Noncredit Research Collaborative

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Objective: This study examines the characteristics, course enrollment patterns, and academic outcomes of students who started their college careers in noncredit courses. Method: Drawing upon a rich dataset that includes transcript and demographic information on both for-credit and noncredit students in multiple institutions, this study explores the demographic and academic profiles of students enrolled in various fields of noncredit education, their course performance in noncredit programs, their educational intent upon initial enrollment, and their transition to the for-credit sector among degree-seeking students. Results: Our results support recent evidence from qualitative studies and studies from a single institution that students enrolled in noncredit programs tend to be adult learners and are typically from a lower socioeconomic background than credit students at community colleges. Yet, more than half of the noncredit students drop out of college after their initial term, even among students who expressed intent to transition to credit-bearing programs. The idiosyncratic patterns of course enrollment and transition to credential programs seem to suggest that there is no general structured pathway or institutional support for credential-seeking noncredit students. Contributions: This article is among one of the first attempts that use student transcript data from multiple institutions to provide a comprehensive understanding of noncredit students and their academic outcomes. Results from this study highlight the importance of future research in exploring institutional services and structures that may effectively facilitate the academic progression and success of noncredit students.

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.

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

Representing approximately two in five community college students, noncredit education is an important but understudied segment of the higher education population. In an effort to help open the “black box” of noncredit education in community colleges, the present study uses an established noncredit course typology (occupational training, sponsored occupational training, personal interest, and precollege remediation) to better understand the predictors of noncredit enrollment and outcomes in Iowa. Using a sample of more than 181,000 records, we employed a series of regression analyses to discuss variables associated with enrollment in the noncredit course types, the number of completions, and the number of contact hours. Nuanced findings and implications were associated with race/ethnicity, gender, institutional mission as captured through Carnegie Classifications, and career fields based on the 16 career clusters.

Objective: In the first study of its kind, the impact of excluding noncredit enrollments in calculations of spending in community colleges is explored. Noncredit enrollments are not reported to Integrated Postsecondary Education Data System (IPEDS), but expenditures for these efforts are. This study corrects for this omission and provides new estimates of spending on community college students in four states. Method: Data on noncredit enrollments were made available from four states—New York, New Jersey, California, and North Carolina. Interviews with campus and state officials within each state helped us verify the findings. In addition, Delta Cost Project data were analyzed and adjusted to account for noncredit enrollments. Results: Our analysis indicates that the expenditure per full-time equivalent (FTE) student measure, which researchers typically use, seriously overstates the resources that community colleges have to spend on educating students; however, great variations exist within and across states. Conclusion: Community colleges are underfunded to an even greater extent than standard IPEDS analyses indicate.

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.