By Karina Beltrán

On February 4, 2024, the TRIO programs at UTK ERO proudly represented our university and center at the annual conference of the Southeastern Association of Educational Opportunity Program Personnel (SAEOPP) in Savannah, GA. This significant event brought together over 500 TRIO professionals from across eight states, underlining the importance and impact of TRIO programs in fostering educational opportunities and support. The conference serves as a platform for sharing insights, strategies, and successes among professionals dedicated to expanding educational access and success for underrepresented students. Among the highlights were presentations from ERO Center’s very own staff, who shared their expertise and innovative approaches to addressing the unique challenges faced by their program participants.

Our Educational Opportunity Center (EOC) project director Stephanie Langley and one of our EOC educational specialists Caroline Milne, delivered a compelling presentation titled “Getting Back on Course: Closing the Education Gap for Formerly Incarcerated Adults.” Their talk focused on the critical work being done with system-involved individuals, showcasing the strategies and programs designed to reintegrate formerly incarcerated adults into educational settings. Their presentation not only highlighted the successes but also served as a guide for other TRIO programs looking to implement similar initiatives. In another session, our Academic Enrichment Upward Bound project (AEUB) director Charles White and our AEUB educational specialist Liaren Gladfelter presented “How to Teach Everything Your Students Ever Wanted to Know but Were Afraid to Ask.” This presentation addressed the challenges of teaching difficult but necessary topics to the populations served by TRIO programs. They offered practical advice and techniques for successfully engaging students in these critical conversations, thereby enhancing their educational experience and life skills.

The SAEOPP conference was an opportunity for TRIO professionals to learn from one another, share best practices, and celebrate the achievements of programs that make a significant difference in the lives of students across the Southeastern United States. The participation of the ERO Center’s TRIO programs not only underscored their commitment to educational equity and success but also positioned them as leaders in the field, willing to share their knowledge and experience for the betterment of all TRIO initiatives.

For more information about the SAEOPP and the impactful work being done through TRIO programs, please visit https://www.saeopp.org/about-us. This conference reaffirms the essential role that these programs play in breaking down barriers to higher education and supporting students in their journey toward academic and personal success.

I’ve been on ChatGPT a lot lately and—apparently—I’m not the only one. I’m not actually using it (though I intend to); I’m there to gawk over what it can do—and, spoiler, it goes well beyond producing first-year term papers. At a recent social gathering, one of my colleagues demonstrated that—if given a fictional research question—the generative artificial intelligence behind ChatGPT can write nearly flawless computer code for a certain syntax-based statistical package commonly used among policy-researcher types, like myself. It was humbling; I’ve spent years learning to write such code, to middling ability. As you might imagine, this demonstration led to some inevitable—and now ubiquitous—hand-wringing about automation and the implications for society.

After Career and Technical Education (CTE) month in February, my mind naturally returned to an area of inquiry I’ve had for some time now: To what degree can automation affect the career outcomes of graduates of CTE programs? I’ve done some preliminary digging and have an idea, but a quick CTE primer is a useful starting point.

Today’s “career and technical education” is yesterday’s “vocational education,” though not really. Like previous iterations, contemporary CTE focuses on equipping high school and community college students with technical skills that are closely tethered to specific workforce applications—think carpentry or plumbing. By contrast, courses and programs within the “academic” curriculum emphasize subject-matter knowledge and the development of broadly applicable skills—think history, science, language studies, etc.

Modern-day CTE advocates would argue the similarities to former vocational education models end there, however, and would likely (and rightly) assert that making the “academic” versus “vocational” education distinction is a bit anachronistic given the college- and career-readiness movement, and material changes to federal CTE legislation have, over time, successfully blurred the lines between the two. There’s a collective (and bipartisan!) sense that these changes have steered CTE in a positive direction, toward “relevance and rigor,” and away from its “dark history” of tracking disadvantaged students into low-wage, low-opportunity occupations.

My recent ChatGPT experience has me wondering about this consensus opinion, however. Let me explain.

