Degree Name

PhD (Doctor of Philosophy)



Date of Award


Committee Chair or Co-Chairs

Alyson Chroust

Committee Members

Stacey Williams, Alison Barton, Meredith Ginley


Underachievement in postsecondary education has been a growing concern for educators and researchers. Higher education institutions have implemented early alert systems to identify students performing below standards. This early warning system has major limitations that confine it to an identification only approach. The current study aimed to investigate the psychometric properties of the Student Attitude Assessment Survey-R (SAAS-R) in a postsecondary sample. First, a confirmatory factor analysis validated the SAAS-R in a postsecondary sample. Predictive validity was then investigated by identifying students as underachieving or achieving based on responses to the SAAS-R and via a regression-based discrepancy model (ability vs. achievement). Then, the SAAS-R was compared to the discrepancy model to see whether the SAAS-R is an accurate assessment for identification of achievement. Tests of convergent validity included comparison of the SAAS-R subscales to well established similar constructs. Discriminant validity was checked by comparing the SAAS-R to a Social Desirability Scale. Finally, measurement invariance was explored to see if the SAAS-R would measure across groups. The SAAS-R demonstrated strong evidence of structural, convergent, and discriminant validity, yet limited evidence of predictive validity. Assessment of measurement invariance across self-identified traditional and non-traditional students yielded no evidence of measurement invariance. Initial psychometric properties support extension of the structural model of the SAAS-R to postsecondary students and the convergent validity utility of the SAAS-R subscales. However, more research is needed before the SAAS-R can be applied as an assessment of underachievement in postsecondary education.

Document Type

Dissertation - unrestricted


Copyright by the authors.