6 papers
RelianceScope: An Analytical Framework for Examining Students' Reliance on Generative AI Chatbots in Problem Solving
Hyoungwook Jin, Minju Yoo, Jieun Han +3
Generative AI chatbots enable personalized problem-solving, but effective learning requires students to self-regulate both how they seek help and how they use AI-generated response…
What Do We Need for an Agentic Society?
Kwon Ko, Hyoungwook Jin
Thirty years ago, Wooldridge and Jennings defined intelligent agents through four properties: autonomy, reactivity, pro-activeness, and social ability. Today, advances in AI can em…
When Scaffolding Breaks: Investigating Student Interaction with LLM-Based Writing Support in Real-Time K-12 EFL Classrooms
Junho Myung, Hyunseung Lim, Hana Oh +6
Large language models (LLMs) are promising tools for scaffolding students' English writing skills, but their effectiveness in real-time K-12 classrooms remains underexplored. Addre…
Benchmarking Large Language Models for Diagnosing Students' Cognitive Skills from Handwritten Math Work
Yoonsu Kim, Hyoungwook Jin, Hayeon Doh +6
Students' handwritten math work provides a rich resource for diagnosing cognitive skills, as it captures intermediate reasoning beyond final answers. We investigate how current lar…
How Do Teachers Create Pedagogical Chatbots?: Current Practices and Challenges
Minju Yoo, Hyoungwook Jin, Juho Kim
AI chatbots have emerged as promising educational tools for personalized learning experiences, with advances in large language models (LLMs) enabling teachers to create and customi…
TeachTune: Reviewing Pedagogical Agents Against Diverse Student Profiles with Simulated Students
Hyoungwook Jin, Minju Yoo, Jeongeon Park +3
Large language models (LLMs) can empower teachers to build pedagogical conversational agents (PCAs) customized for their students. As students have different prior knowledge and mo…