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Title: AuDi: an Auto-Feedback Display for Crowdsourcing
Authors: Tang, Xinru
Zhao, Dongyang
Zhang, Ying
Ding, Xianghua
Issue Date: 2019
Publisher: European Society for Socially Embedded Technologies (EUSSET)
metadata.dc.relation.ispartof: Proceedings of 17th European Conference on Computer-Supported Cooperative Work
Series/Report no.: Reports of the European Society for Socially Embedded Technologies: vol. 3, no. 1
Abstract: While feedback, by experts or peers, is found to have positive effects on crowdsourcing work, it is a costly approach as more people or time is involved in order to provide feedback. This paper explores an automatic feedback display called AuDi for crowdsourcing. AuDi shows the worker’s accuracy rate, which is automatically calculated with the use of an accuracy algorithm, by changing the background color of the task page. We conducted an experimental study with AuDi in the field, and employed both quantitative and qualitative methods for data collection and analysis. Our study shows that, without introducing new cost, such an auto-feedback display is well received by our participants, gives them assurance and more confidence, and also positively contributes to work performance by pushing them to study more and understand better the task requirements.
metadata.dc.identifier.doi: 10.18420/ecscw2019_ep05
ISSN: 2510-2591
metadata.mci.conference.location: Salzburg, Austria 8 - 12 June 2019
Appears in Collections:ECSCW 2019 Exploratory Papers

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