@inproceedings{83461bdb203b4643be114f47a7c02135,
title = "From in the class or in the wild? Peers provide better design feedback than external crowds",
abstract = "As demand for design education increases, instructors are struggling to provide timely, personalized feedback for student projects. Gathering feedback from classroom peers and external crowds offer scalable approaches, but there is little evidence of how they compare. We report on a study in which students (n=127) created early- and late-stage prototypes as part of nine-week projects. At each stage, students received feedback from peers and external crowds: their own social networks, online communities, and a task market. We measured the quality, quantity and valence of the feedback and the actions taken on it, and categorized its content using a taxonomy of critique discourse. The study found that peers produced feedback that was of higher perceived quality, acted upon more, and longer compared to the crowds. However, crowd feedback was found to be a viable supplement to peer feedback and students preferred it for projects targeting specialized audiences. Feedback from all sources spanned only a subset of the critique categories. Instructors may fill this gap by further scaffolding feedback generation. The study contributes insights for how to best utilize different feedback sources in project-based courses.",
keywords = "Crowdsourcing, Design methods, Feedback, Learning",
author = "Helen Wauck and Yen, {Yu Chun} and Fu, {Wai Tat} and Elizabeth Gerber and Dow, {Steven P.} and Bailey, {Brian P.}",
note = "This work was funded in part by the National Science Foundation under awards 1530818, 1462693, 1122206 and 1122320, the first author{\textquoteright}s NSF Graduate Research Fellowship under award 1144245, and an award received by the last author from the Grants for the Advancement of Teaching Engineering program at the University of Illinois.; 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017 ; Conference date: 06-05-2017 Through 11-05-2017",
year = "2017",
month = may,
day = "2",
doi = "10.1145/3025453.3025477",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
pages = "5580--5591",
booktitle = "CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems",
address = "United States",
}