Knowledge-based short videos have become a significant medium for informal learning on platforms like TikTok and YouTube Shorts. However, their educational value hinges on their production methods, the mechanisms for maintaining quality, and the evaluation of learning outcomes. This article provides a comprehensive theoretical analysis of these three dimensions within digital learning ecosystems. Drawing on research into educational videos, studies on microlearning, and the field of platform governance, it addresses three key questions: How creators apply instructional design principles to the extremely short format? How quality can be assured in decentralized production environments lacking institutional oversight? How learning effectiveness should be measured when consumption is fragmented and influenced by algorithms? The analysis concludes that short videos can support learning if they are grounded in evidence-based instructional design. However, it also finds that engagement metrics often prioritize attention over understanding, and that increased engagement does not necessarily lead to deeper learning. The paper proposes a multi-level framework for quality assurance, involving platform-level interventions to ensure accuracy, creator adoption of transparent practices, and community validation. A corresponding evaluation framework distinguishes between engagement metrics, cognitive measures, and outcome-based assessments. This work provides a theoretically grounded explanation of how knowledge disseminates and can be quality-controlled within short-video ecosystems and offers design and assessment guidelines for creators, platforms, and educators.
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Share and Cite
Zheng, C. (2026) Knowledge-based Short Videos in Digital Learning Ecosystems: Content Production, Quality Assurance, and Learning Effectiveness. Scientific Research Bulletin, 3(3), 70-76. https://doi.org/10.71052/srb2024/UOLW8432