htm_g/00002.jpg]


where [39_22592.htm_g/00004.jpg]is a placeholder for one of the postsecondary CTE outcomes we described above (e.g., PSE CTE unit completion, PSE CTE units attempted, PSE CTE GPA, etc.) for student i in school s. On the left-hand side of the model, CTE represents the number of CTE units completed by student i in high school s, and the term [39_22592.htm_g/00006.jpg]represents the set of previously defined control variables. Finally, the error term [39_22592.htm_g/00008.jpg]is estimated with standard errors adjusted for high school clustering.


Tests of Robustness


In addition to using basic OLS regression models to respond to our research questions, we also used two separate empirical techniques to help improve our estimates.


High school fixed effects


The first technique was a school fixed effects model. Using fixed effects requires adding binary indicators for school attended into the model (Schneider, Carnoy, Kilpatrick, Schmidt, & Shavelson, 2007). In doing so, we accounted for differences that may exist between schools. For example, certain schools may have different policies regarding CTE instruction or other factors that may influence student CTE coursetaking and PSE. These differences could potentially result in an overestimation of the strength of the relationship between CTE in high school and CTE in college. Through a high school fixed effects model, all variation in the outcome variables between high schools is held constant. Therefore, the remaining variation occurs within a given school. The equation for our fixed effects models is as follows:


[39_22592.htm_g/00010.jpg]


The only difference between this model and our baseline model is the inclusion of the term [39_22592.htm_g/00012.jpg], which represents indicators for each high school s. Under this model, we removed one school from the calculations to serve as a reference category.


Instrumental variables


To further examine the sensitivity of our findings in the baseline models due to the potential for omitted variables to have biased the relationship of interest we employed instrumental variable estimation (IVE). Given a key purpose of CTE courses is to link high school content to college and careers, students with varying degrees of motivation to further pursue CTE in college may be more inclined to take more of these courses. The use of IVE helps to reduce biases that may not have been fully addressed under previous models.


IVE is a two-stage process. Each stage is represented by a unique regression. In the first stage, the relationship between our outcomes and CTE coursetaking in high school is not immediately evaluated. Instead, this first stage explores the relationship between CTE coursetaking in high school and our instrument. After estimating the coefficients in the first stage, the original outcome is returned to the equation in the second stage, while the estimated values of our main predictor value from the first stage regression are now used as the independent variable. The following equation represents the first stage regression:


[39_22592.htm_g/00014.jpg]


where CTEit represents the original independent variable, but now acts as the dependent variable in this first regression. IVis represents the instrumental variable. The final term is the error term clustered at the school level.


The key piece in this equation is the instrument. The identified instrument is based on previous studies that used national datasets to determine the effects of other types of high school coursetaking on various end of school outcomes (Altonji, 1995; Rose & Betts, 2004). Using subject-specific (i.e., math, science, social studies, English) mean coursetaking at high school s for student i to estimate later wages, Altonji (1995) reduced the overestimation bias. We calculate our instrument similarly, but instead of more traditional academic courses, we use the mean number of CTE units taken by students at school s, excluding the units taken by student i in school s. This use of the mean number of units as a viable instrument in student coursetaking studies is supported as providing a clearer estimation of the effects of high school coursetaking, net of ability and background (Rose & Betts, 2004). As CTE courses are elective courses, there is less likelihood for this instrument to be impacted by endogenous factors, whereas previous research has focused predominantly on units in required subjects (i.e., math, science, English, etc.), which are more vulnerable to potential overestimation of coursetaking effects (Altonji, 1995). Our instrument was calculated as the school average for all students in the high school net student i's CTE units at that school.


While we contend that this approach may help in reducing biases in the estimates of CTE coursetaking, the potential exists that there may still be unobserved biases. In order to address the potential for remaining bias, we correlated our instruments with a number of key aspects that may still be impacting our estimates. Using a school climate measure provided in the dataset, we found there to be only a negligible correlation (-0.07) with average CTE units taken. We also looked that the correlation between average CTE units and school peer averages of a number of other measures, such as peer 9th grade GPA (-0.07), average peer on-time graduation (-0.09), average peer dropout (0.13), and average math performance (-0.15). The evidence presented through these correlations provides strong indications that our CTE instrument may not be correlated with observed aggregate school measures.


