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…
AI-Mediated Feedback Improves Student Revisions: A Randomized Trial with FeedbackWriter in a Large Undergraduate Course
Xinyi Lu, Kexin Phyllis Ju, Mitchell Dudley +2
Despite growing interest in using LLMs to generate feedback on students' writing, little is known about how students respond to AI-mediated versus human-provided feedback. We addre…
Easy Come, Easy Go? Examining the Perceptions and Learning Effects of LLM-based Chatbot in the Context of Search-as-Learning
Yeonsun Yang, Ahyeon Shin, Mincheol Kang +3
The cognitive process of Search-as-Learning (SAL) is most effective when searching promotes active encoding of information. The rise of LLMs-based chatbots, which provide instant a…
More AI Assistance Reduces Cognitive Engagement: Examining the AI Assistance Dilemma in AI-Supported Note-Taking
Xinyue Chen, Kunlin Ruan, Kexin Phyllis Ju +2
As AI tools become increasingly embedded in cognitively demanding tasks such as note-taking, questions remain about whether they enhance or undermine cognitive engagement. This pap…
Exploring LLM-Generated Feedback for Economics Essays: How Teaching Assistants Evaluate and Envision Its Use
Xinyi Lu, Aditya Mahesh, Zejia Shen +3
This project examines the prospect of using AI-generated feedback as suggestions to expedite and enhance human instructors' feedback provision. In particular, we focus on understan…
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…