The increase in use of online educational tools has led to a large amount of educational video materials made available for students. Finding the right video content is usually supported by the overarching learning management system and its interface that organises video items by course, categories and weeks, and makes them searchable. However, once a video is found, students are left without further guidance as to what parts in that video they should focus on. In this article, an additional timeline visualisation to augment the conventional playback timeline is introduced which employs a novel playback weighting strategy in which the history of different video interactions generate scores based on the context of each playback. The resultant scores are presented on the additional timeline, making it in effect a playback-centric usage graph nuanced by how each playback was executed. Students can selectively watch those portions which the contour of the usage visualisation suggests. The visualisation was implemented and deployed in an undergraduate course at a university for two full semesters. 270 students used the system throughout both semesters watching 52 videos, guided by visualisations on what to watch. Analysis of playback logs revealed students selectively watched corresponding to the most important portions of the videos as assessed by the instructor who created the videos. The characteristics of this as a way of guiding students as to where to watch as well as a complementary tool for playback analysis, are discussed. Further insights into the potential values of this visualisation and its underlying playback weighting strategy are also discussed.
翻译:在线教育工具的使用量的增加导致向学生提供大量教育视频材料。找到正确的视频内容通常得到总体学习管理系统及其界面的支持,后者按课程、类别和周对视频项目按课程、类别和周排列,并进行搜索。然而,一旦找到视频,学生就离开,没有进一步指导该视频中哪些部分应该关注。在本篇文章中,引入了额外的时间线可视化,以扩大传统播放回放时间框架,采用新颖的回放权加权策略,不同视频互动的历史根据每个播放回放的背景产生得分。在附加的时针上展示了相应的分数,使其具有以播放回放为主的用量图,通过执行每个播放回放的方式对每个播放的用量图进行细微分。学生们可以有选择地观看这些部分,使用图像的轮廓表明他们应该关注哪些部分。在大学的本科课程中实施并部署了整整两个学期。270名学生在两学期里都使用这个系统观看52个视频,以观看时的可视内容为指导。 剧背记录显示学生有选择地观看了与最重要的视觉前视值对应的比重图,作为指导工具分析工具的视觉分析的一部分,作为指导工具,并评估工具的视觉分析工具,作为工具的推。作为背景分析工具的推导工具的推导工具的推导。