Chrysalis: A Unified System for Comparing Active Teaching and Passive Learning with AI Agents in Education

October 06, 2025 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Prashanth Arun, Vinita Vader, Erya Xu, Brent McCready-Branch, Sarah Seabrook, Kyle Scholz, Ana Crisan, Igor Grossmann, Pascal Poupart arXiv ID 2510.05271 Category cs.HC: Human-Computer Interaction Citations 0 Venue arXiv.org Last Checked 4 months ago
Abstract
AI-assisted learning has seen a remarkable uptick over the last few years, mainly due to the rise in popularity of Large Language Models (LLMs). Their ability to hold long-form, natural language interactions with users makes them excellent resources for exploring school- and university-level topics in a dynamic, active manner. We compare students' experiences when interacting with an LLM companion in two capacities: tutored learning and learning-by-teaching. We do this using Chrysalis, an LLM-based system that we have designed to support both AI tutors and AI teachable agents for any topic. Through a within-subject exploratory study with 36 participants, we present insights into student preferences between the two strategies and how constructs such as intellectual humility vary between these two interaction modes. To our knowledge, we are the first to conduct a direct comparison study on the effects of using an LLM as a tutor versus as a teachable agent on multiple topics. We hope that our work opens up new avenues for future research in this area.
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