You're currently viewing an old version of this dataset. To see the current version, click here.

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

The Deep-IRT model is a synthesis of the item response theory (IRT) model and a knowledge tracing model that is based on the deep neural network architecture called dynamic key-value memory network (DKVMN) to make deep learning based knowledge tracing explainable.

Data and Resources

This dataset has no data

Cite this as

Chun-Kit Yeung (2024). Dataset: Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory. https://doi.org/10.57702/d0lax8gr

Private DOI This DOI is not yet resolvable.
It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 17, 2024
Last update	December 17, 2024
Defined In	https://doi.org/10.48550/arXiv.1904.11738
Author	Chun-Kit Yeung