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RichReview++: Deployment of a Collaborative Multi-modal Annotation System for Instructor Feedback and Peer Discussion

Published: 27 February 2016 Publication History

Abstract

New multi-modal annotation tools hold the promise of bringing the benefits of face-to-face contact to remote, asynchronous interactions. One such system, RichReview++, incorporates new techniques to improve access to the embedded multimedia commentary and allows users to annotate with new modalities, like deictic gestures. We conducted a series of field deployments of RichReview++ to characterize how these features benefit students using them for activities in the university classroom. Our first deployment investigated the use of multi-modal annotations as a way for instructors to provide feedback on student term papers. Our second deployment used annotations to support peer discussion about assigned readings in a graduate-level course. We found that presenting voice comments as interactive waveforms seems to facilitate students' consumption of the instructor's voice comments. We also found that gestural annotations clarify voice and give annotators a quick and lightweight way to alter the scope of their voice comments. Based on these results, we suggest ways to best leverage multi-modal annotation tools in education environments.

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    cover image ACM Conferences
    CSCW '16: Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing
    February 2016
    1866 pages
    ISBN:9781450335928
    DOI:10.1145/2818048
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 27 February 2016

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    Author Tags

    1. Multi-modal annotation
    2. anchored comment
    3. collaborative annotation
    4. instructor feedback
    5. online peer-discussion.

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    February 27 - March 2, 2016
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    CSCW '16 Paper Acceptance Rate 142 of 571 submissions, 25%;
    Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

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    • (2022)Exploring Team-Sourced Hyperlinks to Address Navigation Challenges for Low-Vision Readers of Scientific PapersProceedings of the ACM on Human-Computer Interaction10.1145/35556296:CSCW2(1-23)Online publication date: 11-Nov-2022
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