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preprint

10 papers

Illustrative photograph of a teacher-education group discussing a short fictional tutoring exchange, with two alternative response cards on a seminar table.
Tool / Dataset2026
Tool / Dataset 249

Preprint: TutorCaseBench separates recognizing a strategy from responding to a learner

Yeon Su Park, Chanyoung Park, Tae Soo Kim, Seungju Kim, Hyunwoo Kim, Daho Jung, Jinsung Yoon, Juho Kim

arXiv preprint

A benchmark builds simulated tutoring cases from qualitative education studies. Models were more successful at choosing a proposed strategy than at generating a response adapted to the particular situation.

preprintAI tutor evaluationcase-based assessment
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A Black lecturer and a South Asian university student compare annotated programming answers, a branching diagram and overlapping rubric bars in a bright assessment clinic
Tool / Dataset2026
Tool / Dataset 228

Preprint: Detailed AI grading rubrics did not necessarily diagnose different learning problems

Xi Zhao, Xinyue Jiao, Zhen Xu

arXiv preprint

A preprint examining 3,041 computer-science answers found that detailed AI score dimensions overlapped strongly, while feedback identified fewer misconceptions than instructor comments. Its analysis raises a practical question: can an assessment explain a learner’s error, rather than simply produce plausible scores?

preprintautomated assessmentcomputer science education
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An East Asian female university student and a South Asian male language tutor compare bilingual economics notes and two AI explanations in a sunlit campus language centre
Tool / Dataset2026
Tool / Dataset 226

Preprint: Students’ access to generative AI did not ensure equally usable support across languages

Ming Li, Qin Xie, Ariunaa Enkhtur, Lilan Chen, Fei Cheng

arXiv preprint (work in progress)

Interviews with 42 undergraduates at universities in China, Japan, and Mongolia explored how students selected AI tools, chose interaction languages, and checked outputs. Participants described different routes from technical access to useful academic support, including switching languages when responses seemed inadequate. This work-in-progress preprint presents situated accounts rather than national comparisons or measured learning gains. It raises practical questions about evaluating an AI service in the languages students actually use.

preprintmultilingual educationAI access
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A Black female university student listens through headphones and uses a physical playback control while a White male accessibility specialist reviews a graph and lecture monitor nearby
Tool / Dataset2026
Tool / Dataset 224

Preprint: Lecture audio-description rules and listener preferences did not always agree

Stylianos Psychias, Yingqiang Gao

arXiv preprint

AD4Edu proposes a benchmark and evaluation framework for describing visual information in university lectures. Four blind or low-vision raters assessed 400 description pairs, revealing a gap between compliance with the researchers’ rules and individual preferences, especially about length. This preprint offers tools for studying that gap, with small-sample and playback limitations. It does not demonstrate improved course learning or certify that a lecture meets accessibility requirements.

preprintaccessibilityaudio description
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Illustrative scene of a learner and tutor comparing a handwritten triangle solution with a laptop showing a triangle and branching hint paths at an evening study desk.
Tool / Dataset2026
Tool / Dataset 235

Preprint: Adaptive tutor prompts changed interaction patterns without establishing better learning

Po-Chin Chang, Nicholas Hogan, Aske Plaat, Michiel T. van der Meer

arXiv preprint, version 1

A high-school tutoring preprint examines adaptive prompt selection. Its interaction results invite closer study, but limited exercise data and nonsignificant outcome comparisons leave the learning advantage unresolved.

preprintadaptive tutoringprompt selection
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