arXiv AI
Jul 10
DeepTutor: Towards Agentic Personalized Tutoring
arXiv:2604. 26962v3 Announce Type: replace-cross Abstract: Education is one of the most promising real-world applications for Large Language Models (LLMs).
SortingHat: Redefining Operating Systems Education with a Tailored Digital Teaching Assistant
arXiv:2606. 00015v1 Announce Type: cross Abstract: Operating Systems (OS) courses are among the most challenging in computer science education due to the complexity of internal structures and the diversity of running environments.
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arXiv AI
Jun 16
Lect\=uraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching
arXiv:2606. 16428v1 Announce Type: cross Abstract: Effective personalized AI-assisted learning demands systems that can not only generate accurate learner-specific educational materials, but also dynamically adapt their instruction to diverse learners.
arXiv AI
Jul 16
LessonBench-V1: A Benchmark Dataset for Evaluating AI Lesson Generation Agents
arXiv:2607. 13041v1 Announce Type: cross Abstract: Large Language Model (LLM) based AI educational content generation systems are increasingly being developed, yet no standardised benchmark exists to systematically evaluate them.
arXiv AI
Jun 2
Beyond End-to-End Video Models: An LLM-Based Multi-Agent System for Educational Video Generation
arXiv:2602. 11790v2 Announce Type: replace Abstract: Although recent end-to-end video generation models demonstrate impressive performance in visually oriented content creation, they remain limited in scenarios that require strict logical rigor and precise knowledge representation, such as instructional and educational media.
arXiv AI
Jun 9
Syll: Open-Source Personal Automation with Cross-Surface Execution
arXiv:2606. 07594v1 Announce Type: new Abstract: Personal AI agents must increasingly operate across APIs, shells, web surfaces, and desktop GUIs, yet many systems remain tuned to a single interface and offer limited support for user teaching and auditability.
arXiv Machine Learning
Jun 8
Elmes*: Automated Construction of Fine-Grained Evaluation Rubrics for Large Language Models in Long-Tail Educational Scenarios
arXiv:2606. 06546v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for education requires measuring how models teach, not only what they know.
arXiv AI
Jul 10
Open-ended Multi-agent Autocurricula via Visual Inspection of Policies with Multi-modal LLMs
arXiv:2607. 08193v1 Announce Type: cross Abstract: Open-ended curricula in Reinforcement Learning (RL) aim to train generally-capable agents by identifying tasks that facilitate learning increasingly complex skills.
arXiv AI
6d ago
Agentic AI-driven Immersive Simulation: A Knowledge-Aware Virtual Training Platform for High Dose Rate (HDR) Brachytherapy
The paper introduces an agentic AI-driven immersive simulation for High Dose Rate vaginal cylinder brachytherapy, combining Virtual Reality, mobile computing, and a knowledge-aware assistant powered by Retrieval-Augmented Generation. The system offers a high‑fidelity, risk‑free training environment that provides natural language interfaces and real‑time guidance during complex medical maneuvers. A prototype using Meta Quest 3 and a GPU‑accelerated backend demonstrates acceptable latency and high context precision, answer completeness, and relevance in the pedagogical support.
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.
arXiv AI
Jun 16
Edu-Theater: A Data-Efficient Agent Framework for Scalable Learner Behavior Simulation through Staging Roll-Call
arXiv:2606. 15225v1 Announce Type: cross Abstract: Large-scale learner-task interaction data are crucial for intelligent educational systems but are costly to collect and constrained by privacy and learner engagement.
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.
arXiv AI
Jun 9
AI-Integrated Learning Management System for Middle School: A Longitudinal Study of Learning Outcomes Through High School and Beyond
arXiv:2606. 07544v1 Announce Type: cross Abstract: Middle school is a key window for building core academic skills and the learning routines students carry into later grades, yet many students still fall behind because help is often limited and comes too late, after they have already been stuck for a while.