Affective Computing and Intelligent Interaction: 4th - download pdf or read online

By Arvid Kappas (auth.), Sidney D’Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin (eds.)

ISBN-10: 3642245994

ISBN-13: 9783642245992

ISBN-10: 3642246001

ISBN-13: 9783642246005

The two-volume set LNCS 6974 and LNCS 6975 constitutes the refereed complaints of the Fourth foreign 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 awarded including three invited talks have been rigorously reviewed and chosen from 196 submissions. The papers are prepared in topical sections on attractiveness and synthesis of human have an effect on, affect-sensitive purposes, methodological matters in affective computing, affective and social robotics, affective and behavioral interfaces, appropriate 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

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84 were extracted from ECG, 21 from GSR, 21 from each of the EMG channels, and 67 from the RESP channel. 0 [20], a pattern recognition Matlab library, were used for the classifications. Chi square feature selection was used to reduce the dimensionality of the feature space in order to avoid various problems associated with large feature spaces. The top five features were selected from all datasets used in subsequent analysis (data sets are described in the next section). We relied on five features because some preliminary analysis indicated that five features were sufficient to produce consistent classification results without sacrificing performance.

14–24, 2011. © Springer-Verlag Berlin Heidelberg 2011 The Dynamics between Student Affect and Behavior Occurring 15 classroom settings in [1]. Later analysis where self-transitions were eliminated from analysis found evidence that transitions from confusion to frustration are common, but also found that frustration may lead to several different affective patterns, including alleviated frustration, frustration alternating with confusion, and frustration leading into boredom [5]. It has also been found that altering interactive learning environments to display empathy can disrupt vicious cycles of boredom and frustration [15], although not all types of motivational messages have this effect [19].

05. 15. No other affective states were significantly more or less likely than chance to precede or follow off-task behavior. 01. On-task conversation was not significantly preceded by any affective states. 04. Hence, it appears that on-task conversation resolves problems that might cause future frustration. 001. We hypothesize that a confused student might seek help, increasing the likelihood of being on-task. 01. 05, a particularly striking finding given the higher probability of engaged concentration following on-task conversation.

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Affective Computing and Intelligent Interaction: 4th International Conference, ACII 2011, Memphis, TN, USA, October 9–12, 2011, Proceedings, Part I by Arvid Kappas (auth.), Sidney D’Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin (eds.)


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