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» Extracting Student Models for Intelligent Tutoring Systems
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AIED
2005
Springer
15 years 3 months ago
Engagement tracing: using response times to model student disengagement
Time on task is an important predictor for how much students learn. However, students must be focused on their learning for the time invested to be productive. Unfortunately, stude...
Joseph E. Beck
AIED
2009
Springer
15 years 4 months ago
Who Helps When the Tutor Is Asleep?
While many computer tutoring systems have long been delivered as desktop applications, these systems have only recently begun to appear on mobile devices. In this work we apply pri...
Quincy Brown, Dario D. Salvucci, Frank J. Lee, Vin...
AAAI
2007
15 years 3 days ago
Integrated Introspective Case-Based Reasoning for Intelligent Tutoring Systems
Many intelligent tutoring systems (ITSs) have been developed, deployed, assessed, and proven to facilitate learning. However, most of these systems do not generally adapt to new c...
Leen-Kiat Soh
AIED
2009
Springer
15 years 4 months ago
Assessing Student Paraphrases Using Lexical Semantics and Word Weighting
We present in this paper an approach to assessing student paraphrases in the intelligent tutoring system iSTART. The approach is based on measuring the semantic similarity between ...
Vasile Rus, Mihai C. Lintean, Arthur C. Graesser, ...
UM
2007
Springer
15 years 3 months ago
Eliciting Adaptation Knowledge from On-Line Tutors to Increase Motivation
In the classroom, teachers know how to motivate their students and how to exploit this knowledge to adapt or optimize their instruction when a student shows signs of demotivation. ...
Teresa Hurley, Stephan Weibelzahl