arXiv:2606.17507v1 Announce Type: new Abstract: Generative AI and large language models (LLMs) are increasingly applied to question generation and automated assessment. However, deploying LLMs in preparation for high-stakes exams requires more than prompt engineering; it demands software pipelines that systematically ground model outputs in authorised curriculum artefacts and marking guidelines issued by education authorities. This paper presents a curriculum-grounded, configurable LLM-as-Judge pipeline for question-level marking, co-developed with an industrial partner, to support exam prepar
The rapid advancement and accessibility of large language models (LLMs) are pushing their deployment into high-stakes environments, necessitating robust and reliable application pipelines, especially in education where accuracy and grounding are paramount.
This development indicates a maturing phase for LLM application, moving beyond novelty to integrated, curriculum-dependent systems which could fundamentally alter assessment and curriculum design.
Traditional human-centric marking and question generation processes will face increasing pressure to integrate automated, curriculum-grounded LLM systems for efficiency and consistency, provided these systems achieve high reliability.
- · EdTech companies developing AI-driven assessment tools
- · Educational institutions adopting AI for efficiency
- · Students receiving more consistent and rapid feedback
- · AI developers specializing in reliable, grounded LLM applications
- · Traditional human markers (potentially)
- · Educational institutions slow to adapt to AI
- · Generic LLM companies without domain-specific grounding solutions
Educational systems begin pilot programs and gradual integration of 'LLM-as-Judge' for formative and potentially summative assessments.
Curriculum developers and educators adapt content and teaching methods to optimize for AI-driven assessment criteria and feedback loops.
The role of human educators shifts significantly towards higher-order tutoring, curriculum design, and oversight of AI systems, rather than primary assessment.
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Read at arXiv cs.AI