The fluid and crystallized (Gf–Gc) intelligence theory has been used extensively to evaluate the influence of cognitive abilities on educational outcomes within cross-sectional and longitudinal research designs. This study evaluated the contribution of fluid and crystallized abilities in the performance of a 1-week instructional process with an old dataset applying a latent curve model. This allowed for the specification of latent learning growth factors that took into account individual differences in the final level of performance and the rate of learning in the instructional project. Fluid abilities (Gf) had a significant impact on the rate of learning, whereas crystallized abilities (Gc) had a significant impact on the final learning performance. There was also a significant indirect effect of Gf onto the final learning performance through Gc. These findings are in accordance with some of the premises posited by the Gf–Gc intelligence model.
