Journal Articles

Multiple studies show that outcomes, whether they be better degree completion rates or successful short-term workforce training, are negatively affected by inadequate funding (Kahlenberg, 2015). To bolster their case for underfunding, researchers and college advocacy groups produce studies that rely on an important federal dataset–the Integrated Postsecondary Education Data System (IPEDS)–which attempts to standardize input and output measures among colleges and make comparisons over time possible. This article is about how the use of this national database can lead to a distorted picture of community colleges that can produce incorrect and possibly counterproductive public policy. IPEDS, or sometimes the way that it is used, shortchanges the community college in several ways. This article will discuss three of them, which result in an undercounting of student enrollment at community colleges and, therefore, either directly or indirectly, have a negative impact on funding. The three problems with common uses of IPEDS data are: (1) measuring enrollments using full-time equivalents (FTEs) rather than headcounts; (2) defining the community college sector in a way that undercounts enrollment; and (3) the exclusion of noncredit course enrollments that makes community colleges look better funded than they really are. Correcting the first two of these would not require colleges to collect more data but the third one would. The article gives brief attention to the first two points, reserving the most attention for the third.

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A commonly used metric for measuring college costs, drawn from data in the Integrated Postsecondary Education Data System (IPEDS), is expenditure per full-time equivalent (FTE) student. This article discusses an error in this per FTE calculation when using IPEDS data, especially with regard to community colleges. The problem is that expenditures for noncredit courses are reported to IPEDS but enrollments are not. This exclusion inflates any per FTE student figure calculated from IPEDS, in particular expenditures and revenues. A 2021 IPEDS Technical Review Panel (TRP #62) acknowledged this problem and moved campus institutional research offices a step closer to reporting noncredit enrollment data (RTI International, 2021). This article is the first to provide some numbers on the magnitude of this problem. It covers eight states—California, Iowa, New Jersey, New York, North Carolina, South Carolina, Tennessee, and Virginia. Data on noncredit community college enrollments were made available from system offices in all states. In addition, discussions were held at both the system level and the campus level to verify the data and assumptions. Figures provided by states were merged with existing IPEDS data at the campus and state levels, and then were adjusted to account for noncredit enrollments. The results provide evidence that calculations using IPEDS data alone overestimate the resources that community colleges have to spend on each student, although distortions vary greatly between states and among colleges in the same state. The results have important implications for research studies and college benchmarking.

Keywords: community college spending, noncredit enrollments, IPEDS

Noncredit community college enrollment accounts for approximately 40% of all enrollment in the two-year sector, or five million students (American Association of Community Colleges, 2016). Yet, this population is seldom discussed in the higher education literature due to inconsistent definitions, funding, and data reporting at the state level. Many of the structural elements (e.g., funding, enrollment) have not been documented recently or completely. This study used data from the 2015 Survey of Access and Finance Issues, administered annually to the National Council of State Directors of Community Colleges. The authors calculated noncredit enrollment by function and frequencies on funding mechanisms, funding by function, noncredit data reporting, and the measures captured at the state level. The study also employed polychoric and polyserial correlations examining the relationships among structural, contextual, and perspective-based items. This was done to capture the national landscape on this important community college function through the lens of state-level community college leaders.

Nearly 40% of all public community college enrollment is in noncredit courses. While there have been several recent reports on the noncredit function at community colleges, little has been done in terms of large-scale studies and/or statewide analyses on this population. The purpose of this study was to explore one state’s community college noncredit student data to identify course types, relationships with demographics, and multi-term enrollment patterns. The authors employed a Cramer’s V to identify relationships between enrollment by course type and demographics and conducted a multi-term course analysis on a sample of 122,886 noncredit student records.

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