Aligning data with organization's and workers' goals: designing data labeling systems for social service case notes

dc.contributor.advisorLee, Min Kyung, Ph. D.
dc.creatorGondimalla, Apoorva
dc.date.accessioned2024-04-19T15:10:29Z
dc.date.available2024-04-19T15:10:29Z
dc.date.issued2023-08
dc.date.submittedAugust 2023
dc.date.updated2024-04-19T15:10:29Z
dc.description.abstractIn the era of data-driven approaches in non-profit and social service government organizations, prevailing data collection methods for performance and funding reports are ineffective and unsatisfactory for both workers and organizational leaders. Within social service provision, evaluating outcomes necessitates intricate subjective assessments, resulting in social workers equipped with profound insights into services and outcomes shouldering the burden of manual record-keeping. Simultaneously, organizational leaders grapple with insufficient data for reporting. While existing research explores data collection challenges, there is a dearth of studies that delve into solutions for enhancing these systems. This study examines data labeling systems that encapsulate client interaction outcomes, focusing on caseworkers aiding those experiencing homelessness. Despite advances in domains such as crowd-sourced data labeling, their approaches often fail to consider the unique values and contexts of social workers who intertwine data labeling with their caregiving work. By employing interviews, ideation, and a speed-dating approach, we scrutinize preferences, potential solutions, and challenges in crafting efficient data labeling systems. We evaluate 15 diverse design ideas across four dimensions: alignment with case management objectives, comprehensive portrayal of caseworker contributions, clarity in data labels, and enhancements in labeling process usability. Our findings highlight the collective aspiration for data labeling systems that cater to varied stakeholder information goals while effectively capturing nuanced casework details, streamlining data labeling into a seamless, efficient task. Leveraging our insights, we offer design implications for enhancing data labeling systems, aligning them with the objectives of both organizations and workers.
dc.description.departmentInformation
dc.format.mimetypeapplication/pdf
dc.identifier.uri
dc.identifier.urihttps://hdl.handle.net/2152/124874
dc.identifier.urihttps://doi.org/10.26153/tsw/51476
dc.language.isoen
dc.subjectHuman-computer interaction
dc.subjectData labeling
dc.subjectData collection
dc.subjectCo-design
dc.subjectDesign implications
dc.subjectSocial service
dc.titleAligning data with organization's and workers' goals: designing data labeling systems for social service case notes
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentInformation
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.nameMaster of Science in Information Studies

Access full-text files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
GONDIMALLA-PRIMARY-2024-1.pdf
Size:
2.24 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 2 of 2
No Thumbnail Available
Name:
LICENSE.txt
Size:
1.85 KB
Format:
Plain Text
Description:
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
4.46 KB
Format:
Plain Text
Description: