arXiv:2606. 18617v1 Announce Type: cross Abstract: There exist numerous tutor training platforms.
By Danielle R. Thomas, Marie Cynthia Abijuru Kamikazi, Clara Brandt, Conrad Borchers, Kenneth R. Koedinger
arXiv:2608. 03952v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to provide conversational practice for English-as-a-second-language (ESL) learners.
By Dongjie Yang, Siyan Lin, Leixian Shen, Rui Sheng, Huamin Qu, Zixin Chen
arXiv:2606. 12422v1 Announce Type: cross Abstract: The integration of large language models (LLMs) into educational assessment represents a transformative shift in classroom grading practices.
By Zewei Tian, Alex Liu, Lief Esbenshade, Michael Xiao, Zachary Zhang, Yulia L\'apicus, Thomas Han, Kevin He, Min Sun
arXiv:2607. 26317v1 Announce Type: cross Abstract: Psychometric calibration for educational tests typically requires costly human response data.
By Wenjie Zhou, Yunting Liu, Renjiao Tang, Mark Wilson
arXiv:2607. 13370v1 Announce Type: cross Abstract: This paper is an extension of a paper presented at the ICAART 2026 conference, which introduced LEA (Learning Engagement Assistant), an adaptive AI tutoring agent combining course-specific Retrieval-Augmented Generation (RAG) with structured Knowledge Component (KC) models across integrated Chat, Tutor, and Quiz modes.
By Teri Rumble, Javad Zarrin, P. George Lovell, Ruth Falconer
arXiv:2606. 06546v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for education requires measuring how models teach, not only what they know.
By Tao Liu, Ye Lu, Ruohua Zhang, Siyu Song, Wentao Liu, Aimin Zhou, Hao Hao