Equity at the Center: How Federal Policymakers Can Support Diverse Student Populations in CTE Pathways Through High-Quality Data

By Kayla C. Elliott, Ph.D. and Natalie Truong

In the mid-19th century, railways in the United States consisted of dozens of small local networks with limited range. As the industry grew, private operators began to work together to standardize mechanisms, maximize profits, and minimize costs. Not until Congress passed the Pacific Railway Act in 1862 did a national effort begin to link all the disjointed pieces into one truly transcontinental railroad. Eventually, four of the five transcontinental railroads built used funding from federal land grants.

After their completion, these coast-to-coast connections decreased the time and cost of shipping and travel, increased trade between states, and spurred additional routes. A similar unification of the country’s current Career and Technical Education (CTE) pathways into a cohesive federal system has the potential to standardize goals and metrics, maximize employment, and minimize inequities for learners and workers who all too often get stranded and left behind.

CTE pathways have no shortage of operators. They include the U.S. Department of Labor and U.S. Department of Education, and their state counterparts, kindergarten-to-12th grade (K-12) schools and school systems, colleges and other postsecondary providers, employers, intermediaries, and associations. This wide network of actors facilitates courses and programs that provide the skills and knowledge required for specific jobs or fields of work. High-quality education and career pathways can help learners transition into high-demand, higher-wage careers. Unfortunately, just as the early railways profited from the exploitation and exclusion of Asian, Black, and Native Americans, current CTE pathways uphold the historic practice of tracking today’s students of color into programs that lead to low-wage positions in the U.S. labor market.

Truly high-quality data would finally help stakeholders identify communities of color who are currently lost or inaccessible, such as Afro Latinos, Southeast Asian Americans, and immigrant students, including undocumented students and newcomer students who have recently arrived in the United States. The collection of data on CTE pathways should focus on program-level outcomes to facilitate the identification of learner populations in need of additional supports and interventions. Quality data allow stakeholders to understand which programs are equitably serving, supporting, and retaining students, and which programs need improvement.

These data can help decision-makers understand and assess program quality, success, and outcomes for different learner populations. Truly high-quality data would finally help stakeholders identify learners in communities of color, such as Afro Latinos, Southeast Asian Americans, and undocumented and newcomer immigrants, who are currently invisible in data.

Click here to read the full issue brief.