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Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts.
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Ekt: Exercise-aware knowledge tracing for student performance prediction
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One minute is enough: Early prediction of student success and event-level difficulty during a novice programming task
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Using prerequisites to extract concept maps from textbooks
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Tracking knowledge proficiency of students with educational priors
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Evolution of an intelligent deductive logic tutor using data-driven elements
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Assessing implicit science learning in digital games
E. Rowe, J. Asbell-Clarke, R. S. Baker, M. Eagle, A. G. Hicks, T. M. Barnes, R. A. Brown, and T. Edwards · 2017
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Attention is all you need
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Hierarchical reinforcement learning for pedagogical policy induction
G. Zhou, H. Azizsoltani, M. S. Ausin, T. Barnes, and M. Chi · 2019
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Towards an appropriate query, key, and value computation for knowledge tracing
Y. Choi, Y. Lee, J. Cho, J. Baek, B. Kim, Y. Cha, D. Shin, C. Bae, and J. Heo · 2020
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Ednet: A large-scale hierarchical dataset in education
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When is deep learning the best approach to knowledge tracing?
T. Gervet, K. Koedinger, J. Schneider, T. Mitchell, et al · 2020
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Context-aware attentive knowledge tracing
A. Ghosh, N. Heffernan, and A. S. Lan · 2020
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Extending the hint factory for the assistance dilemma: A novel, data-driven helpneed predictor for proactive problem-solving help
M. Maniktala, C. Cody, A. Isvik, N. Lytle, M. Chi, and T. Barnes · 2020
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pybkt: An accessible python library of bayesian knowledge tracing models
A. Badrinath, F. Wang, and Z. Pardos · 2021
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Knowing" when" and" where": Temporal-astnn for student learning progression in novice programming tasks
Y. Mao, Y. Shi, S. Marwan, T. W. Price, T. Barnes, and M. Chi · 2021
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More with less: Exploring how to use deep learning effectively through semi-supervised learning for automatic bug detection in student code
Y. Shi, Y. Mao, T. Barnes, M. Chi, and T. W. Price · 2021
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Toward semi-automatic misconception discovery using code embeddings
Y. Shi, K. Shah, W. Wang, S. Marwan, P. Penmetsa, and T. Price · 2021
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Saint+: Integrating temporal features for ednet correctness prediction
D. Shin, Y. Shim, H. Yu, S. Lee, B. Kim, and Y. Choi · 2021
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