This article describes a continuing project at the University of South Florida that was first presented in the 83(2) issue of "College and University" (Miller 2007) and further detailed in the 83(3) (Miller and Herreid 2008). Through that point the project had established a predictive formula for determining the risk of attrition of…

This article describes the early outcomes of an ongoing project at the University of South Florida in Tampa that involves using a logistics regression formula derived from pre-matriculation characteristics to predict the risk of individual student attrition. In this piece, the authors will describe the results of the prediction formula and the…

This is the fifth in a series of articles describing an attrition prediction and intervention project at the University of South Florida (USF) in Tampa. The project was originally presented in the 83(2) issue (Miller 2007). The statistical model for predicting attrition was described in the 83(3) issue (Miller and Herreid 2008). The methods and…

The model presented used available data to predict whether or not a student will drop out at some time during his or her college career. The model successfully identified students who would or would not drop out approximately 80% of the time. Logistic regression analysis was employed to predict chances of attrition for matriculating freshmen soon…

Presents a tracking model for monitoring and reporting student transitions through the college years. Develops and illustrates the model by following a mythical class of 500 freshmen and 380 transfer students from matriculation to attrition or graduation. The model focuses on sequences of semesters rather than on freshman, sophomore, junior, and…

Describes Canisius College's efforts to improve student retention over a seven-year period. Includes research data for freshman-to-sophomore attrition figures and graduation rates. Focuses on alliances and agreements that have created the ground for college-wide cooperation in retention. Describes nine intervention strategies implemented at…

Logistic regression is employed to develop a model that enhances early identification of freshmen at risk of attrition. Independent variables employed to predict attrition include demographics; high school experiences; and attitudes, opinions, and values as reported on a survey administered during freshman orientation. Model and results are…

Describes the mentoring program at Canisius College, New York. Program evaluation showed it had a positive impact on the retention and academic performance of freshmen and provided an opportunity to demonstrate the college's concern for students. Both faculty and students reported benefits from the program. (JAC)