A framework using self-rationalization, attribution analysis, and a certification metadata schema with traffic-light workflow enables transparent, audit-ready AI-generated educational assessments aligned to Bloom's and SOLO taxonomies.
Assessing AI-generated questions’ alignment with cognitive frameworks in educational assessment.International Journal of Computer Theory and Engineering, 17(3):114–125
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
The paper presents a curriculum-grounded LLM-as-Judge pipeline for question-level marking that assembles authorized syllabus artifacts to generate rubrics and evaluate student responses.
citing papers explorer
-
LLM-as-Judge in Education: A Curriculum-Grounded Marking Pipeline
The paper presents a curriculum-grounded LLM-as-Judge pipeline for question-level marking that assembles authorized syllabus artifacts to generate rubrics and evaluate student responses.