College Recruiting Targets 'Richer, Whiter High Schools'

high school student diversity 

An ongoing joint data science project at two institutions has found that while colleges and universities claim to care about access for low-income students and people of color, the students they recruit are neither. The research, undertaken by the University of California Los Angeles and the University of Arizona, found that colleges tend to recruit at "richer, whiter high schools."

Researchers used data about off-campus recruiting visits that were referenced on publicly posted admissions websites during 2017. Automated programs also collected data during that period about participation in national college fairs and "group travel tours." Income data from the census was matched to a given high school using its zip code. The initial reporting covers 42 institutions, 16 public research institutions, 13 private research universities and 13 private liberal arts colleges; however, the complete reporting will examine data from more than three times as many schools.

Knowing which high schools received recruiting visits "is important," the researchers wrote in an op-ed article for the New York Times, "because debates about access to higher education often focus on students' abilities but ignore how colleges identify and prioritize prospects." These visits influence where students apply and enroll, they noted. That's especially true among "smart kids from less affluent backgrounds," who want to feel "wanted."

The big reveal: Public high schools in more affluent areas "receive more visits than those in less affluent areas." For example, among the high schools Rutgers University visited, the median neighborhood income was $117,600; the median income for high schools skipped by recruiters was $67,000. For Stony Brook U, schools visited were in neighborhoods with a median income of $110,800; unvisited school communities had median incomes of $68,500.

Among the public research universities, recruiters in-state "visited rich and poor neighborhoods equally"; however, out of state, they "visited the same affluent high schools targeted by private colleges." As an example, the University of Georgia in-state visits focused on high schools in communities with an average median income of $63,000; for out-of-state visits, that income was $103,200. For North Carolina State University in Raleigh, the in-state income was $52,000; the out-of-state income was $122,900.

This focus on enrolling non-residential students is a stop-gap measure in response to state cuts in funding for higher education, the researchers suggested; those out-of-state students pay two to three times more than state residents for the same education.

Colleges and universities were also more likely to recruit at white schools than majority minority schools. One example cited was the University of Colorado Boulder, which visited a Massachusetts high school that was 88 percent white and had 154 students with proficient math scores; it failed to visit another high school about 30 miles away, where just 21 percent of students were white but had about 622 students with proficient math scores. The university's excuse: It focuses on schools "that have historically given us applications."

As the researchers concluded, too often poor students with great grades "end up going to a community college because no one bothers looking for them." If higher education were serious about socioeconomic and racial diversity, "they should look for merit everywhere, not just in wealthy, white communities."

The Off-Campus Recruiting Research Project links to an interactive map, graphs and charts and the methodology are openly available on the Enrollment Management, Recruiting & Access website.

About the Author

Dian Schaffhauser is a former senior contributing editor for 1105 Media's education publications THE Journal, Campus Technology and Spaces4Learning.

Featured

  • glowing digital human brain composed of abstract lines and nodes, connected to STEM icons, including a DNA strand, a cogwheel, a circuit board, and mathematical formulas

    OpenAI Launches 'Reasoning' AI Model Optimized for STEM

    OpenAI has launched o1, a new family of AI models that are optimized for "reasoning-heavy" tasks like math, coding and science.

  • landscape photo with an AI rubber stamp on top

    California AI Watermarking Bill Supported by OpenAI

    OpenAI, creator of ChatGPT, is backing a California bill that would require tech companies to label AI-generated content in the form of a digital "watermark." The proposed legislation, known as the "California Digital Content Provenance Standards" (AB 3211), aims to ensure transparency in digital media by identifying content created through artificial intelligence. This requirement would apply to a broad range of AI-generated material, from harmless memes to deepfakes that could be used to spread misinformation about political candidates.

  • clock with gears and digital circuits inside

    Report Estimates Cost of AI at Nearly $300K Per Minute

    A report from cloud-based data/BI specialist Domo provides a staggering estimate of the minute-by-minute impact of today's generative AI boom.

  • glowing lines connecting colorful nodes on a deep blue and black gradient background

    Juniper Intros AI-Native Networking and Security Management Platform

    Juniper Networks has launched a new solution that integrates security and networking management under a unified cloud and artificial intelligence engine.