To begin, jobs requiring skills that are difficult to automate with available technologies are at lower risk of automation. These skills include things like two-way communication, critical thinking, creativity, planning, management, and problem-solving. These are transferable skills, not technical skills. Career and technical education courses and programs need to equip students with both. Not only will the combination of technical and transferable skills help CTE students compete for the automation-resilient jobs of today (which tend to require bachelor’s degrees), the combination will give them greater agility when automation threats come knocking tomorrow.

This shouldn’t be a stretch; a key element of contemporary, “rigorous and relevant” CTE is a push to better integrate academic content within technical learning contexts. The concern I have is that “academic integration” is mostly open to interpretation, and there’s not a lot of guidance for how to do it well across the16 different trades-based (e.g., Architecture & Construction, and Manufacturing), service-based (e.g., Education & Training and Human Services) and tech-based (e.g., Information Technology and Science, Technology, Engineering and Mathematics (STEM)) CTE fields of study or “career clusters.” There’s also little accountability for academic integration baked into federal policy. Consequently, states, districts, schools, and teachers take different approaches to academic integration, and some approaches are more successful than others.

The importance of—and challenges to—carving out space in every CTE classroom in every CTE career cluster for the development of transferable, nontechnical skills becomes especially salient when you analyze automation risks across the different CTE career clusters. To do this, I merged Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OEWS) data with an available automation-risk index that assigns each occupation an individual risk score. This particular index has a base of 100; occupations with a score above this base have higher risks of automation, and occupations below the base have lower risks of automation. I calculated the average automation risk (weighted by total 2019 employment) for each CTE career-cluster area by entry education level (see Figure 1). Several things stand out.

Note: AFNR = Agriculture, Food & Natural Resources, AC = Architecture & Construction, AV = Arts, A/V Technology & Communication, BM = Business Management & Administration, ED = Education & Training, FIN = Finance, GOV = Government & Public Administration, HS = Health Science, HOSP = Hospitality & Tourism, HUM = Human Services, IT = Information Technology, LAW = Law, Public Safety, Corrections & Security, MAN = Manufacturing, MARK = Marketing, STEM = Science, Technology, Engineering & Math, TRAN = Transportation, Distribution & Logistics. Source: Bureau of Labor Statistics Occupational Employment and Wage Statistics.

First, average automation risks decrease as education level goes up, largely because jobs requiring bachelor’s degrees involve a greater number of transferable skills that are less easy to automate. Second, some CTE career-cluster areas have average automation risks that are low: Education & Training, Health Sciences, Information Technology, and Science, Technology, Engineering and Math. Other CTE career-cluster areas have automation risks that are high: Architecture & Construction, Hospitality & Tourism, Manufacturing, and Transportation, Distribution & Logistics. Third, the gap between the lowest and highest levels of education is greatest in clusters with the highest aggregate automation risk, which suggests the academic-integration hurdle is higher in these clusters compared with others.

All this matters because existing research indicates CTE participation can be stratified by race, gender, income, and rurality. Consequently, some student groups may be overrepresented in at-risk clusters. In other words, exposure to automation risk can be correlated with student characteristics. And if our efforts to equip these students with automation-resilient, transferable skills are not successful in these clusters, we risk the possibility of, once again, funneling disadvantaged students into low-wage, low-opportunity occupations. CTE’s “dark history” becomes its future.

Can contemporary CTE shield students against risks posed by automation? Absolutely. In theory, CTE students should be better prepared for automation. The pieces are there; done right, academic integration, work-based learning, the Comprehensive Local Needs Assessment, and apprenticeship models can work to close the gap between the skills students have and the skills employers need, today and tomorrow. And the “special populations” set-aside now within federal CTE legislation that requires providers to allocate funds toward recruiting low-income, disabled, and racially marginalized students into CTE should help diversify cluster pipelines and mitigate tracking. It’s always been important to get these things right, but the arrival of ChatGPT means it’s now more important than ever.