https://github.com/zmy-9/cmvf
공식 코드Cognition-Mode Aware Variational Representation Learning Framework for Knowledge Tracing
Papers with Code 아카이브
Knowledge Tracing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 2
- 보존된 평가 기록
- 10
Knowledge Tracing is the task of modelling student knowledge over time so that we can accurately predict how students will perform on future interactions. Improvement on this task means that resources can be suggested to students based on their individual needs, and content which is predicted to be too easy or too hard can be skipped or delayed.
Source: Deep Knowledge Tracing
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zmy-9/mf-dakt
공식 코드https://github.com/zmy-9/sfkt
공식 코드https://github.com/zyy-2001/DisKT
공식 코드Disentangled Knowledge Tracing for Alleviating Cognitive Bias
https://github.com/zyy-2001/cuff-kt
공식 코드https://github.com/Chang-Chia-Chi/SaintPlus-Knowledge-Tracing-Pytorch
SAINT+: Integrating Temporal Features for EdNet Correctness Prediction
https://github.com/Fusion4233919/DSAKT
https://github.com/Fusion4233919/SAKT
https://github.com/Machine-Learning-for-Everyone-ML4E/CoP-Code-of-Papers
https://github.com/MindCode-4/code-11/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MindCode-4/code-6/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MindSpore-scientific-2/code-9/tree/main/Last-Query-Transformer-RNN
https://github.com/MindSpore-scientific/code-1/tree/main/Last-Query-Transformer-RNN
https://github.com/MindSpore-scientific/code-3/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/Shivanandmn/Knowledge-Tracing-SAINT
Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
https://github.com/Shivanandmn/SAINT_plus-Knowledge-Tracing-
Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
https://github.com/YangZhouEdu/DKT_pytorch
https://github.com/ZhijieXiong/dlkt
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations
https://github.com/ZhijieXiong/pyedmine
https://github.com/ai4ed/xes3g5m
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models
https://github.com/ajenningsfrankston/graph_kt
https://github.com/apexedm/gikt
https://github.com/arghosh/NeurIPSEducation2020
Option Tracing: Beyond Correctness Analysis in Knowledge Tracing
https://github.com/arshadshk/Last_Query_Transformer_RNN-PyTorch
https://github.com/arshadshk/SAINT-pytorch
Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
https://github.com/arshadshk/SAKT-pytorch
https://github.com/bcaitech1/p4-dkt-no_caffeine_no_gain
https://github.com/bigdata-ustc/ekt
EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction
https://github.com/ckyeungac/DeepIRT
Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory
https://github.com/jarviszhb/KnowledgeTracing
https://github.com/jdxyw/deepKT
https://github.com/jilljenn/slam2018
Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing
https://github.com/lucky7-code/DKVMN
https://github.com/maroxtn/SAINT-Transformer-riiid-kaggle
SAINT+: Integrating Temporal Features for EdNet Correctness Prediction
https://github.com/nanzhaogang/contrib/tree/master/application/a-self-attentive-model-for-knowledge-tracing
https://github.com/pwc-1/Paper-9/tree/main/1/xmod
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.