TY - GEN
T1 - Aligning Data with the Goals of an Organization and Its Workers
T2 - 2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024
AU - Gondimalla, Apoorva
AU - Sreekanth, Varshinee
AU - Joshi, Govind
AU - Nelson, Whitney
AU - Choi, Eunsol
AU - Slota, Stephen C.
AU - Greenberg, Sherri R.
AU - Fleischmann, Kenneth R.
AU - Lee, Min Kyung
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s)
PY - 2024/5/11
Y1 - 2024/5/11
N2 - The challenges of data collection in nonprofits for performance and funding reports are well-established in HCI research. Few studies, however, delve into improving the data collection process. Our study proposes ideas to improve data collection by exploring challenges that social workers experience when labeling their case notes. Through collaboration with an organization that provides intensive case management to those experiencing homelessness in the U.S., we conducted interviews with caseworkers and held design sessions where caseworkers, managers, and program analysts examined storyboarded ideas to improve data labeling. Our findings suggest several design ideas on how data labeling practices can be improved: Aligning labeling with caseworker goals, enabling shared control on data label design for a comprehensive portrayal of caseworker contributions, improving the synthesis of qualitative and quantitative data, and making labeling user-friendly. We contribute design implications for data labeling to better support multiple stakeholder goals in social service contexts.
AB - The challenges of data collection in nonprofits for performance and funding reports are well-established in HCI research. Few studies, however, delve into improving the data collection process. Our study proposes ideas to improve data collection by exploring challenges that social workers experience when labeling their case notes. Through collaboration with an organization that provides intensive case management to those experiencing homelessness in the U.S., we conducted interviews with caseworkers and held design sessions where caseworkers, managers, and program analysts examined storyboarded ideas to improve data labeling. Our findings suggest several design ideas on how data labeling practices can be improved: Aligning labeling with caseworker goals, enabling shared control on data label design for a comprehensive portrayal of caseworker contributions, improving the synthesis of qualitative and quantitative data, and making labeling user-friendly. We contribute design implications for data labeling to better support multiple stakeholder goals in social service contexts.
KW - Case Notes
KW - Data Collection Practices
KW - Data Labeling
KW - Design Ideas
KW - Nonprofits
KW - Social Work
UR - http://www.scopus.com/inward/record.url?scp=85194824407&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85194824407&partnerID=8YFLogxK
U2 - 10.1145/3613904.3642014
DO - 10.1145/3613904.3642014
M3 - Conference contribution
AN - SCOPUS:85194824407
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2024 - Proceedings of the 2024 CHI Conference on Human Factors in Computing Sytems
PB - Association for Computing Machinery
Y2 - 11 May 2024 through 16 May 2024
ER -