{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/50719"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/50719","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Designing with crowds","abstract":"Feedback plays an essential role in the evolution of a design from initial concept to final representation. There are several approaches to receive feedback on designs such as organizing critiques, informally asking peers, and participating in online feedback communities. However, these social approaches highly depend on a user’s social capital and peer networks, and thus the access to desired feedback is limited. This dissertation explores the use of non-expert crowds to generate helpful, affordable, and timely feedback for visual design. The key innovation is the concept of generating structured feedback from non-experts. Based on a formative study, I identified several types of perception-oriented feedback desired from non-experts. To generate this feedback, I designed and implemented a new crowd-based system called Voyant. Voyant enables any user who creates visual designs to receive perception-oriented feedback on the designs from a selected audience. The generated feedback includes the elements seen in a design, the order in which elements are noticed, impressions formed when the design is first viewed, and interpretation of the design relative to guidelines in the domain and the user’s stated goals. I evaluated Voyant with users and their own designs. My evaluations reveal that crowd feedback helps users improve their designs in practice. The feedback helped users identify design problems, gain insight into their designs, and consider their designs from diverse perspectives. The monetary cost of generating the feedback was considered a fair tradeoff for not having to organize critiques or interrupt peers. The content analysis reveals that Voyant generated more interpretative, diverse, and critical feedback than free-form prompts. This dissertation provides the empirical evidence that crowd feedback benefits the end user and contributes new lessons for designing crowd feedback systems that support design activities. Crowd feedback systems provide users more opportunities to make design decisions based on audience input rather than solely on intuitions. These systems have the potential to tighten the design cycle and help users iterate toward solutions that better connect with the intended audience.","abstract_html":"Feedback plays an essential role in the evolution of a design from initial concept to final representation. There are several approaches to receive feedback on designs such as organizing critiques, informally asking peers, and participating in online feedback communities. However, these social approaches highly depend on a user’s social capital and peer networks, and thus the access to desired feedback is limited. This dissertation explores the use of non-expert crowds to generate helpful, affordable, and timely feedback for visual design. The key innovation is the concept of generating structured feedback from non-experts. Based on a formative study, I identified several types of perception-oriented feedback desired from non-experts. To generate this feedback, I designed and implemented a new crowd-based system called Voyant. Voyant enables any user who creates visual designs to receive perception-oriented feedback on the designs from a selected audience. The generated feedback includes the elements seen in a design, the order in which elements are noticed, impressions formed when the design is first viewed, and interpretation of the design relative to guidelines in the domain and the user’s stated goals. I evaluated Voyant with users and their own designs. My evaluations reveal that crowd feedback helps users improve their designs in practice. The feedback helped users identify design problems, gain insight into their designs, and consider their designs from diverse perspectives. The monetary cost of generating the feedback was considered a fair tradeoff for not having to organize critiques or interrupt peers. The content analysis reveals that Voyant generated more interpretative, diverse, and critical feedback than free-form prompts. This dissertation provides the empirical evidence that crowd feedback benefits the end user and contributes new lessons for designing crowd feedback systems that support design activities. Crowd feedback systems provide users more opportunities to make design decisions based on audience input rather than solely on intuitions. These systems have the potential to tighten the design cycle and help users iterate toward solutions that better connect with the intended audience.","abstract_has_math":false,"creators":["Xu, Anbang"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Bailey, Brian P.","Fu, Wai-Tat","Karahalios, Karrie G.","Dow, Steven P."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-09-16T17:25:44Z","date_published":"2014-09-16T17:25:44Z","updated_at":"2026-07-22T22:25:41Z","subjects":["Crowd feedback","Crowdsourcing","Design Iteration","Visual Design","Creativity","Critique"],"languages":["en"],"rights":["Copyright 2014 Anbang Xu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/50719","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bailey, Brian P.","Fu, Wai-Tat","Karahalios, Karrie G.","Dow, Steven P."]},{"key":"dc:creator","label":"Author","values":["Xu, Anbang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-09-16T17:25:44Z","2014-08","2014-09-16"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Crowd feedback","Crowdsourcing","Design Iteration","Visual Design","Creativity","Critique"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2014 Anbang Xu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/50719"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Feedback plays an essential role in the evolution of a design from initial concept to final representation. 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The generated feedback includes the elements seen in a design, the order in which elements are noticed, impressions formed when the design is first viewed, and interpretation of the design relative to guidelines in the domain and the user’s stated goals. I evaluated Voyant with users and their own designs. My evaluations reveal that crowd feedback helps users improve their designs in practice. The feedback helped users identify design problems, gain insight into their designs, and consider their designs from diverse perspectives. The monetary cost of generating the feedback was considered a fair tradeoff for not having to organize critiques or interrupt peers. The content analysis reveals that Voyant generated more interpretative, diverse, and critical feedback than free-form prompts. This dissertation provides the empirical evidence that crowd feedback benefits the end user and contributes new lessons for designing crowd feedback systems that support design activities. 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This dissertation explores the use of non-expert crowds to generate helpful, affordable, and timely feedback for visual design. The key innovation is the concept of generating structured feedback from non-experts. Based on a formative study, I identified several types of perception-oriented feedback desired from non-experts. To generate this feedback, I designed and implemented a new crowd-based system called Voyant. Voyant enables any user who creates visual designs to receive perception-oriented feedback on the designs from a selected audience. The generated feedback includes the elements seen in a design, the order in which elements are noticed, impressions formed when the design is first viewed, and interpretation of the design relative to guidelines in the domain and the user’s stated goals. I evaluated Voyant with users and their own designs. My evaluations reveal that crowd feedback helps users improve their designs in practice. The feedback helped users identify design problems, gain insight into their designs, and consider their designs from diverse perspectives. The monetary cost of generating the feedback was considered a fair tradeoff for not having to organize critiques or interrupt peers. The content analysis reveals that Voyant generated more interpretative, diverse, and critical feedback than free-form prompts. This dissertation provides the empirical evidence that crowd feedback benefits the end user and contributes new lessons for designing crowd feedback systems that support design activities. Crowd feedback systems provide users more opportunities to make design decisions based on audience input rather than solely on intuitions. 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