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 complaints of the Fourth foreign convention on Affective Computing and clever interplay, ACII 2011, held in Memphis,TN, united states, in October 2011.
The one hundred thirty five papers during this quantity set provided including three invited talks have been conscientiously reviewed and chosen from 196 submissions. The papers are geared up in topical sections on acceptance and synthesis of human impact, affect-sensitive functions, methodological concerns in affective computing, affective and social robotics, affective and behavioral interfaces, suitable insights from psychology, affective databases, review 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
Table 3. Base-rate adjusted likelihood (average D’Mello’s L across students) and standard deviation (in parentheses) of each behavior-affect transition (denoted by arrow) or co- occurence (denoted by dash-dash) within the data set. 1) in italics. Off TaskÆ Bored Off TaskÆ Eng. Conc. OnTask Conv Æ Bored OnTask Conv Æ Eng. Conc. Bored Æ Off Task Eng. Conc. Æ Off Task Bored Æ OnTask Conv Eng. Conc. Æ OnTask Conv Off Task -- Bored Off Task -- Eng. Conc. OnTask Conv -- Bored OnTask Conv -- Eng. Conc.
The intelligent tutoring systems community has begun actively exploring computational models of affect, and game-based learning environments present a significant opportunity for investigating student affect in interactive learning. One family of game-based learning environments, narrative-centered learning environments, offer a particularly compelling laboratory for investigating student affect. In narrativecentered environments, learning activities play out in dynamically generated interactive narratives and training scenarios.
3, 22], and goes further, suggesting that collaborative episodes during individual learning often lead to the types of affect and concentration that are associated with successful learning. It may be interesting to investigate, in future research, what the affective impacts are of periods of individual work during collaborative learning. Overall, the findings presented here suggest that the interplay between student behavior and affect, within educational settings, is more complex than previously thought.