title: The Prediction of Students' Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning.
abstract: The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.
authors.affiliation: School of Education, Huazhong University of Science & Technology, Wuhan 430074, China ; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing 100875, China.
authors.forename: Xuezhu
authors.initials: X
authors.lastname: Ren
authors.affiliation: Goethe University Frankfurt, Gruneburgplatz 1, 60323 Frankfurt a. M., Germany.
authors.forename: Karl
authors.initials: K
authors.lastname: Schweizer
authors.affiliation: Goethe University Frankfurt, Gruneburgplatz 1, 60323 Frankfurt a. M., Germany.
authors.forename: Tengfei
authors.initials: T
authors.lastname: Wang
authors.affiliation: Department of Psychology, Zhejiang Sci-Tech University, Hangzhou 310018, China.
authors.forename: Fen
authors.initials: F
authors.lastname: Xu
keywords: academic performance; complex learning; individual differences fluid intelligence