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...
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 present a corpus of spoken dialogues between students and an adaptive Wizard-of-Oz tutoring system, in which student uncertainty was manually annotated in real-time. We detail ...
Katherine Forbes-Riley, Diane J. Litman, Scott Sil...
We discuss the affective aspects of tutoring dialogues in an ITS -called INES- that helps students to practice nursing tasks using a haptic device and a virtual environment. Specia...
Dirk Heylen, Maarten Vissers, Rieks op den Akker, ...
We use χ2 to investigate the context dependency of student affect in our computer tutoring dialogues, targeting uncertainty in student answers in 3 automatically monitorable cont...
Katherine Forbes-Riley, Mihai Rotaru, Diane J. Lit...