Cross-Dataset Bloom Question Classification: Supervised Models and Prompted LLMs

arXiv:2606.13684v1 Announce Type: cross Abstract: Automatic Bloom's taxonomy classification of assessment questions can substantially reduce instructor workload, but labeling is subjective and teacher-dependent. Prior machine learning (ML) and deep learning (DL) approaches reported strong within-dataset results, yet were rarely evaluated in cross-dataset settings, leaving real-world generalizability unclear; meanwhile, LLM effectiveness for Bloom question classification has not been systematically studied. We evaluated the cross-dataset generalization of existing ML/DL methods and assessed LLM

Source: arXiv cs.AI — read the full report at the original publisher.

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