Neuroeducational research in the design and use of a learning technology

Many have warned against a direct ‘brain scan to lesson plan’ approach when attempting to transfer insights from neuroscience to the classroom. Similarly, in the effective design and implementation of learning technology, a judicious interrelation of insights associated with diverse theoretical perspectives (e.g., neuroscientific, pedagogical and classroom praxis) may be required. A design-based research approach to the development of learning technology informed by neuroscience may be one way of achieving this interrelation. Accordingly, here we report on some of the preliminary research of a web app, known as ‘zondle Team Play', that allows teachers to teach whole classes using a games-based approach and which draws on concepts from neuroscience. Rather than just exploring ‘what works’ in terms of the technology, low-fidelity prototyping and participant design helped us explore aspects of praxis and affordances of the technological design that were contingent upon each other. Five cycles of design, intervention, analysis and reflection revealed some potential benefits of a neuroeducational approach to learning technology design, including the development of related pedagogy, identification of immediate and future neuroeducational research questions and the development of language and terms suitable for communicating across interdisciplinary boundaries.

[1]  Erol Özçelik,et al.  The effect of uncertainty on learning in game-like environments , 2013, Comput. Educ..

[2]  A. Weinstein,et al.  Computer and Video Game Addiction—A Comparison between Game Users and Non-Game Users , 2010, The American journal of drug and alcohol abuse.

[3]  Dirk J. Heslenfeld,et al.  Activity in human reward-sensitive brain areas is strongly context dependent , 2005, NeuroImage.

[4]  Jelle Jolles,et al.  Neuromyths in Education: Prevalence and Predictors of Misconceptions among Teachers , 2012, Front. Psychology.

[5]  Leslie Stebbins,et al.  Games for a digital age: K-12 market map and investment analysis , 2013 .

[6]  M. Clifford,et al.  Effects of Payoff and Task Context on Academic Risk Taking. , 1991 .

[7]  S. Sala,et al.  Neuroscience in Education: The good, the bad, and the ugly , 2012 .

[8]  S. Varma,et al.  Dyscalculia: From Brain to Education , 2011, Science.

[9]  Rudy McDaniel,et al.  The role teachers' expectations and value assessments of video games play in their adopting and integrating them into their classrooms , 2011, Br. J. Educ. Technol..

[10]  James M. Boyle,et al.  A systematic literature review of empirical evidence on computer games and serious games , 2012, Comput. Educ..

[11]  Nicola Whitton.  Digital Games and Learning: Research and Theory , 2014 .

[12]  W. Schultz,et al.  Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons , 2003, Science.

[13]  Martin Valcke,et al.  Acceptance of game-based learning by secondary school teachers , 2013, Comput. Educ..

[14]  S. Hennessy,et al.  The role of digital artefacts on the interactive whiteboard in supporting classroom dialogue , 2011, J. Comput. Assist. Learn..

[15]  A.J.M. de Jong,et al.  Explorations in Learning and the Brain: On the Potential of Cognitive Neuroscience for Educational Science , 2009 .

[16]  J. Geake.  Neuromythologies in education , 2008 .

[17]  Janna Jackson,et al.  Game‐based teaching: what educators can learn from videogames , 2009 .

[18]  L. Schauble,et al.  Design Experiments in Educational Research , 2003 .

[19]  Carlo Perrotta,et al.  Game-Based Learning: Latest Evidence and Future Directions , 2013 .

[20]  Abbie Brown,et al.  Design experiments: Theoretical and methodological challenges in creating complex interventions in c , 1992 .

[21]  Paul A. Howard-Jones,et al.  Uncertainty and engagement with learning games , 2009 .

[22]  Timothy J. Todd,et al.  Student attitudes toward the use of games to promote learning in the large classroom setting , 2013 .

[23]  A. Cooper,et al.  Predictive Reward Signal of Dopamine Neurons , 2011 .

[24]  R. Cabeza,et al.  Cognitive neuroscience of emotional memory , 2006, Nature Reviews Neuroscience.

[25]  Paul Maharg,et al.  Digital games and learning: modelling learning experiences in the digital age , 2011 .

[26]  D. Brooks,et al.  Evidence for striatal dopamine release during a video game , 1998, Nature.

[27]  P. Howard-Jones,et al.  The Neuroscience Literacy of Trainee Teachers , 2010 .

[28]  Samuel M. McClure,et al.  Short-term memory traces for action bias in human reinforcement learning , 2007, Brain Research.

[29]  N. Whitton.  Game Engagement Theory and Adult Learning , 2011 .

[30]  Janet G. van Hell,et al.  Explorations in learning and the brain : on the potential of cognitive neuroschience for education , 2009 .

[31]  Lucy Avraamidou,et al.  The use of mobile games in formal and informal learning environments: a review of the literature , 2014 .

[32]  Michela Ott,et al.  The potential relevance of cognitive neuroscience for the development and use of technology-enhanced learning , 2015 .

[33]  P. Shizgal,et al.  Neuroscience. Gambling on dopamine. , 2003, Science.

[34]  Ute Leonards,et al.  The neural mechanisms of learning from competitors , 2010, NeuroImage.

[35]  Deena Skolnick Weisberg,et al.  The Seductive Allure of Neuroscience Explanations , 2008, Journal of Cognitive Neuroscience.

[36]  P. Howard-Jones.  Introducing Neuroeducational Research: Neuroscience, Education and the Brain from Contexts to Practice , 2009 .

[37]  Sarah-Jayne Blakemore,et al.  Neuroscience and Education : Issues and Opportunities , 2009 .

[38]  P. Shizgal,et al.  Gambling on Dopamine , 2003, Science.

[39]  Wu Ting-Fang,et al.  Understanding the Brain: the Birth of a Learning Science New insights on learning through cognitive and brain science , 2007 .