TeachMateGPT: A Multi-Agent Knowledge-Grounded Framework for Pedagogical Assessment Generation from Science Curriculum Materials

TeachMateGPT, a multi-agent framework introduced in an arXiv paper (arXiv:2608.13708v1), improves curriculum-grounded science assessment generation by raising faithfulness from 0.68 to 0.96 and answer relevancy from 0.60 to 0.89 over a vanilla RAG baseline. The system introduces COPE, a hierarchical knowledge base; a staged fail-closed agent pipeline; SAVER, a source-attributed verification protocol; and NCTB-SciGen8, a dataset of 198 items spanning all 14 chapters of the NCTB Class 8 science textbook, rated by three practicing teachers.

arXiv:2608.13708v1 Announce Type: new Abstract: Automatically generating textbook-grounded assessment items can reduce science teachers' workload, but existing retrieval-augmented generation RAG systems rely on flat retrieval, support only single-question generation, lack safeguards against weak evidence, and are ill-suited to low-resource, board-exam-structured curricula. We address these limitations with TeachMateGPT, a multi-agent system contributing four advances to curriculum-grounded science-assessment authoring. i COPE, a hierarchical knowledge base replacing token-window chunking with a multi-resolution index that segments documents along syllabus structure and links them at three granularities via a traversable graph-based lineage, matching evidence to each topic's instructional level. ii A staged, fail-closed agent pipeline replacing one-shot retrieve-then-generate: routing gates search, retrieval fuses dense and lexical evidence under a coverage gate that withholds generation on insufficient evidence, and specialist agents draft objective and constructed-response items. iii SAVER, a source-attributed verification protocol scoring faithfulness, relevance, and hallucination risk against retrieved evidence, applying stricter grounding checks across each creative question's four sub-parts, paired with teacher-in-the-loop evaluation rather than automatic filtering. iv NCTB-SciGen8, a curriculum-grounded dataset of 198 items 143 multiple-choice, 55 creative questions spanning all 14 chapters of the NCTB Class 8 science textbook, produced by the pipeline and rated by three practicing teachers. TeachMateGPT raises faithfulness 0.68 $\rightarrow$ 0.96 and answer relevancy 0.60 $\rightarrow$ 0.89 over a vanilla RAG baseline.