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ERIC Number: ED671086
Record Type: Non-Journal
Publication Date: 2025-Jan
Pages: 62
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: 0000-00-00
Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers. EdWorkingPaper No. 25-1117
Kylie L. Anglin
Annenberg Institute for School Reform at Brown University
Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends in enrollment, revenues, debt and staffing across Ohio's nine largest public universities. We find significant variation in how institutions have evolved over this period. Our analysis suggests Ohio serves as an illustrative case study for examining institutional preparedness, as it represents a "worst-case scenario" across multiple dimensions - from projected enrollment declines to state funding constraints. The paper concludes by considering implications for higher education nationally and suggesting directions for future research on institutional responses to demographic shifts.
Annenberg Institute for School Reform at Brown University. Brown University Box 1985, Providence, RI 02912. Tel: 401-863-7990; Fax: 401-863-1290; e-mail: annenberg@brown.edu; Web site: https://annenberg.brown.edu/
Related Records: EJ1455470
Publication Type: Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: Annenberg Institute for School Reform at Brown University
Grant or Contract Numbers: N/A
Author Affiliations: N/A