| Literature DB >> 6954181 |
Abstract
Preprofessional students' grade point averages (GPAs) and aptitude test scores have been moderately successful in predicting student performance in dental school. The authors attempted to improve the predictability of the school's admission process by combining several preprofessional academic averages and selected nongraded personal attributes into a single Admission Index (AI) score. A Pearson r of 0.67 was found for the relationship between the AI and first-year dental school GPA for University of Louisville dental students accepted into the class of 1984. The correlation coefficient generated from the AI and first-year dental school GPA was markedly superior to those generated by any single predictor. The authors propose that the AI is of value not only for its use in the admission process, but also in the development of an interceptive student monitoring program for the less-qualified student.Mesh:
Year: 1982 PMID: 6954181
Source DB: PubMed Journal: J Dent Educ ISSN: 0022-0337 Impact factor: 2.264