What We Do (and Don't) Know About Noncredit Workforce Programs

The federal government, states, institutional leaders, and researchers are striving to understand the entirety of workforce offerings in the United States. But there is a huge blind spot: noncredit offerings. While colleges, states, and the federal government collect data on for-credit offerings, the data on noncredit offerings, student participation, and outcomes is fragmented—and sometimes nonexistent.

That’s why a team led by Michelle Van Noy of Rutgers University and Mark D’Amico of the University of North Carolina at Charlotte, along with Peter Bahr of the University of Michigan and Di Xu of the University of California, Irvine, are investigating what data is available on noncredit programs at the state level. Through the State Noncredit Data Project, the researchers studied the data collected on noncredit offerings in Iowa, Louisiana, and Virginia.

They defined noncredit offerings to include occupational trainings that prepare students for employment, sponsored trainings developed for a particular employer or industry, pre-college programs such as GED preparation or ESL courses, and personal interest courses driven by local demand. Noncredit offerings might lead to completion of certificates from the colleges, industry certifications, occupational licensure, apprenticeships, and microcredentials, but they do not have to.

Here is what the researchers found from defining data elements, identifying what data is collected, and analyzing trends from the available data:

The Variety of Noncredit Offerings

There are a lot of noncredit offerings. The researchers counted 924 unique offerings at 15 community colleges in Iowa, 396 at 12 community colleges in Louisiana, and 6,045 across the 23 Virginia Community College System (VCCS) institutions.

Most of these offerings are occupational trainings. They represented over 65 percent of Iowa’s programs, nearly 80 percent of Louisiana's, and 82 percent of Virginia’s.

Across the states, the required contact hours for these programs ranged from one to 1,080. Multi-course programs were the minority at only 11 percent of offerings in Iowa and less than 3 percent in Louisiana. Occupational trainings tend to require more contact hours. In Louisiana, for example, less than 3 percent of all programs were multi-course, but 27 percent of occupational trainings were multi-course.

Funding for Noncredit Programs and the Impact on Data Collection

As students generally cannot access Title IV financial aid for noncredit programs, individual colleges can explore innovative financing approaches to maintain these programs and keep them affordable, and they can advocate for policy changes that would create sustainable funding at the federal level. States can also provide funding for noncredit programs or allow students to apply state scholarships to these programs. These three states have diverging approaches to funding noncredit programs.

Iowa is an outlier in that the state has funded noncredit programs since 1999 through a formula that considers programs’ three-year enrollment averages. To receive state funding, programs must “present value” by leading students’ to earn a credential, requiring at least 32 contact hours, or meeting a state-mandated or other community need. Four other state programs also provide funding, some directly to students.

Virginia funds FastForward programs via a “pay-for-performance model” in which the state, students, and colleges share the cost. Students pay one-third of the program cost when they start. Then, the state pays another one-third if the student completes, the state pays the remaining two-thirds if the student receives an industry-recognized credential within six months of completing, or the student pays another one-third if they don’t complete. Virginia also provides some funds to support curriculum development and technology for other noncredit programs, as well as some funding directly to low-income students via the Get A Skill, Get A Job, Get Ahead program.

On the other end of the spectrum, less than one percent of Louisiana's noncredit offerings receive a state reimbursement. While the state does not directly fund noncredit programs, the M. J. Foster Promise Program provides students aged 21 and older with up to $6,400 over three years to pursue an associate degree or workforce credential, including noncredit programs, in five in-demand industries.

State funding impacts what data gets compiled. This is perhaps most evident in Virginia, where data for the FastForward programs was more complete than data for other offerings, due to mandatory reporting to the state. Likewise, because Iowa has funded noncredit programs for two and half decades, the state has a more robust repository of data on these programs than most other states. The link between state funding and data collection suggests that states and systems could build better data repositories on noncredit workforce programs by providing new or additional funds and tying those funds to required reporting.

The Availability of State-Level Data on Noncredit Programs

Only one data element was available for all offerings in all three states: the course or program name. Other data elements were often available (the CIP code, noncredit type, completion rate, contact hours, modality), while others were variable or often missing (the SOC code, type of credential, if work-based learning was required).

One of the more concerning incomplete data is students’ demographic backgrounds. In Iowa, over one-third of students’ race/ethnicity was not recorded. In Virginia, this data was missing for more than two-thirds of students. Gender was recorded more consistently than race and ethnicity but was still not always available.

Without this data, state officials cannot analyze inequities within and across programs. What comparison could be made from the remaining data suggested that Black and Hispanic students were overrepresented in noncredit programs compared to their participation in for-credit coursework. In Louisiana, for example, of the students in occupational programs whose race/ethnicity was recorded, 51 percent were Black and 42 percent were white. Meanwhile, students enrolled in for-credit coursework were 40 percent Black and 42 percent white.

Labor market data is another important data element that is not consistently available. Virginia has labor market data available for all offerings, but the data is still limited. Because it comes from the state’s unemployment insurance system, it might not be available if students didn’t provide their Social Security Numbers, are self-employed or federal employees, or work outside of Virginia. In Iowa, labor market outcomes data was available for nearly 43 percent of occupational training offerings. In Louisiana, no more than 10 percent of offerings had labor market outcomes.

Ideally, states will collect labor market data so they can understand how programs lead to workforce and economic development. For example, by linking student enrollment with labor market outcomes, states can understand which and how many people have the certifications needed to enter into certain occupations.

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