2024/03/12 by Yuexi Chen, Chen, Yuexi, Vlad I. Morariu +5 · 3 citations
Computer Science · Psychology · #Artificial Intelligence (cs.AI) #Educational Games and Gamification #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Intelligent Tutoring Systems and Adaptive Learning #Machine Learning (cs.LG) #Online Learning and Analytics
paper · pdf · doi:10.48550/arxiv.2403.08049
openalex publication_date 2024/03/12 · openalex created_date 2024/03/15 · openalex updated_date 2026/07/28
Mixed-media tutorials, which integrate videos, images, text, and diagrams to teach procedural skills, offer more browsable alternatives than timeline-based videos. However, manually creating such tutorials is tedious, and existing automated solutions are often restricted to a particular domain. While AI models hold promise, it is unclear how to effectively harness their powers, given the multi-modal data involved and the vast landscape of models. We present TutoAI, a cross-domain framework for AI-assisted mixed-media tutorial creation on physical tasks. First, we distill common tutorial components by surveying existing work; then, we present an approach to identify, assemble, and evaluate AI models for component extraction; finally, we propose guidelines for designing user interfaces (UI) that support tutorial creation based on AI-generated components. We show that TutoAI has achieved higher or similar quality compared to a baseline model in preliminary user studies.