arXiv cs.CY· Vikrant Sahu, Khethavath Sunil Naik, Gagan Raj Gupta·· 2 天前AI 评分24
MARS：面向个性化评估的动量感知自适应评分系统
MARS: A Momentum-Aware Adaptive Rating System for Personalized Assessment
AI 导读
研究者提出 MARS，一种动量感知自适应评分系统，将题库表示为有向加权知识图谱，结合动态评分敏感度、作答质量与动量感知的学习者速度更新能力值。在 ASSISTments 2009 和 MARS-SimExam 上，MARS 的评分更新比 Fixed Elo 更平滑，并在限时负分路由下取得最高分，总分较最强基线提升 8.09，超时违规率从 50% 降至 5.6%。
正文 · 原文
Abstract:Adaptive assessment systems personalize learning by estimating learner proficiency and recommending suitable questions. However, many existing approaches rely on fixed difficulty labels, static rating updates, or black-box prediction models that provide limited control over rating stability, interpretability, and time-constrained routing. This paper proposes MARS, a Momentum-Aware Adaptive Rating System for interpretable adaptive assessment. MARS represents the question bank as a directed weighted knowledge graph and updates learner proficiency using dynamic rating sensitivity, response quality, and momentum-aware learner velocity. We also formulate a time-budgeted mark-maximization objective in which the policy selects questions within a fixed test duration under negative marking. Experiments on ASSISTments 2009 and MARS-SimExam evaluate MARS for prediction, rating stability, and adaptive routing. Results show that MARS provides smoother rating updates than Fixed Elo and achieves the highest score under time-budgeted negative-marking routing, improving the total score by 8.09 over the strongest baseline and reducing overtime violations from 50% to 5.6%. These results suggest that MARS is suitable for real-time, interpretable, and deployment-friendly adaptive assessment.
| Subjects: | Computers and Society (cs.CY); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.21685 [cs.CY] |
| (or arXiv:2610.21685v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2610.21685 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Vikrant Sahu [view email]
[v1]
Thu, 15 Oct 2026 11:09:49 UTC (562 KB)
来源：arXiv cs.CY · arxiv.org