We present D-BIRD, a Bayesian dynamic item response model for estimating student ability from sparse, longitudinal assessments. By decomposing ability into a cohort trend and individual trajectory, D-BIRD supports interpretable modeling of learning over time. We evaluate parameter recovery in simulation and demonstrate the model using real-world personalized learning data.
@article{arxiv.2506.21723,
title = {Dynamic Bayesian Item Response Model with Decomposition (D-BIRD): Modeling Cohort and Individual Learning Over Time},
author = {Hansol Lee and Jason B. Cho and David S. Matteson and Benjamin W. Domingue},
journal= {arXiv preprint arXiv:2506.21723},
year = {2025}
}
Comments
Submitted to the NCME Special Conference: Artificial Intelligence in Measurement and Education Conference (AIME-Con)