Foundations of Augmented Cognition. Advancing Human Performance and Decision-Making through Adaptive Systems

Neurophysiological compliance is a correlation of neurophysiological measures (synchronicity) between individuals. Higher compliance among team members is related to better performance, and higher synchronicity occurs during emotional moments of a stimulus. The aim of the current study is to examine whether synchrony may be observable via peripheral nervous system (PNS) activity. We used inter-subject correlation (ISC) analysis to assess whether synchronicity of PNS measures are related to stimulus emotionality or similarity in behavioral responses. Participants viewed a 100-second emotional video, followed by an appeal to donate experimental earnings to a related charity. We found high ISC for cardiac and electrodermal activity (EDA) between donors versus non-donors. For both groups, we found an association between ISC of cardiac activity and emotional moments in the stimulus. For non-donors we found an association between ISC of EDA and emotional moments. Our findings indicate that PNS measures yield similar results to neurophysiological measures.

[1]  Mark G. Core,et al.  Intelligent Tutoring for Interpersonal and Intercultural Skills , 2007 .

[2]  Ronald H. Stevens,et al.  The organizational neurodynamics of teams. , 2013, Nonlinear dynamics, psychology, and life sciences.

[3]  Marios C. Angelides,et al.  Formalising tutoring strategy selection in multimedia tutoring systems , 1999, Inf. Softw. Technol..

[4]  Vincent Aleven,et al.  Defining "Ill-Defined Domains"; A literature survey. , 2006 .

[5]  Paula J. Durlach,et al.  An Adaptive Training Prototype for Small Unmanned Aerial System Employment , 2010 .

[6]  Mark A. McDaniel,et al.  On the design of adaptive treatments for individualized instructional systems , 1981 .

[7]  K. Shockley,et al.  Mutual interpersonal postural constraints are involved in cooperative conversation. , 2003, Journal of experimental psychology. Human perception and performance.

[8]  Kurt VanLehn,et al.  The Behavior of Tutoring Systems , 2006, Int. J. Artif. Intell. Educ..

[9]  Demetrios G. Sampson,et al.  Decision models in the design of adaptive educational hypermedia systems , 2011 .

[10]  J. Chatwin.  Conversation analysis. , 2004, Complementary therapies in medicine.

[11]  Antonija Mitrovic,et al.  Fidelity and Efficiency of Knowledge Representations for Intelligent Tutoring Systems , 2007 .

[12]  Kathleen T. Ashenfelter.  Simultaneous analysis of verbal and nonverbal data during conversation: Symmetry and turn-taking , 2011 .

[13]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[14]  Line Garnero,et al.  Inter-Brain Synchronization during Social Interaction , 2010, PloS one.

[15]  R. Kane,et al.  Please Scroll down for Article the Clinical Neuropsychologist Construct Validity of Selected Automated Neuropsychological Assessment Metrics (anam) Battery Measures , 2022 .

[16]  Arthur C. Graesser,et al.  Language and Discourse Are Powerful Signals of Student Emotions during Tutoring , 2012, IEEE Transactions on Learning Technologies.

[17]  Ronald H. Stevens,et al.  Cognitive Neurophysiologic Synchronies , 2012, Hum. Factors.

[18]  P. L. Brusilovskiy.  The Constructionand ApplicationofStudent Models in Intelligent TutoringSystems , 1994 .

[19]  John R. Anderson,et al.  Rules of the Mind , 1993 .

[20]  Tom Murray,et al.  An Overview of Intelligent Tutoring System Authoring Tools: Updated Analysis of the State of the Art , 2003 .

[21]  Beverly Park Woolf,et al.  Student Modeling , 2010, Advances in Intelligent Tutoring Systems.

[22]  Daniel Olguin Olguin,et al.  Sociometric badges : wearable technology for measuring human behavior , 2007 .

[23]  Ronald H. Stevens,et al.  Can Neurophysiologic Synchronies Provide a Platform for Adapting Team Performance? , 2009, HCI.

[24]  Nancy J. Cooke,et al.  Team coordination dynamics. , 2010, Nonlinear dynamics, psychology, and life sciences.

[25]  Keith Davids,et al.  Nonlinear Dynamics, Psychology, and Life Sciences Special Issue on Psychomotor Coordination and Control Introduction to Special Issue on Psychomotor Coordination and Control , 2008 .

[26]  Benedict du Boulay,et al.  Implementation of motivational tactics in tutoring systems , 1995 .

[27]  Taemie Kim,et al.  Enhancing Organizational Communication using Sociometric Badges , 2007 .

[28]  W. Lewis Johnson,et al.  Animated Agents for Procedural Training in Virtual Reality: Perception, Cognition, and Motor Control , 1999, Appl. Artif. Intell..

[29]  C. E. Englund,et al.  Unified Tri-Service Cognitive Performance Assessment Battery (UTC-PAB). 1. Design and Specification of the Battery , 1987 .

[30]  Vincent Aleven,et al.  Scaling Up Programming by Demonstration for Intelligent Tutoring Systems Development: An Open-Access Web Site for Middle School Mathematics Learning , 2009, IEEE Transactions on Learning Technologies.

[31]  Ryan Shaun Joazeiro de Baker,et al.  Modeling and understanding students' off-task behavior in intelligent tutoring systems , 2007, CHI.