Dynamic Bayesian Item Response Model with Decomposition (D-BIRD): Modeling Cohort and Individual Learning Over Time

Abstract

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.

Submitted to the NCME Special Conference: Artificial Intelligence in Measurement and Education Conference (AIME-Con)