Cortical Activations During a Computer-Based Fraction Learning Game: Preliminary Results from a Pilot Study

Advances in educational neuroscience have made it possible for researchers to conduct studies that observe concurrent behavioral (i.e., task performance) and neural (i.e., brain activation) responses to naturalistic educational activities. Such studies are important because they help educators, clinicians, and researchers to better understand the etiology of both typical and atypical math processing. Because of its ease of use and robust tolerance of movement, functional near-infrared spectroscopy (fNIRS) provides a brain-imaging platform that is optimally suited for such studies. To that end, the focus of the current research is to use fNIRS to help better understand the neural signatures associated with real-world math learning activities. For example, the computer game ‘‘Refraction’’ was designed as a fun and engaging method to improve fraction knowledge in children. Data collected in previous studies have identified significant correlations between Refraction play and improvements in fraction knowledge. Here we provide the results of a pilot study that describes participants’ cortical activations in response to Refraction play. As hypothesized, Refraction play resulted in increases in parietal cortical activations at levels above those measured during spatial-specific activities. Moreover, our results were similar to another fNIRS study by Dresler et al. (J Neural Transm 116(12): 1689–1700, 2009), J. M. Baker (&) Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA e-mail: [email protected] T. Martin A. Aghababyan Advanced Learning Lab, Instructional Technology & Learning Sciences Department, Utah State University, Logan, UT, USA A. Armaghanyan Multisensory Cognition Lab, Department of Psychology, Utah State University, Logan, UT, USA R. Gillam LEAP fNIRS Lab, Communicative Disorders & Deaf Education, Utah State University, Logan, UT, USA 123 Tech Know Learn DOI 10.1007/s10758-015-9251-y