社群網路與數位科技的發展改變了傳統的互動模式，開啟了數位學習和傳播知識的創新典範。本研究有鑑於實境與線上的混合式學習，利用大規模的影片資源，突破學習無彊界。因此，面對大量與複雜的影片資訊，可以有效地註記、分類與過濾資訊成為知識管理的重要課題。

本研究在於探索TED Talks作為學習資源，提出一個以網路為基礎的使用介面，設計具有個人化情感語義的互動註記，協助學習者即時同步回饋與標註意義於影片片段中，透過視覺化的時間軸圖表，將個人的註記歷程有效地外顯化。本研究目的在於幫助學習者主動地回饋個人的內隱想法，也能有效地分類與檢視影片的資訊，更能藉由介面提升學習者、學習內容與學習社群的互動性與參與感。

本研究發現，對學習者而言，介面的互動註記成為反饋意見、標記重點與分類資訊的有效方式。尤其當眾多的學習者有著相同的學習目的，能夠經由互動註記共同參與標記，成為學習社群的協作註記。除了原有的文本內容，附加了不同脈絡詮釋的資訊，形成一種集體智慧的協作標註機制。於是，學習者因分享個人的註記至群體，也得以從群體的貢獻受惠給個人，協助有效地運用資訊，創造一個社群合作式學習之互惠關係。

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.

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