Developing a Real-time Video Annotation Interface for Interactive Learning

Abstract

The development of social network and technology changes the way of the conventional interaction between teaching and learning opening up an innovative model of digital learning and the spread of knowledge In view of the fact the mixture of reality and online learning is breaking the learning boundary by means of massive source of videos Therefore facing unstructured and linear features of videos figuring out an effective method which help leaners annotate sort and filter efficiently becomes an imperative issue of knowledge management to annotate thoughts in time-intensive process or to find specific information in a large number of videos This research is to develop a web-based annotation interface exploring personal affective semantic annotation by applying TED Talks as learning resources so as to help learners instant feedbacks and label meanings in video segments In addition this study aims to help learners actively represent their implicit thoughts and to effectively annotate classify and review information by visual timeline chart It provides a useful interface to enhance the interactivity and engagement of learners learning content and learning community The study has shown that the interactive annotation is an effective method to express learner's implicit feedbacks label key views and classify different information In particular when a large number of learners have the same learning objective they can simultaneously participate in this interactive annotation in turn becoming a collaborative annotation of learning community Consequently a collective intelligence mechanism can be established These annotations not only maintain original textual contents but also attach additional contexts from individual and group learners As a result learners can share individual annotation with the community and benefit a lot from this community as well This helps learners with the effective usage judgment and management of information creating a mutual benefit from social collaborative relationship

Date of Award	2015 Dec 2
Original language	English
Supervisor	Taysheng Jeng (Supervisor)