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Collaborative Content Creation: Impact of Media Type on Author Behavior

Lookup NU author(s): Anna Vasilchenko, Dr Ghaith Tarawneh, Haneen Qarabash, Dr Madeline Balaam



This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by ACM, 2018.

For re-use rights please refer to the publisher's terms and conditions.


Modern education incorporates strong elements of collaborative learning: activities that prompt students to collaborate on completing learning tasks. In this work we investigate the relationship between media type and student collaboration and attribution patterns during collaborative content creation. We run similarity analyses on text and video artifacts submitted by students as part of collaborative exercises in an undergraduate module. Our main finding is that the same cohort of students was significantly more likely to attribute non-original content to its sources when authoring text compared to video content and when this content is not produced by a peer student. Our preliminary results based on only two media suggest that media type has a considerable impact on student collaborative behavior. We conclude that media type must be taken into consideration when designing collaborative learning exercises and addressing issues of academic integrity and copyright infringements.

Publication metadata

Author(s): Vasilchenko A, Tarawneh G, Qarabash H, Balaam M

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: The ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW)

Year of Conference: 2018

Pages: 341–344

Print publication date: 29/10/2018

Online publication date: 29/10/2018

Acceptance date: 10/08/2018

Date deposited: 04/07/2020

Publisher: ACM


DOI: 10.1145/3272973.3274092

Library holdings: Search Newcastle University Library for this item

Series Title: CSCW '18: Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing

ISBN: 9781450360180