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JCIT
2008
131views more  JCIT 2008»
13 years 5 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
AAAI
2006
13 years 6 months ago
A Dynamic Mixture Model to Detect Student Motivation and Proficiency
Unmotivated students do not reap the full rewards of using a computer-based intelligent tutoring system. Detection of improper behavior is thus an important component of an online...
Jeffrey Johns, Beverly Park Woolf
UM
2005
Springer
13 years 11 months ago
Detecting When Students Game the System, Across Tutor Subjects and Classroom Cohorts
Building a generalizable detector of student behavior within intelligent tutoring systems presents two challenges: transferring between different cohorts of students (who may devel...
Ryan Shaun Baker, Albert T. Corbett, Kenneth R. Ko...
AIED
2009
Springer
14 years 1 days ago
Intelligent Tutoring Systems with Multiple Representations and Self-Explanation Prompts Support Learning of Fractions
Although a solid understanding of fractions is foundational in mathematics, the concept of fractions remains a challenging one. Previous research suggests that multiple graphical r...
Martina A. Rau, Vincent Aleven, Nikol Rummel
AIED
2007
Springer
13 years 11 months ago
Predicting Students' Performance with SimStudent: Learning Cognitive Skills from Observation
SimStudent is a machine-learning agent that learns cognitive skills by demonstration. SimStudent was originally built as a building block for Cognitive Tutor Authoring Tools to hel...
Noboru Matsuda, William W. Cohen, Jonathan Sewall,...