TPC Journal V8, Issue 3- FULL ISSUE

272 The Professional Counselor | Volume 8, Issue 3 With Hypothesis 2, the researchers sought to expand on the Belser et al. (2017) study by also predicting retention one year farther, into the third year of college. In this endeavor, the analysis yielded a model that still fit the data well. However, this model was much more accurate in predicting the non- retained students and was slightly less accurate in predicting the retained students, with the overall percentage of correct predictions similar to Hypothesis 1. This finding indicates that the included predictors may provide a more balanced ability to predict long-term retention in STEM majors than in just the first year. The initial major and STEM course variables performed similarly as in Hypothesis 1, and as such, similarly to prior research (Le et al., 2014; Lent et al., 2016). Although sampling issues warrant the reader to read ethnicity results with caution, ethnicity did show to be a good predictor of retention in STEM majors with both Hypotheses 1 and 2. More noteworthy, the African American/Black and Hispanic students had higher odds of being retained. This is inconsistent with most research that shows underrepresented minorities as less likely to be retained in STEM majors (Chen & Soldner, 2013; Cundiff et al., 2013; Gayles & Ampaw, 2014); however, at least one study has previously found results in which ethnic minority students were more likely to be retained in STEM majors (Riegle-Crumb & King, 2010). Gender was removed as a predictor from both models because of its statistical non-significance. Prior research has shown that females are less likely to be retained in STEM majors (Cundiff et al., 2013; Gayles & Ampaw, 2014; Riegle-Crumb et al., 2012), which separates this sample from prior studies. However, the COMPASS sample did have a larger representation of females than typically observed. Moreover, the COMPASS Program has been mindful of prior research related to gender and took steps to address gender concerns in program development (Dagley et al., 2016). The continuous variables retained in the models showed only a mild effect on predicting STEM retention. The SAT Math and Math Placement–Algebra scores did perform consistently with prior research, in which higher math scores related to higher odds of retention (CollegeBoard, 2012; Crisp et al., 2009; Le et al., 2014; Mattern & Patterson, 2013; Rohr, 2012). The CTI variables that were retained in the models performed in line with the Belser et al. (2017) pilot study specific to STEM majors and with prior research examining negative career thoughts in undergraduate retention in other majors (Folsom, Peterson, Reardon, & Mann, 2005; Reardon et al., 2015). Limitations and Implications The present study has limitations, particularly with regard to research design, sampling, and instrumentation. First, the researchers used a comparison group design rather than a control group, and as such, there were certain observable differences between the two groups. Not having a control group limits the researchers’ ability to make causal claims regarding the predictor variables or the STEM career intervention. The researchers also only included a limited number of predictors; the inclusion of additional variables may have strengthened the models. Although the sample size was sufficient based on the a priori power analysis, the low number of participants in some of the categories may have resulted in overfitting or underfitting within the models. Finally, the researchers were not able to test psychometric properties of the SAT Math subtest or the Math Placement–Algebra subtest with this sample because of not having access to the participants’ item responses for each. The researchers attempted to mitigate limitations as much as possible and acknowledge that they can and should be improved upon in future research.