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» Machine Learning Approaches for Inducing Student Models
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ICML
2005
IEEE
14 years 9 months ago
Reducing overfitting in process model induction
In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
ITS
2004
Springer
105views Multimedia» more  ITS 2004»
14 years 2 months ago
The Massive User Modelling System (MUMS)
Developing a learner model containing an accurate representation of a learner’s knowledge is made more difficult in distributed learning environments where the learner uses mult...
Christopher A. Brooks, Mike Winter, Jim E. Greer, ...
AIEDU
2007
93views more  AIEDU 2007»
13 years 8 months ago
UMPTEEN: Named and Anonymous Learner Model Access for Instructors and Peers
Recently, opening the learner model to the learner it represents has become more common in adaptive learning environments. There have also been systems that allow instructors acces...
Susan Bull, Andrew Mabbott, Abdallatif S. Abu-Issa
GPEM
2002
104views more  GPEM 2002»
13 years 8 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec
ICALT
2005
IEEE
14 years 2 months ago
Understanding Object-Oriented Software through Virtual Role-Play
Visualization techniques are commonly used in computer science, particularly for understanding the interactions intrinsic in the object-oriented paradigm. The visualization effect...
Guillermo Jiménez-Díaz, Mercedes G&o...