Sparse Data Knowledge Tracing
Sparse Data Knowledge Tracing is a knowledge tracing framework designed to model student learning effectively under conditions of limited or sparsely available interaction data by leveraging specialized architectures, regularization techniques, or data augmentation strategies to mitigate the challenges of data insufficiency.
7
Publications
653
Citations
17
Authors
9
Institutions
Publications per year
2017–2026
7
Parents
7
A Self-Attentive model for Knowledge Tracing
Shalini Pandey, George Karypis · arXiv (Cornell University) · 2019 · 190 citations · Full text
Prerequisite-Driven Deep Knowledge Tracing
Penghe Chen, Yu Lu, Vincent W. Zheng et al. · 2018 · 165 citations
Education, Educational Technology, Intelligent Tutoring Systems +13
1–5 of 7
17
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2
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2
h-index
2
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1
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1–5 of 17
9
RIKEN Center for Advanced Intelligence Project
Tokyo, Japan
2 h-index
2 publications
201 citations

Kyoto University
Kyoto, Japan
2 h-index
2 publications
201 citations
University of Minnesota System
Minneapolis, United States
1 h-index
2 publications
380 citations
Advanced Digital Sciences Center
Singapore, Singapore
1 h-index
1 publications
165 citations

Beijing Normal University
Beijing, China
1 h-index
3 publications
495 citations

National Institute of Informatics
Tokyo, Japan
1 h-index
3 publications
201 citations
University of Chinese Academy of Sciences
Beijing, China
1 h-index
2 publications
134 citations

Shandong Normal University
Jinan, China
1 h-index
5 publications
95 citations
1–8 of 9
Repository · 4 publications · 233 citations
3
h-index
1 publications · 19 citations
1
h-index
1 publications · 67 citations
1
h-index
Conference · 1 publications · 186 citations
1
h-index
1 publications · 23 citations
1–5