摘要
教育数字化转型背景下,异步视频学习具有跨越传统学习时空限制的独特优势,但也存在学习持续性差、学习者情绪表达障碍、学习效率低下等问题,其中视频画面情感质量对学习者的情绪体验和学习效果具有重要影响。基于此,提出从学习者视角开展异步视频学习情绪预警,并以预警结果为依据反向优化教学视频画面的情感,进而达到视频画面情感进化以及异步视频学习体验与效果优化的双重目标。首先,参考多系统情绪激活理论和多媒体画面语言学理论构建了异步视频学习情绪激活机制的理论模型;其次,以理论模型为依据厘清异步视频学习情绪预警的技术方案,并通过情绪预警实验实现了异步视频学习情绪特征的采集、融合与预警模型构建;最后,从视频学习资源库、异步视频学习情绪预警模块、教学视频画面情感优化设计规则库和资源设计者四方面构建了视频画面情感智能进化系统模型。研究结果为教学视频画面情感进化提出了完整的实践方案,既可改善视频资源质量与异步视频学习成效,又可提升以教师为主的资源设计者的信息技术素养与能力,实现以多模态技术与人工智能技术驱动我国教育数字化转型的高质量发展。
In the context of educational digital transformation, asynchronous video learning has the unique advantage of transcending the spatial and temporal limitations of traditional learning. But there are also problems such as poor learning persistence, learners’ emotional expression disorder, and low learning efficiency. Among them, the emotional quality of instructional video has an important impact on learners’ emotional experiences and learning effects. Based on this, this paper proposes to carry out asynchronous video learning emotion warning from the perspective of learners, and reversely optimize the emotion of instructional video based on the warning results, to achieve the dual goals of video emotion evolution and asynchronous video learning experience and effect optimization. Firstly, a theoretical model of the emotion activation mechanism of asynchronous video learning was constructed by referring to the Multi-system Emotion Activation Theory and Linguistics for Multimedia Design. Secondly, based on the theoretical model, the technical scheme of asynchronous video learning emotion warning is clarified, and the collection, fusion, and early warning model of asynchronous video learning emotion characteristics are realized through the emotion warning experiment. Finally, a video emotional intelligence evolution system model is constructed from four aspects: video learning resource database, asynchronous video learning emotion warning module, instructional video emotional optimization design rule database, and resource designer. The results provide a complete practical scheme for the emotional evolution of instructional video images, which can improve the quality of video resources and the effectiveness of asynchronous video learning, enhance the digital literacy and ability of resource designers, mainly teachers, and realize the high-quality development driven by multi-modal technology and artificial intelligence technology.
作者
王雪
王崟羽
乔玉飞
牛玉洁
贾薪卉
WANG Xue;WANG Yinyu;QIAO Yufei;NIU Yujie;JIA Xinhui(Tianjin Normal University,Tianjin 300387)
出处
《现代远距离教育》
CSSCI
2022年第6期11-22,共12页
Modern Distance Education
基金
2021年国家自然科学基金青年项目“教学视频中情绪设计对学习的影响机制及其优化方法研究”(编号:62107030)。
关键词
异步视频学习
情绪预警
视频画面情感进化
多模态数据
智能算法
Asynchronous Video Learning
Emotion Warning
Emotion Evolution of Instructional Video
Multimodal Data
Intelligent Algorithm
