Fine-grained Knowledge State Modeling
Fine-Grained Knowledge State Modeling is a computational framework that belongs to the class of knowledge tracing models, distinguished by its ability to represent student knowledge at a highly detailed, granular level—such as individual misconceptions or sub-skills—rather than broad skill categories, enabling precise diagnosis and tracking of learning trajectories.
29
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2.5K
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116
Authors
32
Institutions
Publications per year
2017–2026
25
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29
Dynamic Key-Value Memory Networks for Knowledge Tracing
Jiani Zhang, Xingjian Shi, Irwin King et al. · 2017 · 814 citations · Full text
Knowledge Tracing with Sequential Key-Value Memory Networks
2019 · 199 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
Deep Knowledge Tracing On Programming Exercises
Lisa Wang, Angela Sy, Larry Liu et al. · 2017 · 121 citations
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University of Science and Technology of China
Hefei, China
5 h-index
27 publications
1.6K citations

Beijing Normal University
Beijing, China
4 h-index
12 publications
1.1K citations

San Diego State University
San Diego, United States
2 h-index
6 publications
499 citations
Advanced Digital Sciences Center
Singapore, Singapore
2 h-index
2 publications
204 citations
Education University of Hong Kong
Tai Po, Hong Kong
2 h-index
6 publications
499 citations

Anhui University
Hefei, China
2 h-index
3 publications
290 citations
Central China Normal University
Wuhan, China
2 h-index
10 publications
332 citations
Northeast Normal University
Changchun, China
2 h-index
6 publications
499 citations
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5 publications · 275 citations
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Repository · 3 publications · 122 citations
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Conference · 1 publications · 23 citations
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1 publications · 74 citations
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1 publications · 36 citations
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