Knowledge Tracing

39 papers with code • 2 benchmarks • 1 datasets

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


Use these libraries to find Knowledge Tracing models and implementations


Most implemented papers

Deep Knowledge Tracing

chrispiech/DeepKnowledgeTracing NeurIPS 2015

Knowledge tracing---where a machine models the knowledge of a student as they interact with coursework---is a well established problem in computer supported education.

A Self-Attentive model for Knowledge Tracing

shalini1194/SAKT 16 Jul 2019

Knowledge tracing is the task of modeling each student's mastery of knowledge concepts (KCs) as (s)he engages with a sequence of learning activities.

Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing

arshadshk/SAINT-pytorch 14 Feb 2020

To the best of our knowledge, this is the first work to suggest an encoder-decoder model for knowledge tracing that applies deep self-attentive layers to exercises and responses separately.

SAINT+: Integrating Temporal Features for EdNet Correctness Prediction

arshadshk/SAINT-pytorch 19 Oct 2020

We propose SAINT+, a successor of SAINT which is a Transformer based knowledge tracing model that separately processes exercise information and student response information.

DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills

BenoitChoffin/das3h 14 May 2019

In this article, we first frame the research problem of optimizing an adaptive and personalized spaced repetition scheduler when memorization concerns the application of underlying multiple skills.

Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization

ckyeungac/deep-knowledge-tracing-plus 6 Jun 2018

In recent years, a recurrent neural network model called deep knowledge tracing (DKT) has been proposed to handle the knowledge tracing task and literature has shown that DKT generally outperforms traditional methods.

Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory

ckyeungac/DeepIRT 26 Apr 2019

Deep learning based knowledge tracing model has been shown to outperform traditional knowledge tracing model without the need for human-engineered features, yet its parameters and representations have long been criticized for not being explainable.

GIKT: A Graph-based Interaction Model for Knowledge Tracing

Rimoku/GIKT 13 Sep 2020

With the rapid development in online education, knowledge tracing (KT) has become a fundamental problem which traces students' knowledge status and predicts their performance on new questions.

Last Query Transformer RNN for knowledge tracing

arshadshk/Last_Query_Transformer_RNN-PyTorch 10 Feb 2021

The novel point of the model is that it only uses the last input as query in transformer encoder, instead of all sequence, which makes QK matrix multiplication in transformer Encoder to have O(L) time complexity, instead of O(L^2).

Option Tracing: Beyond Correctness Analysis in Knowledge Tracing

arghosh/OptionTracing 19 Apr 2021

Knowledge tracing refers to a family of methods that estimate each student's knowledge component/skill mastery level from their past responses to questions.