PREDICTION OF RETENTION AND PROBATION STATUS OF FIRST-YEAR COLLEGE STUDENTS IN LEARNING COMMUNITIES USING BINARY LOGISTIC REGRESSION MODELS

The first year of college is a critical period of transition for incoming college students. Learning communities have been identified as an approach to link students together in courses that are designed with first-year students’ needs in mind. Yet, learning community teaching teams are often not provided with data prior to the start of the semester about their students in order to target interventions. One question then becomes, what variables known on or before the first day of classes are predictive of first-year student success, in terms of retention and probation status, for first-year college students in learning communities? The correlational study employed univariate and multivariate analyses on pre-college data for three consecutive cohorts of first-year students (n = 4,215) in learning communities at a regional public university in South Texas. Logistic regression models were developed – for all students as well as for individual learning community categories – to predict retention and probation status using the variables of first-semester hours, developmental status, high school percentile, transferred hours, SAT score, age, gender, first-generation status, ethnicity, Pell Grant eligibility, admission date, admission status, and orientation date. Results indicated that group differences were statistically significant for retention based on all pre-college variables excluding first-generation status or age, while group differences were statistically significant for probation status on the basis of all pre-college variables except age. The model to predict retention for all students included five variables (high school percentile, SAT score, Pell Grant eligibility, days since admission, and days since orientation), and the model to predict probation status included three additional variables (transferred hours, gender, and ethnicity). The models for individual learning communities contained different sets of vi predictor variables; the most common predictors of retention or probation status were high school percentile and orientation date. The study has practical implications for admissions officers, orientation planners, and learning community practitioners based on the pre-college variables, such as orientation date, that were found to be predictive of retention or probation status. Topics for further research include exploring the pre-college variables that did not predict either outcome, such as first-generation status, for first-year students in learning communities.