Development of a Reading Material Recommender System Based On Design Science Research Approach

dc.contributor.author Eryilmaz, Evren
dc.contributor.author Thoms, Brian
dc.contributor.author Lee, Kuo-Hao
dc.contributor.author de Castro, Melissa
dc.date.accessioned 2019-01-03T00:05:07Z
dc.date.available 2019-01-03T00:05:07Z
dc.date.issued 2019-01-08
dc.description.abstract Using design science research (DSR), we outline the construction and evaluation of a recommender system incorporated into an existing computer-supported collaborative learning environment. Drawing from Clark’s communication theory and a user-centered design methodology, the proposed design aims to prevent users from having to develop their own conversational overload coping strategies detrimental to learning within large discussions. Two experiments were carried out to investigate the merits of three collaborative filtering recommender systems. Findings from the first experiment show that the constrained Pearson Correlation Coefficient (PCC) similarity metric produced the most accurate recommendations. Consistently, users reported that constrained PCC based recommendations served best to their needs, which prompted users to read more posts. Results from the second experiment strikingly suggest that constrained PCC based recommendations simplified users’ navigation in large discussions by acting as implicit indicators of common ground, freeing users from having to develop their own coping strategies.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2019.303
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59690
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Learning in Digital and Social Media
dc.subject Digital and Social Media
dc.subject Computer-supported collaborative learning, conversation overload, design science research, user-centered design
dc.title Development of a Reading Material Recommender System Based On Design Science Research Approach
dc.type Conference Paper
dc.type.dcmi Text
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
0250.pdf
Size:
1.04 MB
Format:
Adobe Portable Document Format
Description: