4 papers
Revisiting the Regularity of Student Learning Rate: Sensitivity to Which Observations Are Included
Hansol Lee, Guilherme Lichand, Cristina Barnard +4
Mixed-effects models fit to observational practice data are widely used in learning analytics to estimate student-level variation in initial knowledge and learning rate, and the re…
Dynamic Bayesian Item Response Model with Decomposition (D-BIRD): Modeling Cohort and Individual Learning Over Time
Hansol Lee, Jason B. Cho, David S. Matteson +1
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 indiv…
Estimating Heterogeneous Treatment Effects with Item-Level Outcome Data: Insights from Item Response Theory
Joshua B. Gilbert, Zachary Himmelsbach, James Soland +2
Analyses of heterogeneous treatment effects (HTE) are common in applied causal inference research. However, when outcomes are latent variables assessed via psychometric instruments…
Polytomous Explanatory Item Response Models for Item Discrimination: Assessing Negative-Framing Effects in Social-Emotional Learning Surveys
Joshua B. Gilbert, Lijin Zhang, Esther Ulitzsch +1
Modeling item parameters as a function of item characteristics has a long history but has generally focused on models for item location. Explanatory item response models for item d…