StreamWiki : Enabling viewers of knowledge sharing live streams to collaboratively generate archival documentation for effective in-stream and post-hoc learning

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Article number112
Journal / PublicationProceedings of the ACM on Human-Computer Interaction
Volume2
Issue numberCSCW
Publication statusPublished - 1 Nov 2018
Externally publishedYes

Abstract

Knowledge-sharing live streams are distinct from traditional educational videos, in part due to the large concurrently-viewing audience and the real-time discussions that are possible between viewers and the streamer. Though this medium creates unique opportunities for interactive learning, it also brings about the challenge of creating a useful archive for post-hoc learning. This paper presents the results of interviews with knowledge sharing streamers, their moderators, and viewers to understand current experiences and needs for sharing and learning knowledge through live streaming. Based on those findings, we built StreamWiki, a tool which leverages the availability of live stream viewers to produce useful archives of the interactive learning experience. On StreamWiki, moderators initiate high-level tasks that viewers complete by conducting microtasks, such as writing summaries, sending comments, and voting for informative comments. As a result, a summary document is built in real time. Through the tests of our prototype with streamers and viewers, we found that StreamWiki could help viewers understand the content and the context of the stream, during the stream and also later, for post-hoc learning.

Research Area(s)

  • Collaborative documentation, Knowledge building, Knowledge sharing, Learning, Live streaming

Bibliographic Note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to lbscholars@cityu.edu.hk.

Citation Format(s)

StreamWiki: Enabling viewers of knowledge sharing live streams to collaboratively generate archival documentation for effective in-stream and post-hoc learning. / Lu, Zhicong; Heo, Seongkook; Wigdor, Daniel.
In: Proceedings of the ACM on Human-Computer Interaction, Vol. 2, No. CSCW, 112, 01.11.2018.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review