AI in Education
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Papers tagged with: #llms-as-raters

7.4
psychometric_modeling

Interpretable, Fairly Evaluated Automated L2 Speaking Assessment that Beats the Single-Human Ceiling and Why Pause Encoding Does Not Change LLM Fluency Scores

Eichi Uehara · arXiv (2026) · doi:10.48550/arxiv.2608.26137 · gemini-3.8-flash

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7.4
psychometric_modeling

Machine--human agreement in marking undergraduate assignments is specific to model, prompt and institution

Giulio Corsi, Maryam Abo-Tabik, Yael Benn, Georgiana Thorpe Apreutesei, Roni Tibon, Alexandru Marcoci, Deborah Talmi · arXiv (2026) · doi:10.48550/arxiv.2610.18019 · gemini-3.8-flash

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7.4
assessment_design

MisconceptDialogue: Evaluation Criteria Shape Measured Success in LLM Math Tutoring

Woojin Lee, Yoonkyu Woo, Jinah Kim, Hyeok-Min Gwon, Jin‐Xia Huang · arXiv (Cornell University) (2026) · doi:10.48550/arxiv.2610.31679 · gemini-3.6-flash

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7.2
psychometric_modeling

Operating characteristics of agreement metrics in AI-based scoring: a Monte Carlo simulation

Alperen Yandi · Frontiers in Psychology (2026) · doi:10.3389/fpsyg.2026.1705653 · gemini-3.8-flash

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7.9
quasi_experiment

Judged in Company: In-Context Batching Makes LLM Verdicts Depend on Other Items

Peng Xie, Amr Alanwar · arXiv (2026) · doi:10.48550/arxiv.2610.40241 · gemini-3.8-flash

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7.2
assessment_design

Automated Refinement of Essay Scoring Rubrics for Language Models via Reflect-and-Revise

Keno Harada, Lui Yoshida, Takeshi Kojima, Yusuke Iwasawa, Yutaka Matsuo · Conference on Computational Natural Language Learning (2026) · doi:10.18653/v1/2026.conll-main.47 · gemini-3.6-flash

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