当“说不”能生成更好的视频：为基于教学法的AI内容创作设计双重把关机制
When Saying No Makes Better Videos: Designing Dual Gatekeeping for Pedagogically Grounded AI Content Creation
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中文总结 AI 辅助
该研究针对AI内容创作设计双重把关机制，结合人工调整与自动化指标，证明审慎拒绝与生成式AI可协同提升教学类视频质量。
中文摘要 AI 辅助
为避免采用美学精致但教学法存在缺陷的AI内容，我们研究了一种包含两层结构化拒绝的视频创作流程。第一层让教育工作者能够基于多媒体学习理论迭代调整AI脚本，第二层则使用自动化指标标记教学连贯性及叙事-视觉同步性的违规情况。尽管两层均非完备，它们的协同作用确保了原则性拒绝——即推迟AI输出直至其达到严格标准——成为提升质量的催化剂。结合23名教育工作者参与的3个主题研究，以及来自成熟科学与哲学课程的7个主题的自动化指标评估，结果显示两层均能独立改善相同的教学维度，表明审慎的拒绝与生成式AI并非对立，而是合作伙伴。
英文摘要
To prevent the adoption of aesthetically polished but pedagogically flawed AI content, we study a video authoring pipeline featuring two layers of structured refusal. The first layer empowers educators to iteratively reshape AI scripts based on multimedia learning theory, while the second employs automated metrics to flag violations in instructional coherence and narrative-visual synchronization. While neither layer is exhaustive, their synergy ensures that principled resistance--the act of deferring AI output until it meets rigorous standards--becomes a catalyst for higher quality. Evaluation combining a study with 23 educators across 3 topics and automated metrics across 7 topics drawn from established science and philosophy curricula shows that both layers independently improve the same instructional dimensions, suggesting that thoughtful resistance and generative AI are not opposites but partners.
发表机构
- Seoul National University（首尔大学）
- Samsung Electronics（三星电子）
机构由 AI 辅助整理，请以论文原文为准。
