AgentCAT: Simulating Computerized Adaptive Testing via Multi-Agent Large Language Models

arXiv:2606.21832v1 Announce Type: new Abstract: Computerized Adaptive Testing (CAT), as a key technology for personalized education, aims to accurately assess examinee proficiency by retrieving exercises dynamically matching current ability estimates. However, existing CAT research is constrained by limitations of static offline data and isolated component optimization. Restricted by partial labels in offline logs, researchers degrade the dynamic assessment process into static sequence predictio