Preparing for Future Learning with a Tangible User Interface: The Case of Neuroscience

In this paper, we describe the development and evaluation of a microworld-based learning environment for neuroscience. Our system, BrainExplorer, allows students to discover the way neural pathways work by interacting with a tangible user interface. By severing and reconfiguring connections, users can observe how the visual field is impaired and, thus, actively learn from their exploration. An ecological evaluation of BrainExplorer revealed that 1) students who engaged in the open-ended exploration outperformed students who used traditional textbook materials and 2) correctly sequencing activities is fundamental for improving student performance. Participants who used the tabletop first and then studied a text significantly outperformed participants who read a text first and then used the tabletop. Additionally, those results were best predicted by the quality of students' verbalizations while using BrainExplorer. The implications of this study for preparing students for future learning with Tangible User Interfaces are discussed.

[1]  Casey Reas,et al.  Processing: a programming handbook for visual designers and artists , 2007 .

[2]  David S. Goodsell,et al.  Augmented reality with tangible auto-fabricated models for molecular biology applications , 2004, IEEE Visualization 2004.

[3]  Bertrand Schneider,et al.  Phylo-Genie: engaging students in collaborative 'tree-thinking' through tabletop techniques , 2012, CHI.

[4]  L. Standing.  Learning 10000 pictures , 1973 .

[5]  Yvonne Rogers,et al.  Using 'tangibles' to promote novel forms of playful learning , 2003, Interact. Comput..

[6]  Paulo Blikstein,et al.  An Atom is Known by the Company it Keeps: A Constructionist Learning Environment for Materials Science Using Agent-Based Modeling , 2009, Int. J. Comput. Math. Learn..

[7]  Bertrand Schneider,et al.  Benefits of a Tangible Interface for Collaborative Learning and Interaction , 2011, IEEE Transactions on Learning Technologies.

[8]  L. Carruth,et al.  Brains Rule!: a model program for developing professional stewardship among neuroscientists. , 2006, CBE life sciences education.

[9]  Daniel L. Schwartz,et al.  Rethinking transfer: A simple proposal with multiple implica-tions , 1999 .

[10]  Daniel L. Schwartz,et al.  Inventing to Prepare for Future Learning: The Hidden Efficiency of Encouraging Original Student Production in Statistics Instruction , 2004 .

[11]  Ross Bencina,et al.  reacTIVision: a computer-vision framework for table-based tangible interaction , 2007, TEI.

[12]  Paulo Blikstein,et al.  GoGo Board: Augmenting Programmable Bricks for Economically Challenged Audiences , 2004, ICLS.

[13]  D. Brann,et al.  Curriculum development and technology incorporation in teaching neuroscience to graduate students in a medical school environment. , 2006, Advances in physiology education.

[14]  Y Wang,et al.  Bringing Clay and Sand into Digital Design — Continuous Tangible user Interfaces , 2004 .

[15]  Daniel L. Schwartz,et al.  Practicing versus inventing with contrasting cases: The effects of telling first on learning and transfer. , 2011 .

[16]  E. Gibson,et al.  Principles of Perceptual Learning and Development , 1973 .

[17]  Leah Buechley,et al.  The LilyPad Arduino: using computational textiles to investigate engagement, aesthetics, and diversity in computer science education , 2008, CHI.

[18]  Hiroshi Ishii,et al.  Tangible bits: towards seamless interfaces between people, bits and atoms , 1997, CHI.

[19]  Paolo Bonato,et al.  Upper extremity rehabilitation of children with cerebral palsy using accelerometer feedback on a multitouch display , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[20]  Orit Shaer,et al.  Enhancing genomic learning through tabletop interaction , 2011, CHI.

[21]  A. M. White.  The Process of Education , 1994 .

[22]  Sara Price,et al.  What have you done! the role of 'interference' in tangible environments for supporting collaborative learning , 2009, CSCL.

[23]  Leslie Miller,et al.  An online, interactive approach to teaching neuroscience to adolescents. , 2006, CBE life sciences education.

[24]  Laurie D. Edwards,et al.  Microworlds as Representations , 1995 .

[25]  S. Ainsworth.  DeFT: A Conceptual Framework for Considering Learning with Multiple Representations. , 2006 .

[26]  Michael S. Horn,et al.  Modeling on the table: agent-based modeling in elementary school with NetTango , 2011, IDC.

[27]  Patrick Jermann,et al.  A tabletop learning environment for logistics assistants: activating teachers , 2008 .

[28]  Paulo Blikstein,et al.  Mechanix: an interactive display for exploring engineering design through a tangible interface , 2010, TEI.

[29]  John H. Byrne,et al.  Teaching Basic Principles of Neuroscience with Computer Simulations , 2006, Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience.

[30]  Hiroshi Ishii,et al.  Mechanical constraints as computational constraints in tabletop tangible interfaces , 2007, CHI.

[31]  J. Roschelle,et al.  Misconceptions Reconceived: A Constructivist Analysis of Knowledge in Transition , 1994 .

[32]  Yvonne Rogers,et al.  Around the table: are multiple-touch surfaces better than single-touch for children's collaborative interactions? , 2009, CSCL.

[33]  E. Gibson.  Principles of Perceptual Learning and Development , 1969 .

[34]  J. Piaget.  The Language and Thought of the Child , 1927 .

[35]  Kristopher J Preacher,et al.  Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models , 2008, Behavior research methods.

[36]  Marcia K. Johnson,et al.  Source monitoring. , 1993, Psychological bulletin.

[37]  Yvonne Rogers,et al.  Children designing together on a multi-touch tabletop: an analysis of spatial orientation and user interactions , 2009, IDC.

[38]  Yvonne Rogers,et al.  Collaborating around vertical and horizontal large interactive displays: which way is best? , 2004, Interact. Comput..

[39]  Paul Marshall,et al.  Do tangible interfaces enhance learning? , 2007, TEI.

[40]  Ricki Goldman,et al.  Conducting Video Research in the Learning Sciences: Guidance on Selection, Analysis, Technology, and Ethics , 2010 .

[41]  J. Bransford,et al.  Constraints on effective elaboration: Effects of precision and subject generation , 1979 .

[42]  U. Wilensky,et al.  Thinking Like a Wolf, a Sheep, or a Firefly: Learning Biology Through Constructing and Testing Computational Theories—An Embodied Modeling Approach , 2006 .

[43]  E. Keen-Rhinehart,et al.  Interactive Methods for Teaching Action Potentials, an Example of Teaching Innovation from Neuroscience Postdoctoral Fellows in the Fellowships in Research and Science Teaching (FIRST) Program , 2009, Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience.

[44]  F. Schon,et al.  Is clinical neurology really so difficult? , 2002, Journal of neurology, neurosurgery, and psychiatry.