Knowledge Tracing
69 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
Libraries
Use these libraries to find Knowledge Tracing models and implementations
EdNet
Most implemented papers
Option Tracing: Beyond Correctness Analysis in Knowledge Tracing
Knowledge tracing refers to a family of methods that estimate each student's knowledge component/skill mastery level from their past responses to questions.
Application of Deep Self-Attention in Knowledge Tracing
The development of intelligent tutoring system has greatly influenced the way students learn and practice, which increases their learning efficiency.
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models
However, the success behind deep learning based knowledge tracing (DLKT) approaches is still left somewhat unknown and proper measurement and analysis of these DLKT approaches remain a challenge.
Back to the Basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation
Estimating student proficiency is an important task for computer based learning systems.
Dynamic Key-Value Memory Networks for Knowledge Tracing
Knowledge Tracing (KT) is a task of tracing evolving knowledge state of students with respect to one or more concepts as they engage in a sequence of learning activities.
Deep Factorization Machines for Knowledge Tracing
jilljenn/ktm
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This paper introduces our solution to the 2018 Duolingo Shared Task on Second Language Acquisition Modeling (SLAM).
Deep Factorization Machines for Knowledge Tracing
jilljenn/ktm
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WS 2018
This paper introduces our solution to the 2018 Duolingo Shared Task on Second Language Acquisition Modeling (SLAM).
Incorporating Features Learned by an Enhanced Deep Knowledge Tracing Model for STEM/Non-STEM Job Prediction
The 2017 ASSISTments Data Mining competition aims to use data from a longitudinal study for predicting a brand-new outcome of students which had never been studied before by the educational data mining research community.
Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing
In Intelligent Tutoring System (ITS), tracing the student's knowledge state during learning has been studied for several decades in order to provide more supportive learning instructions.
