@inproceedings{lee-etal-2025-dynamic-bayesian,
    title = "Dynamic {B}ayesian Item Response Model with Decomposition ({D}-{BIRD}): Modeling Cohort and Individual Learning Over Time",
    author = "Lee, Hansol  and
      Cho, Jason B.  and
      Matteson, David S.  and
      Domingue, Benjamin",
    editor = "Wilson, Joshua  and
      Ormerod, Christopher  and
      Beiting Parrish, Magdalen",
    booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers",
    month = oct,
    year = "2025",
    address = "Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States",
    publisher = "National Council on Measurement in Education (NCME)",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.aimecon-main.43/",
    pages = "398--405",
    ISBN = "979-8-218-84228-4",
    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."
}