In order to account for the potential correlation of our instrument with unobserved school-level factors, we also included school fixed effects in our instrumental variable models. Similar to a model using school fixed effects alone, this additional constraint ensures that all variation in CTE coursetaking is occurring within a given school, as opposed to between schools. All of the instrumental variable models here also include school fixed effects.


RESULTS


In interpreting these results, it is important to keep the following in mind. First, one unit of high school CTE equates to one full yearlong course (a semester long course would count as a half unit). Second, the average college course is worth three units. Therefore, a one-unit increase at the postsecondary level equates to one-third of a college course (a 0.75-unit increase would equate to one-quarter of a college course). Third, the coefficients presented represent the predicted number of additional units a student would be expected to complete in college.


POSTSECONDARY CTE


Our first research question asked whether CTE coursetaking in high school was predictive of CTE coursetaking in college. We examined four postsecondary outcomes to respond to this question—total postsecondary CTE units completed, total postsecondary CTE units attempted, postsecondary CTE GPA, and first year postsecondary CTE units completed. Table 3 presents the baseline OLS and school fixed effects estimates for each of these outcomes including all control variables. Bear in mind, these estimates examine only the first institution a student attended.



Table 3

       
         

CTE in High School's Influence on CTE in College

 

 

 

 

 

Completed CTE Units

Attempted CTE Units

CTE GPA

First Year Completed Units

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

 

OLS

School Fixed Effects

OLS

School Fixed Effects

OLS

School Fixed Effects

OLS

School Fixed Effects

High School CTE units

1.80***

2.76***

1.76***

2.95***

0.01

0.00

0.30*

0.35*

 

(0.48)

(0.65)

(0.50)

(0.68)

(0.01)

(0.02)

(0.13)

(0.16)

Demographic data

        

  Female

-0.74

-0.81

-1.35

-1.37

0.18***

0.17***

-0.31

-0.28

 

(0.82)

(0.90)

(0.86)

(0.95)

(0.02)

(0.03)

(0.16)

(0.16)

  Race/ethnicity

        

    Black

-3.53**

-0.41

-1.39

1.97

-0.37***

-0.31***

-0.34

-0.30

 

(1.30)

(1.72)

(1.37)

(1.82)

(0.05)

(0.05)

(0.30)

(0.38)

    Asian/Pacific Islander

0.70

1.85

1.41

2.63

0.00

-0.04

-0.04

-0.15

 

(1.48)

(1.83)

(1.61)

(1.90)

(0.04)

(0.05)

(0.24)

(0.29)

    Hispanic

-6.00***

-3.53*

-6.26***

-3.49*

-0.11**

-0.08

-0.92***

-0.70*

 

(1.29)

(1.67)

(1.35)

(1.75)

(0.04)

(0.05)

(0.24)

(0.30)

    More than 1 race

-3.66

-1.27

-3.50

-0.85

-0.03

-0.02

0.31

0.39

 

(1.89)

(2.10)

(1.98)

(2.23)

(0.06)

(0.06)

(0.45)

(0.48)

    Native American

-9.42**

-10.21

-9.50**

-10.96

-0.10

-0.19

0.67

-0.11

 

(3.24)

(5.57)

(3.43)

(5.81)

(0.18)

(0.20)

(0.78)

(1.05)

Family data

        

  Family arrangement

        

    Single parent household

-1.81

-1.62

-1.54

-1.39

-0.03

-0.01

0.35

0.34

 

(1.09)

(1.18)

(1.14)

(1.24)

(0.03)

(0.03)

(0.22)

(0.24)

    Other arrangement

-3.98***

-3.94**

-3.79**

-3.97**

-0.07*

-0.04

-0.13

-0.13

 

(1.09)

(1.20)

(1.15)

(1.27)

(0.03)

(0.03)

(0.21)

(0.23)

  Highest parental education

        

