Exercise Hierarchical Feature Enhanced Knowledge Tracing
Not on the map. Why?
Abstract (arXiv)
Knowledge tracing is a fundamental task in the computer-aid educational system. In this paper, we propose a hierarchical exercise feature enhanced knowledge tracing framework, which could enhance the ability of knowledge tracing by incorporating knowledge distribution, semantic features, and difficulty features from exercise text. Extensive experiments show the high performance of our framework.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Oct 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 2; 2024: 1; 2025: 0; 2026: 1.
4 papers.
- 2023A quantitative study of NLP approaches to question difficulty estimationcited by 13
- 2023Difficulty-Focused Contrastive Learning for Knowledge Tracing with a Large Language Model-Based Difficulty Predictioncited by 9
- 2024Active Learning to Guide Labeling Efforts for Question Difficulty Estimationcited by 1
- 2026Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Spacecited by 1
- 2026Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space26 Feb 2026
- 2024Active Learning to Guide Labeling Efforts for Question Difficulty Estimation14 Sep 2024
- 2023Difficulty-Focused Contrastive Learning for Knowledge Tracing with a Large Language Model-Based Difficulty Prediction19 Dec 2023
- 2023A quantitative study of NLP approaches to question difficulty estimation17 May 2023