Joseph G. Glynn

Signaling Student Retention With Prematriculation Data

Logistic regression is employed to develop a model that seeks to provide information to enhance early identification of freshmen at risk of attrition. The early identification is accomplished shortly after freshman orientation. The dependent variable of interest is the binary and nominal variable of persistence. Students who proceed from freshman matriculation to graduation without ever having dropped out are classified as persistors, and freshman matriculates who leave college either temporarily or permanently are classified as dropouts. The 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. The model and its results will be presented along with a brief description of the institutional intervention program designed to enhance student persistence.

Configural Invariance of a Model of Student Attrition

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 after freshman orientation. The dependent variable was the probability a student would, at some time in their college experience, drop out of college. The independent or predictor variables included demographics, high school experiences and factor scores based on a survey of attitudes, opinions and values. A two-stage procedure consisting of factor analysis in the first stage and logistic regression in the second stage provided model parameter estimates for each cohort of matriculating freshman in years 2000 to 2003. Empirical tests revealed the model was fully configural invariant in the first stage and partially configural invariant in the second stage.

Strategic Market Evaluation of Two Retail Electronic Funds Transfer Systems (EFTS)

This paper deals with research that was used to develop a strategic plan for the evaluation of two off-site electronic funds transfer systems (EFTS). Faced with a choice between automatic teller machines (ATM) or an in-store banking system (ISB), management must determine which approach will provide them with the greatest opportunity to penetrate selected target markets. Mapping the attitudinal and personal characteristics of four consumer segments by means of discriminant analysis contributed significantly to the assessment of the two systems with respect to the bank’s marketing objectives.