Validation of the Adaptive Vocational Interest Diagnostic
Abstract
Initial research with the Adaptive Vocational Interest Diagnostic (AVID) demonstrated that this assessment is a valid predictor of Soldiers attitudes and performance in several military operational specialties (MOS). However, previous research has only examined a static version of the AVID. Therefore, one goal of the current research was to expand on previous work by conducting a concurrent validation study of a computer-adaptive version of the AVID (CAT AVID). The data for this research were collected from Soldiers in numerous MOS and results indicated that the validity of the CAT AVID is comparable to the validity of the static version. In addition to the validation analyses, three simulations were conducted to explore the optimal ways of operationalizing interest fit. The results of these simulations demonstrated that regression-based composites of AVID scales performed better than the congruence indices that have traditionally been used in the interest literature. In addition, regression-weighted composites also performed as well as or better than other modern prediction methods based on machine learning. Finally, simulations also demonstrated that matching individuals to jobs based on their interests could substantially improve the overall performance of Soldiers. These findings provide additional evidence that the AVID may be useful for MOS assignment
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2023
- Accession Number
- AD1211165
Entities
People
- Bo Zhang
- Christopher Nye
- Fritz Drasgow
- James Rounds
- Kirkendall D Kirkendall
- Oleksaandra S Chernyshenko
- Stephen Stark
- Tianjun Sun
Organizations
- Drasgow Consulting Group