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OZCHI
2005
ACM
13 years 10 months ago
Making sense of student use of nonverbal cues for intelligent tutoring systems
Many software systems would significantly improve performance if they could interpret the nonverbal cues in their user’s interactions as humans normally do. Currently, Intellige...
Farhad Dadgostar, Hokyoung Ryu, Abdolhossein Sarra...
HCI
2009
13 years 2 months ago
Responding to Learners' Cognitive-Affective States with Supportive and Shakeup Dialogues
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...
AAAI
1998
13 years 6 months ago
Procedural Help in Andes: Generating Hints Using a Bayesian Network Student Model
One of the most important problems for an intelligent tutoring system is deciding how to respond when a student asks for help. Responding cooperatively requires an understanding o...
Abigail S. Gertner, Cristina Conati, Kurt VanLehn
IADIS
2003
13 years 6 months ago
A Facial Expression Analysis Component for Affective Tutoring Systems
Intelligent tutoring systems (ITS) provide individualised instruction. They offer many advantages over the traditional classroom scenario: they are always available, non-judgement...
Scott P. Overmyer, Hamid Gholam Hosseini, Chao Fan...
UM
2005
Springer
13 years 10 months ago
Modeling Students' Metacognitive Errors in Two Intelligent Tutoring Systems
Intelligent tutoring systems help students acquire cognitive skills by tracing students’ knowledge and providing relevant feedback. However, feedback that focuses only on the cog...
Ido Roll, Ryan Shaun Baker, Vincent Aleven, Bruce ...