TY - GEN
T1 - Decipher
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
AU - Yen, Yu Chun Grace
AU - Kim, Joy O.
AU - Bailey, Brian P.
N1 - Funding Information:
This work was supported in part by NSF awards 1462693 and 1530818 and a graduate dissertation fellowship awarded to the first author.
Publisher Copyright:
© 2020 ACM.
PY - 2020/4/21
Y1 - 2020/4/21
N2 - Feedback from diverse audiences can vary in focus, differ in structure, and contradict each other, making it hard to interpret and act on. While prior work has explored generating quality feedback, our work helps a designer interpret that feedback. Through a formative study with professional designers (N=10), we discovered that the interpretation process includes categorizing feedback, identifying valuable feedback, and prioritizing which feedback to incorporate in a revision. We also found that designers leverage feedback topic and sentiment, and the status of the provider to aid interpretation. Based on the findings, we created a new tool (Decipher) that enables designers to visualize and navigate a collection of feedback using its topic and sentiment structure. In a preliminary evaluation (N=20), we found that Decipher helped users feel less overwhelmed during feedback interpretation tasks and better attend to critical issues and conflicting opinions compared to using a typical document-editing tool.
AB - Feedback from diverse audiences can vary in focus, differ in structure, and contradict each other, making it hard to interpret and act on. While prior work has explored generating quality feedback, our work helps a designer interpret that feedback. Through a formative study with professional designers (N=10), we discovered that the interpretation process includes categorizing feedback, identifying valuable feedback, and prioritizing which feedback to incorporate in a revision. We also found that designers leverage feedback topic and sentiment, and the status of the provider to aid interpretation. Based on the findings, we created a new tool (Decipher) that enables designers to visualize and navigate a collection of feedback using its topic and sentiment structure. In a preliminary evaluation (N=20), we found that Decipher helped users feel less overwhelmed during feedback interpretation tasks and better attend to critical issues and conflicting opinions compared to using a typical document-editing tool.
KW - creativity
KW - creativity support tools
KW - feedback
KW - sense-making
UR - http://www.scopus.com/inward/record.url?scp=85091275474&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091275474&partnerID=8YFLogxK
U2 - 10.1145/3313831.3376380
DO - 10.1145/3313831.3376380
M3 - Conference contribution
AN - SCOPUS:85091275474
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 25 April 2020 through 30 April 2020
ER -