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Download full textKylie L. Anglin – Annenberg Institute for School Reform at Brown University, 2025
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…
Descriptors: Validity, Artificial Intelligence, Models, Best Practices
Peer reviewed
Direct linkCharlotte Z. Mann; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2025
Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…
Descriptors: Causal Models, Statistical Analysis, Privacy, Risk
Ahmed Alkaabi; Asma Abdallah; Shamma Alblooshi; Fatima Alomari; Sara Alneaimi – Journal of Education and e-Learning Research, 2025
This study examines the opportunities and challenges of employing ChatGPT in higher education, identifies essential user competencies, and evaluates its impact in the absence of formal policy guidelines. A qualitative case study design involved interviews with 10 faculty members and 10 students at a federal university in the United Arab Emirates.…
Descriptors: Artificial Intelligence, Teaching Methods, Computer Software, Higher Education
