We explored the reliability of detecting a learner's affect from conversational features extracted from interactions with AutoTutor, an intelligent tutoring system that helps...
Sidney K. D'Mello, Scotty D. Craig, Amy M. Withers...
We investigated the potential of automatic detection of a learner’s affective states from posture patterns and dialogue features obtained from an interaction with AutoTutor, an i...
We have developed and evaluated an affect-sensitive version of AutoTutor, a dialogue based ITS that simulates human tutors. While the original AutoTutor is sensitive to learners’...
Sidney K. D'Mello, Blair Lehman, Jeremiah Sullins,...
This paper describes two affect-sensitive variants of an existing intelligent tutoring system called AutoTutor. The new versions of AutoTutor detect learners' boredom, confusi...
Sidney K. D'Mello, Scotty D. Craig, Karl Fike, Art...
Automatic detection of communication errors in conversational systems has been explored extensively in the speech community. However, most previous studies have used only acoustic...