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[2602.19623] PedaCo-Gen: Scaffolding Pedagogical Agency in Human-AI Collaborative Video Authoring
Summary
PedaCo-Gen is a novel AI system designed to enhance the quality of instructional video creation by integrating pedagogical principles and collaborative human-AI interaction.
Why It Matters
This research addresses the gap in current generative AI models that prioritize visual quality over educational effectiveness. By introducing a structured approach to video authoring, it empowers educators to maintain pedagogical agency while leveraging AI capabilities, potentially transforming instructional design practices.
Key Takeaways
- PedaCo-Gen enhances video quality through a collaborative AI-human approach.
- The system incorporates Mayer's Cognitive Theory for effective instructional design.
- Participants reported increased production efficiency and perceived AI as a valuable instructional partner.
- The Intermediate Representation phase allows for iterative refinement of video content.
- This research promotes reclaiming pedagogical agency in AI-assisted content creation.
Computer Science > Computer Vision and Pattern Recognition arXiv:2602.19623 (cs) [Submitted on 23 Feb 2026] Title:PedaCo-Gen: Scaffolding Pedagogical Agency in Human-AI Collaborative Video Authoring Authors:Injun Baek, Yearim Kim, Nojun Kwak View a PDF of the paper titled PedaCo-Gen: Scaffolding Pedagogical Agency in Human-AI Collaborative Video Authoring, by Injun Baek and 2 other authors View PDF HTML (experimental) Abstract:While advancements in Text-to-Video (T2V) generative AI offer a promising path toward democratizing content creation, current models are often optimized for visual fidelity rather than instructional efficacy. This study introduces PedaCo-Gen, a pedagogically-informed human-AI collaborative video generating system for authoring instructional videos based on Mayer's Cognitive Theory of Multimedia Learning (CTML). Moving away from traditional "one-shot" generation, PedaCo-Gen introduces an Intermediate Representation (IR) phase, enabling educators to interactively review and refine video blueprints-comprising scripts and visual descriptions-with an AI reviewer. Our study with 23 education experts demonstrates that PedaCo-Gen significantly enhances video quality across various topics and CTML principles compared to baselines. Participants perceived the AI-driven guidance not merely as a set of instructions but as a metacognitive scaffold that augmented their instructional design expertise, reporting high production efficiency (M=4.26) and guide validity ...