    High school degree or less

0.61

0.36

0.54

0.21

0.03

0.01

0.02

-0.08

 

(1.00)

(1.07)

(1.08)

(1.15)

(0.03)

(0.03)

(0.26)

(0.27)

    BA degree or higher

0.70

0.77

0.24

0.37

0.05*

0.03

-0.43*

-0.42*

 

(0.96)

(1.04)

(1.02)

(1.09)

(0.03)

(0.03)

(0.18)

(0.21)

  Household income

        

    Lowest 25%

-1.13

-0.98

-0.59

-0.71

-0.08*

-0.06

-0.27

-0.32

 

(1.18)

(1.29)

(1.21)

(1.32)

(0.04)

(0.04)

(0.28)

(0.32)

    Highest 75%

0.26

-0.54

0.68

-0.02

0.01

-0.01

0.00

0.00

 

(1.08)

(1.15)

(1.13)

(1.21)

(0.02)

(0.03)

(0.18)

(0.20)

Academic history and attitudes

        

  9th grade GPA

4.85***

4.82***

3.72***

3.55***

0.31***

0.33***

0.27**

0.17

 

(0.56)

(0.64)

(0.60)

(0.67)

(0.02)

(0.02)

(0.10)

(0.11)

CTE units as percent of total

-0.20

-0.44*

-0.16

-0.48*

0.00

0.00

0.00

-0.01

 

(0.16)

(0.22)

(0.17)

(0.23)

0.00

(0.01)

(0.04)

(0.05)

High school math units

2.09***

2.08***

2.25***

2.23***

0.03***

0.03***

0.05*

0.04*

 

(0.14)

(0.15)

(0.14)

(0.16)

0.00

0.00

(0.02)

(0.02)

  Importance of education

2.67

2.46

2.78

2.62

-0.01

-0.01

0.08

0.16

 

(1.37)

(1.44)

(1.42)

(1.49)

(0.04)

(0.05)

(0.29)

(0.30)

  Post-secondary expectations

        

    Any college

1.78

0.44

1.52

0.19

-0.05

-0.06

1.43*

1.04

 

(1.66)

(1.80)

(1.70)

(1.87)

(0.06)

(0.07)

(0.58)

(0.56)

 Complete 4 year degree or   more

5.98***

5.07***

6.29***

5.36***

0.00

0.00

-0.60

-0.57

 

(1.36)

(1.51)

(1.44)

(1.62)

(0.06)

(0.06)

(0.45)

(0.46)

  Math self efficacy

-1.18*

-1.11

-1.01

-0.86

0.01

0.00

-0.06

0.01

 

(0.59)

(0.66)

(0.63)

(0.70)

(0.02)

(0.02)

(0.11)

(0.12)

  Parent involvement

0.78

0.84

0.69

0.65

0.02

0.04

-0.03

0.08

 

(0.83)

(0.93)

(0.88)

(0.98)

(0.03)

(0.03)

(0.17)

(0.18)

  Employment outside the home

-0.71

-0.17

-0.34

0.12

-0.02

-0.02

-0.28

-0.23

 

(0.85)

(0.93)

(0.91)

(1.00)

(0.03)

(0.03)

(0.15)

(0.17)

  Involved in extracurriculuars

1.10***

1.30***

1.18***

1.36***

0.01

0.01

0.15*

0.12*

 

(0.31)

(0.33)

(0.32)

(0.35)

(0.01)

(0.01)

(0.06)

(0.06)

         

n

6,000

6,000

6,000

6,000

5,530

5,530

5,830

5,830

Standard errors in parentheses

      

* p < 0.05, ** p < 0.01, *** p < 0.001

       



The first row shows the relationship between CTE units in high school with the identified postsecondary outcomes. Across both OLS and school fixed effects models, we found that high school CTE coursetaking significantly predicted an increase in both units completed and units attempted in college. When taking into account school fixed effects in estimating PSE CTE units completed, column 2 presents a coefficient of 2.76 for high school CTE units. This indicates that for every one unit of high school, we would predict a student to take approximately 2.76 additional CTE units in college. This is equivalent to approximately one additional semester course, given that a semester course is worth three units. Considering the school fixed effects coefficient is larger than the OLS model, this suggests there was a degree of underestimation in the role of high school CTE coursetaking on college CTE coursetaking using the baseline OLS model.


