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» Contextual Slip and Prediction of Student Performance after ...
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UM
2007
Springer
14 years 1 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...
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
UM
2010
Springer
13 years 11 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...
PROCEDIA
2010
157views more  PROCEDIA 2010»
13 years 6 months ago
Recommender system for predicting student performance
Recommender systems are widely used in many areas, especially in e-commerce. Recently, they are also applied in e-learning tasks such as recommending resources (e.g. papers, books...
Nguyen Thai-Nghe, Lucas Drumond, Artus Krohn-Grimb...
UMUAI
2008
110views more  UMUAI 2008»
13 years 7 months ago
Modeling self-efficacy in intelligent tutoring systems: An inductive approach
Abstract. Self-efficacy is an individual's belief about her ability to perform well in a given situation. Because selfefficacious students are effective learners, endowing int...
Scott W. McQuiggan, Bradford W. Mott, James C. Les...