Fabíola Ribeiro
Author directory2026
Exploratory Bayesian Multidimensional IRT with Rater Effects for Scoring Generative AI Usage
Leon Camus | Sebastian Gombert | Fabíola Ribeiro | Gianluca Romano | Carmen Köhler | Hendrik Drachsler
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
Leon Camus | Sebastian Gombert | Fabíola Ribeiro | Gianluca Romano | Carmen Köhler | Hendrik Drachsler
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
How students use generative AI is a configuration of distinct behaviors, not one skill, yet scoring typically collapses it onto a single proficiency axis, conflating process with product. We develop a multidimensional Bayesian IRT model with rater effects and post-hoc Varimax-permutation identification, surfacing three substantive dimensions: prompting effort, content delegation, AI-delivered citations. Domain familiarity shifts students toward more active engagement and away from delegation.