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,...
We explored the possibility of predicting learners’ affective states (boredom, flow/engagement, confusion, and frustration) by monitoring variations in the cohesiveness of tutori...
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...
Emotions have a functional relevance to learning and achievement. Not surprisingly then, affective diagnoses are an important aspect of expert human mentoring. Computerbased learni...
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...