An Optical Brain Imaging Study on the Improvements in Mathematical Fluency from Game-based Learning

In this study we examined the effectiveness of game-based learning in improving math fluency compared to a conventional drill and practice approach. An optical brain imaging method called functional near-infrared spectroscopy (fNIR) was utilized to assess changes in brain activation in prefrontal cortex related to cognitive load and working memory functions, so that the improvement gained by the increased attentional and cognitive training involved in a mobile game called MathDash could be examined in terms of how and why game-based learning can be effective. Overall, our experiment with college students indicated that Math Dash was equally effective in terms of improving computational fluency in comparison to the drill and practice approach.

[1]  Atsusi Hirumi,et al.  Examining the pedagogical foundations of modern educational computer games , 2008, Comput. Educ..

[2]  Masashi Kiguchi,et al.  Greater contribution of cerebral than extracerebral hemodynamics to near-infrared spectroscopy signals for functional activation and resting-state connectivity in infants , 2014, Neurophotonics.

[3]  M. Buchsbaum,et al.  Regional glucose metabolic changes after learning a complex visuospatial/motor task: a positron emission tomographic study , 1992, Brain Research.

[4]  Arthur W Toga,et al.  Spatiotemporal Evolution of Functional Hemodynamic Changes and Their Relationship to Neuronal Activity , 2005, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[5]  A. Su,et al.  The National Council of Teachers of Mathematics , 1932, The Mathematical Gazette.

[6]  Douglas Fuchs,et al.  The Effects of Computer-Assisted Instruction on Number Combination Skill in At-Risk First Graders , 2006, Journal of learning disabilities.

[7]  N. Logothetis,et al.  Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1 , 2006, Nature Neuroscience.

[8]  Barbara L. Grabowski,et al.  Gameplaying for maths learning: cooperative or not? , 2007, Br. J. Educ. Technol..

[9]  Y. Kafai.  The Educational Potential of Electronic Games: From Games-to-Teach to Games-to-Learn , 2001 .

[10]  Marcelo Mendonça Teixeira,et al.  The Educational Potential of Electronic Games , 2016 .

[11]  Lloyd P. Rieber,et al.  DESIGNING LEARNING ENVIRONMENTS THAT EXCITE SERIOUS PLAY , 2001 .

[12]  Nancy C. Jordan,et al.  A longitudinal study of mathematical competencies in children with specific mathematics difficulties versus children with comorbid mathematics and reading difficulties. , 2003, Child development.

[13]  Jan Theeuwes,et al.  OpenSesame: An open-source, graphical experiment builder for the social sciences , 2011, Behavior Research Methods.

[14]  J. Patton,et al.  A Life Skills Approach to Mathematics Instruction , 1997, Journal of learning disabilities.

[15]  Hasan Ayaz,et al.  Differentiating functions of the lateral and medial prefrontal cortex in motor response inhibition , 2014, NeuroImage.

[16]  Thomas W. Malone,et al.  Toward a Theory of Intrinsically Motivating Instruction , 1981, Cogn. Sci..

[17]  J. Gee,et al.  ON EMPIRICAL EVIDENCE ON GAMES AND LEARNING , 2015 .

[18]  David C. Geary,et al.  Children's Mathematical Development: Research and Practical Applications , 1996 .

[19]  Hasan Ayaz,et al.  Sliding-window motion artifact rejection for Functional Near-Infrared Spectroscopy , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[20]  Hiroki Sato,et al.  A NIRS–fMRI investigation of prefrontal cortex activity during a working memory task , 2013, NeuroImage.

[21]  Susan Jo Russell,et al.  Developing Computational Fluency with Whole Numbers. , 2000 .

[22]  Hasan Ayaz,et al.  Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation , 2011, Journal of visualized experiments : JoVE.

[23]  Russell Gersten,et al.  Early Identification and Interventions for Students With Mathematics Difficulties , 2005, Journal of learning disabilities.

[24]  E. Hillman.  Coupling mechanism and significance of the BOLD signal: a status report. , 2014, Annual review of neuroscience.

[25]  M. Green,et al.  Digital natives , 2012, BDJ.

[26]  Lloyd P. Rieber,et al.  Animation as feedback in a computer-based simulation: Representation matters , 1996 .

[27]  최영한,et al.  미국 NCTM의 Principles and Standards for School Mathematics에 나타난 수학과 교수,학습의 이론 , 2002 .

[28]  Fengfeng Ke,et al.  A case study of computer gaming for math: Engaged learning from gameplay? , 2008, Comput. Educ..

[29]  A. Ruocco,et al.  A problem-solving task specialized for functional neuroimaging: validation of the Scarborough adaptation of the Tower of London (S-TOL) using near-infrared spectroscopy , 2014, Front. Hum. Neurosci..

[30]  Robert S. Siegler,et al.  Rightstart: Providing the central conceptual prerequisites for first formal learning of arithmetic to students at risk for school failure. , 1994 .

[31]  D. Kleinfeld,et al.  Suppressed Neuronal Activity and Concurrent Arteriolar Vasoconstriction May Explain Negative Blood Oxygenation Level-Dependent Signal , 2007, The Journal of Neuroscience.

[32]  A Villringer,et al.  Near-infrared spectroscopy: does it function in functional activation studies of the adult brain? , 2000, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[33]  S. Griffin,et al.  Building number sense with Number Worlds: a mathematics program for young children , 2004 .

[34]  Kamran Sedig,et al.  From Play to Thoughtful Learning: A Design Strategy to Engage Children With Mathematical Representations , 2008 .

[35]  David C. Geary,et al.  Early Foundations for Mathematics Learning and Their Relations to Learning Disabilities , 2013, Current directions in psychological science.

[36]  Nancy C. Jordan,et al.  Using Kindergarten Number Sense to Predict Calculation Fluency in Second Grade , 2008, Journal of learning disabilities.

[37]  C. Aubrey,et al.  Early mathematics development and later achievement: Further evidence , 2006 .

[38]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[39]  William H. Kraus.  Using a Computer Game to Reinforce Skills in Addition Basic Facts in Second Grade , 1981 .

[40]  David A. Boas,et al.  Quantification of the cortical contribution to the NIRS signal over the motor cortex using concurrent NIRS-fMRI measurements , 2012, NeuroImage.

[41]  Atsusi Hirumi,et al.  Effects of a computer game on mathematics achievement and class motivation: an experimental study , 2008 .

[42]  K. Izzetoglu,et al.  Registering fNIR Data to Brain Surface Image using MRI templates , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[43]  Britton Chance,et al.  Functional Optical Brain Imaging Using Near-Infrared During Cognitive Tasks , 2004, Int. J. Hum. Comput. Interact..

[44]  Hasan Ayaz,et al.  Optical brain monitoring for operator training and mental workload assessment , 2012, NeuroImage.

[45]  B. Onaral,et al.  Frontal lobe role in simple arithmetic calculations: An fNIR study , 2012, Neuroscience Letters.

[46]  Lloyd P. Rieber,et al.  Seriously considering play: Designing interactive learning environments based on the blending of microworlds, simulations, and games , 1996 .

[47]  M. Prensky.  Digital Natives, Digital Immigrants Part 1 , 2001 .