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ERIC Number: ED397726
Record Type: Non-Journal
Publication Date: 1996-May
Pages: 23
Abstractor: N/A
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Identifying Students at Risk: Utilizing Traditional and Non-Traditional Data Sources. AIR 1996 Annual Forum Paper.
Huesman, Ronald L., Jr.; And Others
A study tracked 3,192 University of Iowa freshmen through their first year and into their second year on campus. Logistic regression analyses using multiple data sources (admissions and registrar files, a standardized entrance test (the American College Testing Program Assessment) student profile section, an entering freshman survey) were conducted to determine models of student persistence at two points: freshman year spring re-enrollment and sophomore year fall re-enrollment. Two relatively successful models for predicting sophomore persistence were derived, although both models predicted correctly rather small percentages of non-persisters. A followup study on the reasons given for withdrawal by false-positives in the model is recommended. For this sample, it was found that modeling persistence was related to college-level academic indicators; the only non-academic factor to enter the prediction equation was students' perceived need for financial aid. (Contains 17 references.) (MSE)
Publication Type: Reports - Research; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A