Exploring the relationship between COVID‐19 and immediate 2‐year college enrollment and persistence among Kalamazoo Promise scholars.
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| Title: | Exploring the relationship between COVID‐19 and immediate 2‐year college enrollment and persistence among Kalamazoo Promise scholars. |
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| Authors: | McMullen, Isabel1 (AUTHOR) imcmullen@wisc.edu, Collier, Daniel2 (AUTHOR) |
| Source: | New Directions for Community Colleges. Sep2023, Vol. 2023 Issue 203, p75-85. 11p. 1 Chart. |
| Subject Terms: | *College enrollment, *Tuition-free universities & colleges, *College freshmen, *College attendance, COVID-19 |
| Abstract: | There are hundreds of recognized tuition‐free college "promise" programs, but few are as generous or flexible as the Kalamazoo Promise (KPromise). Pre‐COVID studies on KPromise have demonstrated effects on increased college attendance, credit completion, and persistence. Extending these findings to the COVID‐19 pandemic context can help establish a baseline understanding of the ability and limits of tuition‐free college to mitigate a shock to college enrollment and speed the recovery in the aftermath. This chapter explores incoming student college enrollment and first‐year persistence among recent KPromise cohorts at the primary community college that scholars attend: Kalamazoo Valley Community College (KVCC). We found that enrollment decreased for two consecutive cohorts, notably among students with lower high school academic performance. We found that first‐year stop out overall increased, and these two changes together resulted in demographic changes in the KPromise student population at KVCC. Our findings have important implications for tuition‐free programs and the 2‐year institutions that receive Promise students. [ABSTRACT FROM AUTHOR] |
| Copyright of New Directions for Community Colleges is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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