![]() ![]() Carroll regarded the broad abilities as different "flavors" of g. Key: fluid intelligence (Gf), crystallized intelligence (Gc), general memory and learning (Gy), broad visual perception (Gv), broad auditory perception (Gu), broad retrieval ability (Gr), broad cognitive speediness (Gs), and processing speed (Gt). Carroll distinguishes his hierarchical approach from taxonomic approaches such as Guilford's Structure of Intellect model (three-dimensional model with contents, operations, and products).Ĭarroll's three-stratum model. Carroll suggests that the distinction between level and speed factors may be the broadest taxonomy of cognitive tasks that can be offered. Tasks that contribute to speed factors are distinguished by the relative speed with which individuals can complete them. The tasks that contribute to the identification of level factors can be sorted by difficulty and individuals differentiated by whether they have acquired the skill to perform the tasks. This does not alter the effectiveness of factor scores in accounting for behavioral differences.Ĭarroll proposes a taxonomic dimension in the distinction between level factors and speed factors. Carroll argues further that they are not mere artifacts of a mathematical process, but likely reflect physiological factors explaining differences in ability (e.g., nerve firing rates). The factors describe stable and observable differences among individuals in the performance of tasks. The three layers (strata) are defined as representing narrow, broad, and general cognitive ability. These analyses suggested a three-layered model where each layer accounts for the variations in the correlations within the previous layer. It is based on a factor-analytic study of the correlation of individual-difference variables from data such as psychological tests, school marks and competence ratings from more than 460 datasets. This change in relatively early sensory processing (i.e.The three-stratum theory is a theory of cognitive ability proposed by the American psychologist John Carroll in 1993. The early N1-P2 change found only for generalized learning, suggests that generalized learning relies on the attentional system in reorganizing the way acoustic features are selectively processed. Rote learning, however, is marked only by temporally later source configuration changes. In the context of adapting to a talker, generalized learning is marked by an amplitude reduction in the N1-P2 complex and by the presence of a late-negative (LN) wave in the auditory evoked potential following training. Analysis of long-latency auditory evoked potentials at Pretest and Posttest revealed that while rote and generalized learning both produce rapid changes in auditory processing, the nature of these changes differed. Participants were trained using either (1) a large inventory of words where no words repeated across the experiment (generalized learning) or (2) a small inventory of words where words repeated (rote learning). Here, we examine the differences in neural responses to generalized versus rote learning in auditory cortical processing by training listeners to understand a novel synthetic talker using a Pretest-Posttest design with electroencephalography (EEG). Behavioral research has demonstrated that listeners are able to rapidly generalize their experience with a talker's speech and quickly improve understanding of a difficult-to-understand talker without prolonged practice, e.g., even after a single training session. The ability to generalize rapidly across specific experiences is vital for robust recognition of new patterns, especially in speech perception considering acoustic-phonetic pattern variability. ![]()
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