Knowledge Tracing

67 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

Datasets


Latest papers with no code

KTbench: A Novel Data Leakage-Free Framework for Knowledge Tracing

no code yet • 22 Mar 2024

To address these problems, we introduce a general masking framework that mitigates the first problem and enhances the performance of such KT models while preserving the original model architecture without significant alterations.

Predictive, scalable and interpretable knowledge tracing on structured domains

no code yet • 19 Mar 2024

This requires estimates of both the learner's progress (''knowledge tracing''; KT), and the prerequisite structure of the learning domain (''knowledge mapping'').

A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models

no code yet • 12 Mar 2024

However, the inherent black-box nature of deep learning techniques often poses a hurdle for teachers to fully embrace the model's prediction results.

A Survey of Explainable Knowledge Tracing

no code yet • 12 Mar 2024

This paper thoroughly analyzes the interpretability of KT algorithms.

Improving Low-Resource Knowledge Tracing Tasks by Supervised Pre-training and Importance Mechanism Fine-tuning

no code yet • 11 Mar 2024

Knowledge tracing (KT) aims to estimate student's knowledge mastery based on their historical interactions.

Predicting Learning Performance with Large Language Models: A Study in Adult Literacy

no code yet • 4 Mar 2024

This research is motivated by the potential of LLMs to predict learning performance based on its inherent reasoning and computational capabilities.

A Review of Data Mining in Personalized Education: Current Trends and Future Prospects

no code yet • 27 Feb 2024

Personalized education, tailored to individual student needs, leverages educational technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness.

KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students

no code yet • 19 Feb 2024

Flashcard schedulers are tools that rely on 1) student models to predict the flashcards a student knows; and 2) teaching policies to schedule cards based on these predictions.

Analysis of Knowledge Tracing performance on synthesised student data

no code yet • 30 Jan 2024

Knowledge Tracing (KT) aims to predict the future performance of students by tracking the development of their knowledge states.

Parametric Constraints for Bayesian Knowledge Tracing from First Principles

no code yet • 23 Dec 2023

Bayesian Knowledge Tracing (BKT) is a probabilistic model of a learner's state of mastery corresponding to a knowledge component.