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» Emotions and Learning with AutoTutor
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AIED
2009
Springer
13 years 11 months ago
The Relationship Between Modality and Metacognition While Interacting with AutoTutor
In this paper we explored the relationship between metacognitive statements and learning gains with students’ typed and spoken interactions with an intelligent tutoring system, c...
Jeremiah Sullins, Moongee Jeon, Sidney K. D'Mello,...
AIED
2009
Springer
13 years 9 months ago
Cohesion Relationships in Tutorial Dialogue as Predictors of Affective States
We explored the possibility of predicting learners’ affective states (boredom, flow/engagement, confusion, and frustration) by monitoring variations in the cohesiveness of tutori...
Sidney K. D'Mello, Nia Dowell, Arthur C. Graesser
SAC
2008
ACM
13 years 4 months ago
Learning to identify emotions in text
This paper describes experiments concerned with the automatic analysis of emotions in text. We describe the construction of a large data set annotated for six basic emotions: ange...
Carlo Strapparava, Rada Mihalcea
ICALT
2010
IEEE
13 years 3 months ago
Modelling Affect in Learning Environments - Motivation and Methods
Emotions have a functional relevance to learning and achievement. Not surprisingly then, affective diagnoses are an important aspect of expert human mentoring. Computerbased learni...
Shazia Afzal, Peter Robinson
ICDM
2010
IEEE
186views Data Mining» more  ICDM 2010»
13 years 3 months ago
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model
Human emotion is one important underlying force affecting and affected by the dynamics of social networks. An interesting question is "can we predict a person's mood base...
Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jing...