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Cognitive and noncognitive predictors of success
Edited by Susan T. Fiske, Princeton University, Princeton, NJ, and approved October 6, 2019 (received for review June 19, 2019)

Significance
To examine cognitive and noncognitive predictors of success, we conducted a megaanalysis of prospective, longitudinal data on over 10,000 cadets at the US Military Academy at West Point. Cognitive ability was negatively related to physical ability and grit. While cognitive ability predicted academic and military grades, the noncognitive attributes of physical ability and grit were more prognostic of other achievement outcomes, including successful completion of initiation training and 4-y graduation.
Abstract
When predicting success, how important are personal attributes other than cognitive ability? To address this question, we capitalized on a full decade of prospective, longitudinal data from n = 11,258 cadets entering training at the US Military Academy at West Point. Prior to training, cognitive ability was negatively correlated with both physical ability and grit. Cognitive ability emerged as the strongest predictor of academic and military grades, but noncognitive attributes were more prognostic of other achievement outcomes, including successful completion of initiation training and 4-y graduation. We conclude that noncognitive aspects of human capital deserve greater attention from both scientists and practitioners interested in predicting real-world success.
Footnotes
- ↵1To whom correspondence may be addressed. Email: aduckworth{at}characterlab.org.
Author contributions: A.L.D. designed research; A.L.D., A.Q., D.R.K., and M.D.M. performed research; R.H.H. contributed new reagents/analytic tools; A.L.D. and R.G. analyzed data; and A.L.D. wrote the paper.
The authors declare no competing interest.
This article is a PNAS Direct Submission.
Data deposition: The preregistration plan of the project can be found on AsPredicted (https://aspredicted.org/wt6vs.pdf). The data and web appendix can be found on Open Science Framework (https://osf.io/yx3vg/).
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1910510116/-/DCSupplemental.
- Copyright © 2019 the Author(s). Published by PNAS.
This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
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