Assumptions about learning styles and cognitive abilities inform the nation's STEM educational curricula and standards. The proposal is aimed at addressing fundamental unanswered questions about the construct, including the neural correlates of individual differences in visual, verbal, and spatial cognitive styles. The PI will examine whether cognitive styles reflect learning and reasoning strategies rather than abilities, which has important implications for the way in which individuals? needs are met in classrooms and other learning environments. Through a series of experiments, the PI will study the behavioral and neural correlates of cognitive styles as well as its effects on memory and attention. These experiments will address such specific questions as: Do cognitive styles represent orthogonal dimensions rather than opposing ends of a spectrum? What neural mechanisms underlie these styles? Does general fluid intelligence relate to an ability to switch flexibly between styles as dictated by task context? Will those who have a propensity towards a particular cognitive style show better memory retention for information presented in their preferred modality? Is successful encoding correlated with activity in predicted brain regions? At the time of encoding, does one tend to convert information presented in a non-preferred modality into a preferred modality? The project will culminate in series of experimental interventions design to study the effectiveness of training participants to adopt a new cognitive style and apply it to an untrained task. The promise of this project is that it will help synthesize and make more coherent current theories and findings on cognitive and learning styles and, supported by solid scientific methodology, lay the foundation for improved pedagogical techniques.
What are cognitive styles? Do they exist, and how, if at all, do they impact learning, thinking, and the retention of information? The goal of this project was to investigate whether cognitive processing varies on an individual basis as a function of self-reported cognitive styles. Our studies were aimed at answering two major questions: 1) Do cognitive styles reliably predict any behavioral differences on task performance?, and 2) Can a better understanding of cognitive styles on a neural level elucidate individual differences in thought processes that correlate with cognitive styles? In this way we developed and supported a theory of cognitive styles that relates self-reported preferences with reliable differences in cognitive processes. In a critical review, Pashler and colleagues (2008) reported that there was no extant evidence to support the predominant theory regarding learning styles, the "meshing hypothesis". This hypothesis states that the optimal learning environment involves matching the presentation format of information (pictures or words) with oneâ€™s preferred learning style (visual or verbal). In contrast with the meshing hypothesis, results from work in our lab has supported an alternate theory, namely the "conversion hypothesis". Under this hypothesis, cognitive styles do not represent a bias towards a particular presentation format. Instead, they represent a predisposition for mentally representing information in either the visual or the verbal modality. Thus, rather than learning better from pictures versus text, an individual who rates highly on a scale of visual cognitive style would be likely to try to generate and recollect a mental image of a newly-learned concept irrespective of whether it was presented visually or verbally. Likewise, the verbal cognitive style scale correlates with reliance on a labeling strategy. In this way, cognitive styles are better conceived of as predispositions for different task processing strategies, rather than as differences in preference for presentation format. Data in support of the conversion hypothesis come from both neural and behavioral evidence. From studies in which we used fMRI, we have found that in functionally-defined verbal brain areas, left supramarginal gyrus (SMG) in particular, brain activity correlates with the verbal cognitive style during tasks that require judging and encoding visual stimuli. Similarly, activity in functionally-defined visual brain areas, such as fusiform cortex, correlates with visual cognitive style when the task requires processing of words that name imageable stimuli (e.g., colors and shapes). The neural basis of the verbal labeling strategy during a visual task may involve the co-activation of the left SMG along with task-relevant processing in visual brain regions. For example, in a virtual navigation experiment, task-related left SMG activity was shown to correlate with activity in a visual region important for scene processing and navigation. Moreover, we used transcranial magnetic stimulation (TMS) to further test the importance of left SMG for processing in the verbal cognitive style during a visual task. Consistent with the conversion hypothesis, TMS to this region selectively impaired task performance for the individuals who rated themselves higher on the verbal style dimension. Additionally, volumetric analysis of left SMG revealed greater white matter volume correlating with the verbal cognitive style, and DTI revealed more connections between left SMG and right fusiform cortex correlating with the verbal cognitive style. These findings are consistent with the notion that the verbal cognitive style is reliably associated with a predisposition for engaging in verbal processing of stimuli, even when the stimuli are presented in a visual format. The conversion hypothesis further predicts certain behavioral effects that are in contrast with the meshing hypothesis. For example, according to dual coding theory (e.g., Paivio, 1978), information that has a verbal code and a visual code should be recollected more reliably than stimuli that only tap one or the other modality. Therefore, the conversion hypothesis would predict that the verbal cognitive style, rather than the visual style should predict memory for images that are easily named such as common shapes and colors or even landmarks. In this vein, work in our lab has revealed just such an effect of the verbal labeling strategy. For both pictures of common objects, as well as pictures of landmarks encountered in a virtual navigation environment, recognition was predicted by higher scores on the verbal, not the visual, cognitive style scale. In contrast, however, higher scores on the visual dimension did predict better performance for non-verbalizable visual information, in this case the relative directions between landmarks that were encountered only in an egocentric framework. Moreover, instructional cues to engage in visual or verbal encoding strategies during route learning resulted in the predicted interaction, in which the cued verbal strategy improved performance on landmark memory while the visual strategy improved judgments of relative direction. Taken together, these findings reveal new aspects of what cognitive styles represent, and indicate new directions for future research to continue to explore their relationship with learning, memory, and conceptual representation.