YT-Pilot: Turning YouTube into Structured Learning Pathways with Context-Aware AI Support

2026-04-03

AI Summary

This study addresses the fragmentation of learning content on YouTube, which lacks persistent interaction structures to support goal setting, planning, and cross-video integration. Drawing on self-regulated learning theory, this work proposes a novel persistent interface architecture centered on “learning paths” that unifies planning and execution, enabling goal specification, navigation, progress tracking, and cross-video knowledge linking. The system integrates context-aware AI with path-aware interaction design to ensure cognitive and operational coherence across multiple video resources. A user study (N=20) demonstrates that this approach significantly enhances users’ goal clarity, path coherence, and progress awareness, while fostering path-level inferential behaviors that span multiple learning resources.

Abstract

YouTube is widely used for informal learning, where learners explore lectures and tutorials without a predefined curriculum. However, learning across videos remains fragmented: learners must decide what to watch, how videos relate, and how knowledge builds. Existing tools provide partial support but treat planning and learning as separate activities, lacking a persistent interaction structure that connects them. Grounded in self-regulated learning theory (SRLT), we introduce YT-Pilot, a pathway-aware learning system that operationalizes the learning pathway as a persistent, user-facing interaction structure spanning planning and learning. The pathway coordinates goal setting, planning, navigation, progress tracking, and cross-video assistance. Through a within-subjects study ($N=20$), we show that YT-Pilot significantly improves perceived goal clarity, pathway coherence, and progress tracking, while shifting interaction toward pathway-level reasoning across multiple resources.

Problem

• informal learning
• learning pathways
• video-based learning
• self-regulated learning
• learning fragmentation

Innovation

• structured learning pathways
• context-aware AI
• self-regulated learning
• cross-video assistance
• persistent interaction structure