By Arvid Kappas (auth.), Sidney D’Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin (eds.)
The two-volume set LNCS 6974 and LNCS 6975 constitutes the refereed lawsuits of the Fourth overseas convention on Affective Computing and clever interplay, ACII 2011, held in Memphis,TN, united states, in October 2011.
The a hundred thirty five papers during this quantity set offered including three invited talks have been conscientiously reviewed and chosen from 196 submissions. The papers are prepared in topical sections on attractiveness and synthesis of human impact, affect-sensitive functions, methodological concerns in affective computing, affective and social robotics, affective and behavioral interfaces, proper insights from psychology, affective databases, assessment and annotation tools.
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Additional resources for Affective Computing and Intelligent Interaction: 4th International Conference, ACII 2011, Memphis, TN, USA, October 9–12, 2011, Proceedings, Part I
1, 6], and helping some students regulate their boredom. A similar finding is obtained in , where frustrated students who go off-task were seen to demonstrate future engagement. Hence, offtask behavior, within reasonable limits, may actually be beneficial for affect and in turn perhaps even for learning. This finding accords with work by Kreijns  suggesting another positive effect of off-task behavior, improved relationships between students (and in turn improved collaboration). We also find interesting relationships between on-task conversation and affect.
Also includes indeterminate behavior and cases where it was impossible to code affect, such as when a student went to the bathroom or the software crashed. g. 1, 6, 19]. ”. Working silently in the game was coded as on- task solitary behavior, even though the student was competing with another student. 0 observations per student. ”. ”, observation three was not considered to be immediately after observation one). 7 seconds passed between observations. 1 Overall Frequency of Behaviors and Affective States The frequency of each behavior coded, averaged within each student and then averaged across students, is given in Table 1.
4868, pp. 35–50. Springer, Heidelberg (2008) 9. : Continuous Inference of Psychological Stress from Sensory Measurements Collected in the Natural Environment. In: Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Chicago, IL (April 12-14, 2011) 10. : Testing procedures for non-stationarity and non-linearity in physiological signals. Mathematical Biosciences 157, 303–320 (1999) 11. : Online classification of nonstationary data streams.