The Success Of The CPQ In Identifying At-Risk Students

A recent meta-analysis by ACT (Lotkowski, Robbins, & Noeth, 2004) reported that thirteen academic and non-academic variables accounted for 17% of the variability in college student retention. In all studies conducted thus far, the CPQ has explained a much higher proportion of the variance. Thus, we are often asked: Why is the CPQ so successful in identifying at-risk students?

Our initial strategy had a great deal to do with the instrument’s success. Before the first datum was collected we spent many hours talking with advisors, faculty, counselors and policy makers. They provided invaluable insights regarding what they needed to know to improve retention at their schools.

Equally important was the decision to focus upon students’ interactions with the academic and social environments. These experiences, which cannot be assessed at matriculation or during orientation, have a profound impact upon students’ persistence decisions. The ability to accurately identify at-risk students and determine why they are at-risk is greatly enhanced if you record their reactions to the academic and social milieu provided by your college or university.

A recent analysis of CPQ data indicates how very critical the first six to eight weeks of college are in determining students’ persistence decisions. Retention was regressed upon a number of variables typically available at matriculation (e.g., high school grades, standardized test scores). They produced a Nagelkerke R Square of .08. When the ten scales composing the Student Experiences Form and other measures of the CPQ were added to the equation, the Nagelkerke R Square was .37, a 4.65 fold increase in the efficiency of prediction.

Click here for the next stop on the Advanced Tour (Are There Research Opportunities In Using The CPQ?).