协同远程学习中语义压缩教学视频的自适应同步

IF 3.3 Q1 EDUCATION & EDUCATIONAL RESEARCH International Journal of Distance Education Technologies Pub Date : 2007-04-01 DOI:10.4018/jdet.2007040105
Dan B. Phung, G. Valetto, G. Kaiser, Tiecheng Liu, J. Kender
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引用次数: 8

摘要

网络课程的日益普及凸显了对学生群体协作学习工具的需求。此外,在线课程中讲座视频的引入引起了人们对学生可用网络资源差异的关注。我们提出了一种称为aiv(自适应交互式互联网团队视频)的电子学习架构和适应模型,它允许学生群体协作同步观看视频。aiv坚持不变,即每个学生在任何时候都将看到语义上相同的内容。为了适应动态的网络条件和用户的系统需求,提出了一种语义压缩模型来提供不同细节层次的教学视频。我们利用语义压缩算法的能力,通过调整客户端在适当的层上播放,为客户端提供尽可能丰富的观看体验,从而提供语义等效视频的不同层。视频播放器的动作,如播放、暂停和停止,可以由任何小组成员发起,并且这些动作的结果与所有其他学生同步。这些功能允许学生在串联中回顾讲座视频,促进学习过程。实验表明,即使在带宽波动的情况下,aiv也可以通过自适应调整每个学生的质量水平而保持不变性,从而成功地同步分布式学生的教学视频,同时优化视频质量。
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Adaptive Synchronization of Semantically Compressed Instructional Videos for Collaborative Distance Learning
The increasing popularity of online courses has highlighted the need for collaborative learning tools for student groups. In addition, the introduction of lecture videos into the online curriculum has drawn attention to the disparity in the network resources available to students. We present an e-Learning architecture and adaptation model called AITV (Adaptive Interactive Internet Team Video), which allows groups of students to collaboratively view a video in synchrony. AITV upholds the invariant that each student will view semantically equivalent content at all times. A semantic compression model is developed to provide instructional videos at different level-of-details to accommodate dynamic network conditions and users’ system requirements. We take advantage of the semantic compression algorithm’s ability to provide different layers of semantically equivalent video by adapting the client to play at the appropriate layer that provides the client with the richest possible viewing experience. Video player actions, like play, pause and stop, can be initiated by any group member and and the results of those actions are synchronized with all the other students. These features allow students to review a lecture video in tandem, facilitating the learning process. Experimental trials show that AITV successfully synchronizes instructional videos for distributed students while concurrently optimizing the video quality, even under conditions of fluctuating bandwidth, by adaptively adjusting the quality level for each student while still maintaining the invariant.
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来源期刊
CiteScore
9.10
自引率
0.00%
发文量
14
期刊介绍: Discussions of computational methods, algorithms, implemented prototype systems, and applications of open and distance learning are the focuses of this publication. Practical experiences and surveys of using distance learning systems are also welcome. Distance education technologies published in IJDET will be divided into three categories, communication technologies, intelligent technologies.
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