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JCIT
2008
131views more  JCIT 2008»
13 years 4 months ago
Intelligent Tutoring System: Predicting Students Results Using Neural Networks
In this paper we propose methods to utilize Artificial Neural Networks to obtain knowledge for the management of educational resources. The final evaluations provide us a model th...
E. R. Naganathan, R. Venkatesh, N. Uma Maheswari
EDM
2010
160views Data Mining» more  EDM 2010»
13 years 6 months ago
Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...
UM
2007
Springer
13 years 11 months ago
The Effect of Model Granularity on Student Performance Prediction Using Bayesian Networks
A standing question in the field of Intelligent Tutoring Systems and User Modeling in general is what is the appropriate level of model granularity (how many skills to model) and h...
Zachary A. Pardos, Neil T. Heffernan, Brigham Ande...
ITS
2004
Springer
138views Multimedia» more  ITS 2004»
13 years 10 months ago
A Metacognitive ACT-R Model of Students' Learning Strategies in Intelligent Tutoring Systems
Research has shown that students’ problem-solving actions vary in type and duration. Among other causes, this behavior is a result of strategies that are driven by different goal...
Ido Roll, Ryan Shaun Baker, Vincent Aleven, Kennet...
UM
2010
Springer
13 years 8 months ago
Ranking Feature Sets for Emotion Models Used in Classroom Based Intelligent Tutoring Systems
Abstract. Recent progress has been made by using sensors with Intelligent Tutoring Systems in classrooms in order to predict the affective state of students users. If tutors are a...
David G. Cooper, Kasia Muldner, Ivon Arroyo, Bever...