A similar pattern emerged regarding the relationship between high school CTE coursetaking and the number of units attempted. Again, there was a degree of underestimation when relying on the OLS model, and thus we turn to the school fixed effects model. The fourth column shows that for every additional unit of high school CTE, a student was predicted to attempt 2.95 additional CTE units in college (again, approximately one more semester course). Unlike units completed and attempted, increased CTE completion in high school did not predict PSE CTE GPA. Finally, high school CTE unit completion predicted CTE unit completion in the first year of PSE with larger findings in the school fixed effects model.


In an effort to further reduce potential biases in the estimates, Table 4 presents the second stage IVE CTE coefficients in addition to the first-stage F-statistics for each of the models, where a value of 10 or greater indicates that the instrument is a relevant predictor of the endogenous regressor after controlling for the exogenous regressors (Staiger & Stock, 1997). Note that the control variables from Table 3 are included in the estimations although they are not presented for the sake of clarity. Similar to Table 3, high school CTE completion remains significantly associated with postsecondary CTE units completed (2.62) and attempted (2.67), while there remains no significant association with PSE CTE GPA. Using this technique, however, we did not find a significant relationship between high school CTE and the first year of CTE in PSE.



Table 4

    
     

Results from Second Stage of Instrumental Variable Estimation

 

 

(1)

(2)

(3)

(4)

 

Total Completed CTE Units

Total CTE Units Attempted

Total CTE GPA

First Year Completed CTE Units

CTE high school units

2.62***

2.67***

0.01

0.25

 

(0.78)

(0.80)

(0.02)

(0.24)

     

F-Statistic

455.22***

455.22***

513.64***

441.11***

     

n

6,000

6,000

5,530

5,830

Standard errors in parentheses

   

* p < 0.05, ** p < 0.01, *** p < 0.001

   



As was the case when comparing OLS and school fixed effects, the estimates presented here do showcase that our OLS models may have been slightly underestimating the relationship between high school and college CTE coursetaking. The estimates in Table 4 aligned more closely with those school fixed effects models. Regardless of model, however, in returning to our initial research question regarding the relationship between high school CTE coursetaking and PSE CTE coursetaking, an overall theme has emerged—there does appear to exist an overall positive pipeline between high school and postsecondary CTE coursetaking.


2-YEAR AND 4-YEAR POSTSECONDARY CTE


Our second research question asked whether the 2-year and 4-year college CTE pipeline was noticeably different. Table 5 shows the pipeline differences between 2-year and 4-year colleges. Note that each cell represents a CTE coursetaking coefficient from a unique regression, which also included all control variables from Table 3. We do not present basic OLS results as school fixed effects and IVE coefficients are potentially less biased. It is important also to note that these analyses looked only at the first year of PSE coursetaking as mentioned above.


As can be seen in the second column, the coefficient from the IVE/school fixed model—which provides a less biased result than school fixed effects alone—associated with 4-year CTE unit completion (0.86) was significant, while that for 2-year colleges (-0.15) was not. These results indicate that a one-unit increase of CTE in high school predicts completing nearly one additional unit during the first year at a 4-year college, while there is not a predictive relationship with 2-year colleges. This pattern held in the estimations looking at credits attempted. Once again, there was no relationship with PSE CTE GPA. Regarding our second research question, there does appear to be a differential relationship in the CTE pipeline between 2- and 4-year colleges.



