Abstract

Theoretical arguments and analyses from 2 studies provide compelling evidence that computerized measures of information-processing skills and abilities are highly useful supplements to more traditional, paper-based measures of general mental ability for predicting individuals' capacity to learn from and perform on highly challenging, multifaceted tutors. These tutors were designed to emulate learning and performance in complex, real-world settings. Hierarchical confirmatory factor analysis provided evidence that a general, higher order factor model with general ability at the apex could quite adequately and singularly account for the individual-differences data, both traditional and cognitive-process measures. Results are interpreted in light of the utility and generality of human cognitive abilities.

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