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Published Online:https://doi.org/10.1027/1866-5888/a000116

We examine the extent to which g and specific abilities predict learning in a training context by juxtaposing contrasting theories of cognitive ability (i.e., Spearmanian theory and nested-factors theory) and using an analytical strategy (i.e., multidimensional importance analysis) that aligns with underlying theoretical assumptions of both theories. When conducting incremental validity analysis (Spearmanian approach), specific abilities did not add much to the prediction of learning. However, when conducting relative weights analysis (nested-factors approach), specific abilities were the dominant predictors of learning. Results suggest different theoretical and analytical approaches can lead to different results. Results also suggest specific abilities may provide predictive utility beyond g in the training context, but recognizing this utility depends on one’s theoretical assumptions and methodological approach.

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