Share Paper: Using Novel Video Indexing and Data Analytics Tool to Enhance Interactions in e-Learning

1. Shuangbao Wang, University of Maryland, United States
2. William Kelly, Metonymy Corporation, United States
3. Jie Zhang, Academy of Science, China

Abstract: In this paper, we present a novel system - inVideo for video data analytics, and its use in learning analytics as the field strives towards new cultures of learning in the digital realm involving large quantities of video data in online learning systems and MOOCs. InVideo is able to analyze video content automatically without the need for initial viewing by a human. Using a highly efficient video indexing engine we developed, the system is able to analyze both language and video frames. The time-stamped commenting and tagging features make it an effective tool for increasing interactions between students and e-learning ...