Table 5

      
       

College CTE Outcomes by 2-year or 4-year College (First Year Only)

 

 

 

Total Completed CTE Units

Total Attempted CTE Units

Total CTE GPA

 

(1)

(2)

(3)

(4)

(5)

(6)

 

School Fixed Effects

Instrumental Variables

School Fixed Effects

Instrumental Variables

School Fixed Effects

Instrumental Variables

2-year College

      

CTE high school units

0.18

-0.15

0.20

-0.20

-0.01

0.00

 

(0.31)

(0.50)

(0.31)

(0.50)

(0.04)

(0.05)

       

F-Statistic

 

361.53***

 

361.53***

 

220.11***

       

n

2,750

2,750

2,750

2,750

1,600

1,600

 

 

 

 

 

 

 

4-year College

      

CTE high school units

0.63**

0.86**

0.53*

0.75**

0.01

0.04

 

(0.22)

(0.27)

(0.23)

(0.29)

(0.05)

(0.06)

       

F-Statistic

 

219.87***

 

219.87***

 

186.82***

       

n

3,070

3,070

3,070

3,070

1,910

1,910

Standard errors in parentheses

     

* p < 0.05, ** p < 0.01, *** p < 0.001

    



The results were interesting in that it appeared that high school CTE coursetaking was more predictive of CTE coursetaking in 4-year colleges. Our guiding theory suggested that the CTE pipeline would at least be predictive of 2-year CTE coursetaking, if not more so than in 4-year colleges. One possible explanation for this unexpected result is that CTE itself is such a broad categorization that certain, more specific, categories of CTE are related to postsecondary coursetaking in different ways—some positively, some negatively. Therefore, in order to gain additional insight into this discrepancy, we disaggregated the broad CTE umbrella category into smaller, more well-defined areas.


POSTSECONDARY CTE CATEGORIES


Our third research question examined whether the CTE pipeline varied based on different categories of CTE. As mentioned above, we identified four specific categories—applied STEM, business, trade and industry, and health. Seeing as units completed and units attempted were consistently similar across all our estimations, we focused solely on total units of CTE completed in PSE as our outcome of interest in this analysis. Table 6 presents the results of these estimations.



Table 6

        
         

Outcomes by CTE Categorya

 

 

 

 

 

Total Completed CTE Units

First Year Completed CTE Units

First Year CTE Units: 2-Year Students

First Year CTE Units: 4-Year Students

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

 

School Fixed Effects

Inst. Variables

School Fixed Effects

Inst. Variables

School Fixed Effects

Inst. Variables

School Fixed Effects

Inst. Variables

Applied STEM

        

High school CTE units

2.86***

4.54***

0.28***

0.47***

0.17

0.37**

0.37***

0.55***

 

(0.44)

(0.57)

(0.07)

(0.10)

(0.12)

(0.14)

(0.11)

(0.16)

         

F-Statistic

 

291.28***

 

277.46***

 

236.24***

 

137.35***

Business

 

 

 

 

 

 

 

 

High school CTE units

2.89***

3.77***

0.26***

0.34***

0.28***

0.38***

0.27***

0.30***

 

(0.37)

(0.47)

(0.04)

(0.06)

(0.06)

(0.09)

(0.07)

(0.06)

         

F-Statistic

 

813.13***

 

790.03***

 

395.31***

 

458.11***

Trade and Industry

 

 

 

 

 

 

 

 

High school CTE units

1.22***

2.90***

0.34***

0.72***

0.39***

0.78***

0.22

0.55*

 

(0.22)

(0.45)

(0.07)

(0.15)

(0.10)

(0.22)

(0.11)

(0.24)

         

F-Statistic

 

122.76***

 

121.32***

 

99.51***

 

71.73***

Health

 

 

 

 

 

 

 

 

High school CTE units

4.87***

5.53***

0.21*

0.21

0.05

-0.03

0.27

0.32

 

(0.94)

(1.15)

(0.10)

(0.12)

(0.21)

(0.27)

(0.15)

(0.18)

         

F-Statistic

 

211.56***

 

201.06***

 

713.39***

 

93.81***

         

n

6,000

6,000

5,830

5,830

2,750

2,750

3,070

3,070

Standard errors in parentheses

    

* p < 0.05, ** p < 0.01, *** p < 0.001

    

a  - We did include all other CTE areas into a single “other CTE” grouping, but since these areas did not share a common theme, we chose to exclude them from our analyses.



