What Do College Ranking Data Tell Us About Student Retention

We describe an application of the TETRAD II causal discovery program to the problem of search for causes of low student retention in U.S. universities. TETRAD II discovers a class of possible causal structures of a system from a data set containing measurements of the system variables. The signiicance of learning the causal structure of a system is that it allows for predicting the eeect of interventions into the system, crucial in policy making. Our data sets contained information on 204 U.S. national universities, collected by the US News and World Report magazine for the purpose of college ranking in 1992 and 1993. One apparently robust nding of our study is that student retention is directly related to the average standardized test scores of the incoming freshmen. When test scores of incoming students are controlled for, factors such as student faculty ratio, faculty salary, and university's educational expenses per student are all independent of graduation rates, and, therefore, do not seem to directly innuence student retention. As the test scores are indicators of the overall quality of the incoming students, we predict that one of the most eeective ways of improving student retention in an individual university is increasing the university's selectivity.