生成式AI支持下中国矿业科技英语短视频创作策略研究——基于262份问卷数据的实证分析

Generative AI-Supported Strategies for Creating Short Videos on China’s Mining Science and Technology English—An Empirical Analysis Based on 262 Questionnaire Responses

摘要: 生成式人工智能技术的快速发展，为矿业科技英语短视频创作提供了新的技术路径与传播可能。本研究基于262份有效问卷数据，系统分析了当前大学生在生成式AI支持下创作矿业科技英语短视频的行为特征、技术应用现状与核心诉求。研究发现：生成式AI已深度融入短视频创作的各个阶段，尤其在资料搜集、文稿准备、翻译优化等环节发挥显著作用，用户满意度普遍较高；但专业准确性、内容同质化、数据安全与版权归属等问题仍是制约深度应用的关键障碍。基于数据分析结果，本文提出“内容为本、专业为核、技术为用、安全为基”的创作策略框架，并从主题策划、内容生产、技术应用、传播优化四个维度构建具体实施路径，为矿业院校开展AI赋能的科技英语教学与传播实践提供参考。

Abstract: The rapid advancement of generative artificial intelligence technologies has opened up new technical pathways and communication possibilities for the creation of English-language short videos on mining science and technology. Based on data from 262 valid questionnaires, this study systematically examines the behavioral characteristics, current status of technology application, and core needs of university students in producing such videos with the support of generative AI. The findings reveal that generative AI has been deeply integrated into various stages of short video production, playing a particularly significant role in materials collection, script preparation, and translation optimization, with generally high user satisfaction. However, issues such as professional accuracy, content homogenization, data security, and copyright ownership remain key obstacles that constrain deeper application. On the basis of the data analysis, this paper proposes a creative strategy framework centered on the principles of “content as the foundation, professionalism as the core, technology as the tool, and security as the bedrock”. It further constructs a concrete implementation pathway across four dimensions—theme planning, content production, technology application, and communication optimization—thereby providing a reference for AI-enhanced English for science and technology teaching and communication practices in mining engineering institutions.