Combining Crowdsourcing and Learning to Improve Engagement and Performance

被引:19
作者
Dontcheva, Mira [1 ]
Morris, Robert [2 ]
Brandt, Joel [1 ]
Gerber, Elizabeth M. [3 ]
机构
[1] Adobe Res, San Francisco, CA 94107 USA
[2] MIT, Media Lab, Cambridge, MA 02139 USA
[3] Northwestern Univ, Evanston, IL USA
来源
32ND ANNUAL ACM CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2014) | 2014年
关键词
Crowdsourcing; training; games;
D O I
10.1145/2556288.2557217
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Crowdsourcing complex creative tasks remains difficult, in part because these tasks require skilled workers. Most crowdsourcing platforms do not help workers acquire the skills necessary to accomplish complex creative tasks. In this paper, we describe a platform that combines learning and crowdsourcing to benefit both the workers and the requesters. Workers gain new skills through interactive step-by-step tutorials and test their knowledge by improving real-world images submitted by requesters. In a series of three deployments spanning two years, we varied the design of our platform to enhance the learning experience and improve the quality of the crowd work. We tested our approach in the context of Level Up for Photoshop, which teaches people how to do basic photograph improvement tasks using Adobe Photoshop. We found that by using our system workers gained new skills and produced high-quality edits for requested images, even if they had little prior experience editing images.
引用
收藏
页码:3379 / 3388
页数:10
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