2 resultados para Cognitive learning theory

em DigitalCommons@University of Nebraska - Lincoln


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This study was designed to compare the writing motivation of students with specific language impairments with their non-disabled peers. Due to the cognitive and linguistic demands of the writing process, students with language impairments face unique difficulties during the writing process. It was hypothesized that students with specific language impairments will be more likely to report lower levels of perceived writing competence and be less autonomously motivated to write. Students in grades 3-5 in 11 schools (33 with specific language impairments, 242 non-disabled peers) completed self-report measures, designed from a Self-Determination Theory perspective, which measured the degree that students are intrinsically motivated to write as well as their perceived writing competence. Statistical analyses showed that (1) students with specific language impairments reported lower levels of perceived writing competence and autonomous writing motivation; (2) SLI status was a significant predictor of perceived writing competence after spelling, grade, and gender were controlled; and (3) when spelling, grade, and gender were controlled, perceived writing competence was a significant predictor of autonomous writing motivation, but SLI status was not. The results of this study are expected to inform the current understanding of the relationship between language ability and writing motivation in students with specific language impairments, as well as the design of future writing interventions.

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Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.