In Table 6, each coefficient represents the CTE coursetaking coefficient from a unique regression, including all control variables as seen in Table 3.  Note that each outcome is category specific depending on the model. In the first section, the outcomes are applied STEM units. In the second section, the outcomes are business units. In the third section, the outcomes are trade and industry units. In the fourth section, the outcomes are health units.


Across our three identified CTE categories, high school CTE was significantly predictive of increased CTE unit accumulation in college in each of these categories, as seen in columns 1 and 2. These analyses examined PSE coursetaking across the length of time a student was enrolled in his/her first institution. Students who took more applied STEM courses in high school took more applied STEM courses in college. Students who took more business courses in high school took more business courses in college. Students who took more trade and industry courses in high school took more trade and industry courses in college, and high school health courses linked to health courses in college. Of all models, the health category had the largest coefficients across PSE. The results imply that for every additional year of health CTE in high school, it would be expected that students would complete nearly two more CTE courses in college.


In columns 3 and 4, we limited the outcome to only first year postsecondary unit completion. Using this outcome, there remained a significant relationship across all categories except for health. This lack of a significant result in the health category during the first year suggests that students tend to take a majority of health classes later in their postsecondary careers. During the first year of PSE, trade and industry had the largest coefficient at 0.72, indicating that one additional year of trade and industry coursework in high school predicts nearly one-fourth of an additional course in college.


Once credit completion was broken out by 2- and 4-year college attendance, some key differences began to shine through. The outcomes here are representative of the courses completed during a student’s first year in PSE. In the applied STEM category, high school coursework predicted both 2- and 4-year college applied STEM. However, the coefficient for 4-year college (0.55) was slightly larger than that for 2-year college (0.37). Across business CTE courses, the results were reversed. High school CTE more strongly predicted business CTE in 2-year colleges than in 4-year colleges. In 2-year colleges, each additional high school business CTE unit was associated with an additional 0.38 units completed during the first year, while the relationship to 4-year college business CTE was slightly lower at 0.30 units. Trade and industry CTE coursetaking also linked more closely (0.78) at the 2-year level than at the 4-year level (0.55). Health, however, was significant at neither level of PSE for the first year.


In reference to our third research question, the results here suggest that examining CTE as a general category may not accurately identify the true nature of the coursetaking pipeline(s) between high school and college. Instead it is necessary to examine pieces of CTE individually to observe these individual relationships. In addition to observing these direct pipeline connections within categories, we found negative cross-category connections in some cases. This result further supports our theory that CTE categories have unique pipelines. It also supports our theory regarding why CTE as a broad category was unable to capture the link between high school CTE coursetaking and 2-year college CTE coursetaking.


POSTSECONDARY MATH COURSETAKING


A potential issue with the tightening of a CTE coursetaking pipeline is that students might forego enrollment in other courses. Given that mathematics courses serve as scaffolding for later learning, and as a proxy for overall educational attainment, it is important that CTE is not acting to crowd out the progression through the math pipeline. In order to alleviate these concerns, we looked at whether there was a negative relationship between increased high school CTE coursetaking and PSE math units completed and math GPA in college. Table 7 presents the results of these coefficients, again with all other control variables included in the model though not presented for clarity. If CTE units in high school were crowding out math coursework in college, we would have expected to see a negative relationship between CTE in high school and math in college. However, as can be seen, there exists no relationship between high school CTE and postsecondary math. In addition to a null relationship between CTE units in high school and postsecondary math unit completion, there was also no relationship with GPA in math courses in college. These null results are positive signs for CTE coursetaking in high school. As previous legislation has worked to more closely integrate CTE with more academic coursework (Dougherty & Lombardi, 2016), a non-negative impact on academic math courses in college indicates these efforts are exhibiting some success.



