Cognitive and noncognitive predictors of success.

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.

Using artificial intelligence to assess personal qualities in college admissions.

Personal qualities like prosocial purpose and leadership predict important life outcomes, including college success. Unfortunately, the holistic assessment of personal qualities in college admissions is opaque and resource intensive. Can artificial intelligence (AI) advance the goals of holistic admissions? While cost-effective, AI has been criticized as a "black box" that may inadvertently penalize already disadvantaged subgroups when used in high-stakes settings. Here, we consider an AI approach to assessing personal qualities that aims to overcome these limitations. Research assistants and admissions officers first identified the presence/absence of seven personal qualities in n = 3131 applicant essays describing extracurricular and work experiences. Next, we fine-tuned pretrained language models with these ratings, which successfully reproduced human codes across demographic subgroups. Last, in a national sample (N = 309,594), computer-generated scores collectively demonstrated incremental validity for predicting 6-year college graduation. We discuss challenges and opportunities of AI for assessing personal qualities.

A brief behavioral measure of frustration tolerance predicts academic achievement immediately and two years later.

Achieving important goals is widely assumed to require confronting obstacles, failing repeatedly, and persisting in the face of frustration. Yet empirical evidence linking achievement and frustration tolerance is lacking. To facilitate work on this important topic, we developed and validated a novel behavioral measure of frustration tolerance: the Mirror Tracing Frustration Task (MTFT). In this 5-min task, participants allocate time between a difficult tracing task and entertaining games and videos. In two studies of young adults (Study 1: N = 148, Study 2: N = 283), we demonstrated that the MTFT increased frustration more than 18 other emotions, and that MTFT scores were related to self-reported frustration tolerance. Next, we assessed whether frustration tolerance correlated with similar constructs, including self-control and grit, as well as objective measures of real-world achievement. In a prospective longitudinal study of high-school seniors (N = 391), MTFT scores predicted grade-point average and standardized achievement test scores, and-more than 2 years after completing the MTFT-progress toward a college degree. Though small in size (i.e., rs ranging from .10 to .24), frustration tolerance predicted outcomes over and above a rich set of covariates, including IQ, sociodemographics, self-control, and grit. These findings demonstrate the validity of the MTFT and highlight the importance of frustration tolerance for achieving valued goals. (PsycINFO Database Record (c) 2019 APA, all rights reserved).