Hugging Face Trending Papers

How assigned AI use before class shapes active student engagement in class

arXiv Computation and Language
Aug 25

LLM Pedagogical Behavior in AI Tutoring Interactions

arXiv:2608.22993v1 Announce Type: new Abstract: Students increasingly use LLMs as tutors for coursework and problem solving. Little is known about the level of assistance LLMs provide when students u...

By Suhyeon Lee, Juneha Baek, Jaehyeong Park, Donghyuk Shin
arXiv AI
Aug 19

Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning

The paper presents a tutoring platform that combines a generative AI chatbot with a reinforcement learning algorithm to adaptively sequence practice problems for students learning Python. In a five‑month field study across ten high schools, the adaptive sequencing improved unassisted final exam performance by 0.15 standard deviations, with mediation analysis indicating that higher engagement drove the gains. The study demonstrates that signals from student‑chatbot interactions can be leveraged to personalize and optimize learning at scale.

By Angel Tsai-Hsuan Chung, Botong Zhang, Ling-Chieh Kung, Hamsa Bastani, Osbert Bastani
OpenAI Blog
Aug 26

Learning never stops: How AI makes learning continuous

OpenAI’s new report examines how students and educators are using ChatGPT to create a more continuous learning experience, extending support beyond traditional classroom settings. It highlights the role of AI in facilitating ongoing educational engagement and resource accessibility. The study showcases practical applications of AI tools in modern learning environments.

arXiv AI
Sep 28

Adapting for AI: How elementary teachers adjust their practices for an AI-integrated curriculum

The article examines how three elementary teachers implemented a conversational AI‑based curriculum using the ToyTalk platform during a three‑week summer camp. Over 13 instructional days, teachers employed adaptive practices—repair, differentiation, translation, and balancing—to navigate tensions among technology, learners, and instruction. Their understanding of AI and instructional roles evolved throughout the camp, leading to design implications for deploying conversational AI in elementary classrooms.

By Fasika Melese, Ruiyang Wu, Xinyue Cui, Joanna Perkins, Xiaoyi Tian, Tiffany Barnes, Shiyan Jiang
arXiv AI
Sep 18

Edustories: A Collection of Real-world Case Studies from Classroom Practices

Edustories is a dataset of 1,492 teacher‑written case studies that detail real elementary and high‑school classroom situations involving challenging student behavior, pedagogical interventions, and their outcomes. The collection is designed to enable research on AI assistance in collective teaching contexts, such as evaluating large language models’ ability to predict the success of teacher interventions. Comparative tests show that current models achieve 58% accuracy, below the 64% accuracy of human experts, indicating a gap between AI and human expertise in predicting classroom outcomes.

By Michal \v{S}tef\'anik, Jan Nehyba, Jirina Karasova, Martin Fico, Lucie \v{S}karkov\'a, Mark\'eta Ko\v{s}atkov\'a, David Kosatka
Hugging Face Trending Papers
Jul 15

Learning Engagement Assistant (LEA): Cross-Course Scalability and Classroom Evaluation of an Agentic AI Tutoring System

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. That prior work validated LEA on a single STEM course (CMP511) exclusively through simulation, using synthetic learner agents.

Hugging Face Trending Papers
Aug 12

Making AI-Generated Feedback Matter: From Provision to Student Enactment

Feedback processes strongly influence student learning, yet their educational value depends on addressing two distinct challenges: providing high-quality, timely, and individualised feedback at scale, and supporting students to interpret, evaluate, and act on that feedback productively. Generative AI offers a credible means of addressing the provision challenge, but students' uptake of AI-generated feedback remains limited.