Agentic Tutoring
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Voting Protocols as Coordination Mechanisms for Role-Constrained Multi-Agent Tutoring Systems
arXiv:2606.08030v1 Announce Type: new Abstract: Agentic tutoring systems introduce a coordination challenge: multiple agents may propose different but reasonable interventions, yet only one response can be delivered to the learner. In this paper, we study how voting protocols shape cooperation among four role-constrained pedagogical agents responsible for scaffolding, misconception, motivation, and metacognition. We compare four voting protocols -- simple, ranked, cumulative, and approval...
Identifying High-Confidence Social Biases in LLMs for Trustworthy Conversational Tutoring Agents
arXiv:2606.01584v1 Announce Type: new Abstract: Conversational tutoring agents have been shown to improve learning engagement and student outcomes, and large language models (LLMs) are increasingly used in these systems to provide scalable, personalized feedback. However, LLMs may perpetuate or amplify stereotypical social biases, posing particular risks in educational settings. In this study, we evaluate LLMs in conversational tutoring scenarios to identify high-confidence social biases,...
SocialCoach: Personalized Social Skill Learning with RL-based Agentic Tutoring and Practice
arXiv:2606.04155v1 Announce Type: new Abstract: Social skills such as negotiation and leadership are crucial for personal and professional success in today's interconnected world. However, scalable and effective training remains a significant challenge due to the scarcity of expert coaching. In this paper, we introduce SocialCoach, a holistic LLM-powered agentic tutoring system for personalized social skill development at scale.
PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers on Overleaf
arXiv:2606.08857v1 Announce Type: new Abstract: Expert writing feedback from experienced researchers is critical for early-career scholars to improve their manuscripts, yet high-quality feedback often remains scarce because reviewing research papers is labor-intensive. Emerging AI-powered writing assistants largely focus on grammar fixes or simulating peer review with final scores, yet they fall short of providing concrete, actionable suggestions that help students improve their papers...
Powering An Ecosystem Of Pedagogical AI Agents: A Validation Strategy For A Unified Data Architecture
Announce Type: new Abstract: The application of AI in education has evolved from monolithic intelligent tutoring systems to a diverse ecosystem of pedagogical agents, including conversational assistants, virtual coaches, and adaptive tutors. This shift requires a unified and scalable data architecture to manage the complex information feedback loops between human instructors, learners, and the varied AI agents. The design, development, and deployment of the data architecture in turn raises a...
Warning About AI Fallibility Increases Help-Seeking in an Intelligent Tutoring System
arXiv:2606.03822v1 Announce Type: new Abstract: Recent work in Technology-Enhanced Learning and Human-Computer Interaction highlights the importance of transparency and trust calibration in AI-supported learning environments as they pose a risk of hallucinations. In this study, we investigate whether a simple transparency intervention that warns students that a pedagogical agent may make mistakes affects learner behavior in a math intelligent tutoring system. We conducted a classroom...
Regulating the AI Tutor: Intentions, Help-Seeking, and Self-Regulated Learning in Adolescent GenAI Use
Announce Type: new Abstract: Generative AI (GenAI) tools are now common learning companions for adolescents, yet how they regulate their use during authentic learning tasks remains poorly understood. Self-regulated learning (SRL) and high-level help-seeking (HS) are commonly proposed as safeguards against passive or shortcut-oriented use, but most empirical studies focus on aggregate learning outcomes rather than these moment-to-moment processes during AI-supported learning. This...
Superintelligence: The Idea That Eats Smart People (2016)
This is the text version of a talk I gave on October 29, 2016, at Web Camp Zagreb [video] (45 mins) SuperintelligenceThe Idea That Eats Smart People | | | In 1945, as American physicists were preparing to test the atomic bomb, it occurred to someone to ask if such a test could set the atmosphere on fire. This was a legitimate concern.