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» Detecting Student Misuse of Intelligent Tutoring Systems
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99
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EDM
2010
121views Data Mining» more  EDM 2010»
15 years 12 days ago
Identifying Students' Inquiry Planning Using Machine Learning
This research investigates the detection of student meta-cognitive planning processes in real-time using log tracing techniques. We use fine and coarse-grained data distillation, i...
Orlando Montalvo, Ryan Shaun Joazeiro de Baker, Mi...
138
Voted
AH
2008
Springer
15 years 8 months ago
Analysing High-Level Help-Seeking Behaviour in ITSs
Abstract. In this paper, we look at initial results of data mining students’ help-seeking behaviour in two ITSs: SQL-Tutor and EER-Tutor. We categorised help given by these tutor...
Moffat Mathews, Tanja Mitrovic, David Thomson
AIED
2007
Springer
15 years 8 months ago
Mind and Body: Dialogue and Posture for Affect Detection in Learning Environments
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...
Sidney K. D'Mello, Arthur C. Graesser
113
Voted
AIMSA
2008
Springer
15 years 8 months ago
ASAP- An Advanced System for Assessing Chat Participants
: Although instant messaging is a very popular tool for collaboration and it has been used for a wide variety of CSCL tasks, there are only a few applications for assisting the tut...
Mihai Dascalu, Erol-Valeriu Chioasca, Stefan Traus...
NAACL
2004
15 years 3 months ago
Predicting Emotion in Spoken Dialogue from Multiple Knowledge Sources
We examine the utility of multiple types of turn-level and contextual linguistic features for automatically predicting student emotions in human-human spoken tutoring dialogues. W...
Katherine Forbes-Riley, Diane J. Litman