Table 7

    
     

Math Outcomes in College

 

 

 

 

Total Math Units Completed

Math GPA

 

(1)

(2)

(3)

(4)

 

School Fixed Effects

Instrumental Variables

School Fixed Effects

Instrumental Variables

CTE high school units

0.08

0.03

-0.06

-0.03

 

(0.09)

(0.13)

(0.04)

(0.05)

     

n

5,540

5,540

3,470

3,470

Standard errors in parentheses

   

* p < 0.05, ** p < 0.01, *** p < 0.001

   



DISCUSSION


Given the increased demand for more and more technical skills in rising cohorts of college graduates (Bureau of Labor Statistics, 2013), CTE coursetaking has continued to gain prominence across the United States. No single reason exists for this demand. Perhaps it is in response to a national sentiment to more effectively align the K12–college-career pipeline, where the skillsets learned throughout schooling could have more direct applications to employment opportunities. Perhaps it is due to federal investments in CTE programs. In this case, with the pending reauthorization of the “Perkins Act,” the time has never been more pertinent to assess whether CTE coursetaking is an efficacious way to align the nodes of this pipeline.


With the rise of CTE coursetaking across the nation, there has been a burgeoning body of research examining whether taking CTE coursework in high school aligns with improved student outcomes, both in high school and college (Association of Career and Technical Education, 2009; Bozick & Dalton, 2013; Gottfried, 2015; Gottfried, Bozick, & Srinivasan, 2014; McCharen & High, 2008; Plank et al., 2008; Stone et al., 2008). These studies provide evidence of a link between high school CTE and higher math achievement or a greater likelihood of majoring in certain fields. Missing, however, from this field has been an examination of whether CTE coursetaking in high school aligns with CTE coursetaking in college. This has been an oversight, given that understanding whether there are CTE “coursetaking pipelines” between high school and college would help elucidate more clearly the path as to where skills are being accumulated throughout schooling.


To address this gap, we examined coursetaking patterns for a national cohort of students as they progressed from high school to college. Having access to full high school and college transcript data, it was possible to link CTE coursetaking across the pipeline. The results of our analyses suggested evidence of a coursetaking pipeline. More CTE units taken in high school predicted more CTE units taken in college. In fact, the relationship was almost one-to-one: each yearlong CTE course taken in high school predicted an approximate one-semester course taken or attempted in college.


This is an important finding as it shows students do choose to pursue additional CTE in college after having taken CTE in high school. Students may be laying the foundation for a solid skill base in high school and then building upon those skills through further CTE taking in PSE. This is a key result, as it points to the existence of the second node in the CTE pipeline—PSE coursetaking. An implication of this finding is that CTE in high school, which is itself funded through the current iteration of the Perkins legislation, appears to have a noticeable link to CTE participation in college. Policymakers and legislators busy debating about whether to reauthorize Perkins may have a keener insight into the “returns” to the legislation as a result of this study.


Our second research question inquired into whether there were general differences between 2- and 4-year college students with regard to CTE coursetaking in college. The results suggested that high school students who attended 4-year colleges took more CTE courses in college based on the number of CTE courses they took in high school. On the other hand, there was no evidence of a strong coursetaking pipeline for 2-year college students. This finding was surprising given the long history of CTE partnerships between high schools and local 2-year colleges. However, while these results may suggest that the push to connect CTE in high school specifically with CTE in 2-year colleges is not effective, a closer look shows this is not necessarily the case. As mentioned above, students who go on to attend 2-year colleges complete significantly more CTE units in high school. This shows that there could very well be a strong connection between high school CTE and 2-year enrollment that is not reflected in first year CTE coursetaking at the 2-year level. One potential explanation is that the connections to 2-year CTE coursetaking are more limited in scope than a broad CTE category, and that students choose 2-year colleges for more specific CTE needs.


Our third research question delved into more detail about the nature of the CTE coursetaking pipeline. Our findings suggest that the CTE coursetaking pipelines are indeed specific to categories of CTE. For instance, students who took applied STEM CTE courses in high school took more applied STEM courses in college, with a pattern that was approximately one course to one course. Business CTE course takers exhibited a similar pattern. The link between high school and college trade and industry CTE coursetaking was slightly weaker, where two high school courses were predictive of one semester college course in this area. The patterns were also differentiated for 2- and 4-year college students. For applied STEM and business categories, the pipeline was stronger for 4-year college students. On the other hand, in trade and industry, the pipeline was stronger for 2-year college students.


