Predicting "At Risk" Students
 with the CSFI  

The question of students "at risk" is a multi-faceted one. Nearly 50% of community college freshmen enrolled this year will not return the following year. Four-year colleges and universities don't fare much better: approximately 27% are non-returns the second year. The results of this loss are staggering to the student,  the college, and society at large.

How can colleges retain more students? In order to intervene and retain these "at risk" students, colleges must know who they are and how they can help them. The College Success Factors Index (CSFI) was designed to help colleges identify "at risk" students by name, and by weakness (according to the 8 factors of academic success).     

The Validity of Prediction
To determine through empirical measurement the percentage of students at risk, any instrument used must be validated to prove its ability to predict return and non-return.

In two recent studies, the CSFI predicted non-returns the second year at twice the Registrar's expectations:

While this research was not designed to match students, each of these studies shows the reported efficacy of the CSFI in predicting non-return the second year. 

Grade point average (GPA) is an important element of "high risk" and "non-return" prediction. In another study at a California community college, the CSFI scales were compared from all samples of students (gender, ethnicity, etc.) in a multiple regression analysis to predict GPA. A correlation of r.=.36 was obtained, which means that the 8 scales of the CSFI accounted for 13% of the variance of GPA. This is very similar to the predicted value of high school GPA, which shows a r.=.40 correlation with college GPA. When the CSFI scales are combined with high school grades, a correlation of r.=.50 is obtained, accounting for 25% of the variance in college GPA: a modest but statistically significant increase.

The Identification of Specific Students

Unlike the Registrar's aggregated predictive data, the CSFI identifies "at risk" students by name, so that individual interventions are possible. In each of the studies above, "at risk" students were identified by the CSFI. One California community college study identified 93 students who were "high risk" for non-return.

Individual Student Factor Identification 

The CSFI identifies which of the 8 factors a student is "at risk" for.  The study results have indicated that a watch-line score for each of the factors does exist. Further, that students who were two standard deviations below the watch-line were at extremely "high risk" for non-return.

Factor scores may also be aggregated for administrators and faculty to understand risk factors in general, and to design interventions.

Curriculum Interventions

Colleges are able to improve retentions rates by using interventions related to the CSFI and its factors.

At one community college, a student development course (FYE) was designed with the CSFI and related interventions. Students in the program were matched with others who were not given the interventions. After several semesters, there was 11% more retention among those students who had taken the course designed with the CSFI.

Summary
All of these studies indicate that the CSFI is valid in predicting "at risk" students and that subsequent interventions using its factors improve retention rates.