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» Detecting Student Misuse of Intelligent Tutoring Systems
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AIED
2005
Springer
14 years 1 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
FLAIRS
2000
13 years 9 months ago
Reasoning from Data Rather than Theory
Thecurrent frameworkfor constructing intelligent tutoring systems(ITS) is to use psychological/pedagogical theories of learning, and encode this knowledgeinto the tutor. However,t...
Joseph E. Beck, Beverly Park Woolf
AIED
2009
Springer
14 years 2 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...
EDM
2008
141views Data Mining» more  EDM 2008»
13 years 9 months ago
Acquiring Background Knowledge for Intelligent Tutoring Systems
One of the unresolved problems faced in the construction of intelligent tutoring systems is the acquisition of background knowledge, either for the specification of the teaching st...
Cláudia Antunes
AAAI
2007
13 years 10 months 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