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Deep learning based knowledge tracing model has been shown to outperform traditional knowledge tracing model without the need for human-engineered features, yet its parameters and representations have long been criticized for not being explainable.
Probabilistic models for some intelligence and attainment tests
Georg Rash · 1960
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Knowledge tracing: modeling the acquisition of procedural knowledge
Albert T. Corbett and John R. Anderson · 1995
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Learning factors analysis – a general method for cognitive model evaluation and improvement
Hao Cen, Kenneth R. Koedinger, and Brian Junker · 2006
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Performance factors analysis – a new alternative to knowledge tracing
Philip I. Pavlik, Hao Cen, and Kenneth R. Koedinger · 2009
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Modeling individualization in a Bayesian networks implementation of knowledge tracing
Zachary A. Pardos and Neil T. Heffernan · 2010
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The form of the forgetting curve and the fate of memories
Lee Averell and Andrew Heathcote · 2011
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KT-IDEM: Introducing item difficulty to the knowledge tracing model
Zachary A. Pardos and Neil T. Heffernan · 2011
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S. Corrado, and Jeff Dean · 2013
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Individualized Bayesian knowledge tracing models
Michael V. Yudelson, Kenneth R. Koedinger, and Geoffrey J. Gordon · 2013
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Integrating knowledge tracing and item response theory: A tale of two frameworks
Mohammad M. Khajah, Yun Huang, José P. González-Brenes, Michael C. Mozer, and Peter Brusilovsky · 2014
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Item response theory for measurement validity
Frances M. Yang and Solon T. Kao · 2014
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Move your lamp post: Recent data reflects learner knowledge better than older data
April Galyardt and Ilya Goldin · 2015
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Deep knowledge tracing
Chris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, and Jascha Sohl-Dickstein · 2015
How deep is knowledge tracing
Mohammad M. Khajah, Robert V. Lindsey, and Michael C. Mozer · 2016
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Towards Bayesian deep learning: A framework and some existing methods
Hao Wang and Dit-Yan Yeung · 2016
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Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation
Kevin H. Wilson, Yan Karklin, Bojian Han, and Chaitanya Ekanadham · 2016
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Dynamic key-value memory networks for knowledge tracing
Jiani Zhang, Xingjian Shi, Irwin King, and Dit-Yan Yeung · 2017
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Exercise-enhanced sequential modeling for student performance prediction
Yu Su, Qingwen Liu, Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen, Chris Ding, Si Wei, and Guoping Hu · 2018
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Addressing two problems in deep knowledge tracing via prediction-consistent regularization
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Cited alongside, same era.
Hybrid computing using a neural network with dynamic external memory
Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwińska, Sergio G. Colmenarejo, Edward Grefenstette, Tiago Ramalho, John Agapiou, et al · 2016
Cited alongside, same era.
Chun-Kit Yeung and Dit-Yan Yeung · 2018
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Office of Educational Assessment, University of Washington
Understanding Item Analyses · 2019
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