Date of Award:


Document Type:


Degree Name:

Doctor of Philosophy (PhD)




Kerry E Jordan


Children who struggle to learn math are often identified by their poor performance on common math learning activities, such as number line estimations. While such behavioral assessments are useful in the classroom, naturalistic neuroimaging of children engaged in real-world math learning activities has the potential to identify concurrent behavioral and neurological correlates to poor math performance. Such correlates may help pinpoint effective teaching strategies for atypical learners, and may highlight instructional methods that elicit typical neurological response patterns to such activities. For example, multisensory stimulation that contains information about number enhances infants' and preschool children's behavioral performance on many numerical tasks and has been shown to elicit neural activation in areas related to number processing and decision-making. Thus, when applied to math teaching tools, multisensory stimulation may provide a platform through which both behavioral and neural math-related processes may be enhanced. Common approaches to neuroimaging of math processing lack ecological validity and are often not analogous to real-world learning activities. However, because of its liberal tolerance of movement, near-infrared spectroscopy (NIRS) provides an ideal platform for such studies. Here, NIRS is used to provide the first concurrent examination of neurological and behavioral data from number line estimation performance within children and adults. Moreover, in an effort to observe the behavioral and neurological benefits to number line estimations that may arise from multisensory stimulation, differential feedback (i.e., visual, auditory, or audiovisual) about estimation performance is provided throughout a portion of the task. Results suggest behavioral and neural performance is enhanced by feedback. Moreover, significant effects of age suggest young children show greater neurological response to feedback, and increase in task difficulty resulted in decreased behavioral performance and increased neurological activation associated with mathematical processing. Thus, typical math learners effectively recruit areas of the brain known to process number when math activities become increasingly difficult. Data inform understanding typical behavioral and neural responses to real-world math learning tasks, and may prove useful in triangulating signatures of atypical math learning. Moreover, results demonstrate the utility of NIRS as a platform to provide simultaneous neurological and behavioral data during naturalistic math learning activities.