The implications from our third question are fairly broad. First, the differential connections dependent on CTE category suggest there are indeed unique pipelines within CTE. Moving forward, future legislation may focus on these categories more specifically in order to foster skill-building in each area. Additionally, the different 2-year and 4-year pipelines across categories suggest that while there have been efforts to connect high school CTE closely with 2-year colleges, there is still work to be done, especially in the areas of applied STEM and health. This becomes an even more pressing issue as occupations in the health sector requiring less than a 4-year degree continue to grow. Finally, while looking at first-year unit completion is a necessary method for comparing 2- and 4-year pipelines, it does not tell the entire story for certain categories. Specifically, in the health category there is a strong overall pipeline between high school and postsecondary coursetaking, but this connection is not present at the first-year. This provides even more evidence for the necessity to examine CTE in smaller categories.  


In summary, the results of our analyses here showcase a general relationship between CTE coursetaking in high school and increased CTE coursetaking in college. For students attending 4-year colleges after high school, this relationship was particularly salient. For students attending 2-year schools, CTE coursetaking in high school was not paired with increased CTE course taking in college, in general. However, we found evidence of increased college CTE coursetaking in the specific CTE cluster of trade and industry. This last point may be evidence of the obvious for those familiar with 2-year colleges and the goals and career trajectories of the students who attend them. However, for others this result may be a worrisome indicator of stratification within the CTE pipeline, one that may be a harbinger of subsequent stratification in the labor market and beyond. Regardless, this finding along with the others we previously covered would have remained hidden were it not for the empirical analyses contained in the current study.


LIMITATIONS


Our study is the first to examine a CTE high school to CTE college pipeline in coursetaking. Therefore, the limitations of our work can serve as a foundation for future research in this area. For instance, one limitation of the current study is that, while the analytic sample was large and nationally representative, like many secondary data sources we did not have control over the selection of students into CTE courses in high school or in college. We sought to address this limitation with robust modeling strategies including IVE, though it is likely the case that legislators wanting definitive proof of a causal link between Perkins and increased CTE coursetaking in college will need to wait for a future study that employs random assignment or exploits a natural experiment.


Second, while we were able to disaggregate our CTE measure into more refined categories for STEM, business, trade and industry, and health, the sample sizes were limited for evaluating the heterogeneous “other” category. With a larger sample, perhaps using administrative statewide data that connects high school and college coursework, it would be possible to gain the statistical power to examine these other CTE categories. Our dataset does allow for nationally representative conclusions yet has limited power for strands in the “other” category, yet relying on statewide data, however, does potentially limit generalizability, and thus there are tradeoffs with every dataset.


Finally, while we were able to rely on rich transcript histories in both high school and college for our sample of students, there was no information on course content. Future research might consider a smaller-scale study where an examination of CTE instructional practices and content might be examined. Findings from such a study would help to elucidate on the hypothesized mechanisms put forth in this article. Together, our study and future research can begin to construct a broad yet detailed portrait of CTE coursetaking pipelines and potential reasons for their persistence between nodes of education.



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Cite This Article as: Teachers College Record Volume 121 Number 3, 2019, p. 1-32
https://www.tcrecord.org ID Number: 22592, Date Accessed: 10/28/2021 5:19:23 AM

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About the Author
  • Jay Stratte Plasman
    University of California Santa Barbara
    E-mail Author
    JAY STRATTE PLASMAN is a PhD candidate in the Education Policy, Leadership, and Methodology program in the Gevirtz Graduate School of Education at the University of California, Santa Barbara. His research focuses on college and career readiness, particularly concerning career and technical education and federal education policy.
  • Michael Gottfried
    University of California Santa Barbara
    E-mail Author
    MICHAEL A. GOTTFRIED is an Associate Professor in the Gevirtz Graduate School of Education. His research focuses on the economics of education and education policy. Recent publications include “Linking Getting to School with Going to School,” an Educational Evaluation and Policy Analysis.
  • Cameron Sublett
    Pepperdine University
    E-mail Author
    CAMERON SUBLETT is an Associate Professor of Education in the Graduate School of Education and Psychology at Pepperdine University. His research examines policy, leadership, and research methods in K–16 education contexts.
 
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