Effectively predicting academic success is essential for providing students with the resources they need to succeed in their careers and for matching individuals to postsecondary institutions that suit their needs. Despite evidence for ACT scores as meaningful predictors of both first-year grade point average (FYGPA) and degree completion, little…

The Work Values Inventory and Self-Directed Search were used to predict retention of students in office occupation majors at Utah Valley Community College. The predictive model distinguished among students either retained (graduated, on-track, and "jobbed-out") and noncompleters. Noncompletion was correctly predicted for about 73 percent…

Tinto's conceptual schema of college dropout forms the theoretical framework for the development of a model of university student dropout intention. This study validated Tinto's model in two different departments within a single university. Analyses were conducted on a sample of 684 college freshmen in the Education and Economics Department. A…

This paper describes a methodology used in an on-going retention study at New York University (NYU) to identify a series of easily measured factors affecting student departure decisions. Three logistic regression models for predicting student retention were developed, each containing data available at three distinct times during the first…

Describes a study applying the Tinto Model to predict student persistence/exit in a community college setting. A questionnaire assessing background, environmental, and integration variables was administered to full-time students during their first semester, successfully predicting subsequent persistence/exit behavior and affirming the utility of…