Cited by 60Innovative Human-Technology InteractionPersonal Information Management and User BehaviorUsability and User Interface Design

Design Recommendations for Self-Monitoring in the Workplace: Studies in Software Development

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Meyer, Andre N., Murphy, Gail C., Zimmermann, Thomas, Fritz, Thomas·2017·Proceedings of the ACM on Human-Computer Interaction

Abstract

One way to improve the productivity of knowledge workers is to increase their self-awareness about productivity at work through self-monitoring. Yet, little is known about expectations of, the experience with, and the impact of self-monitoring in the workplace. To address this gap, we studied software developers, as one community of knowledge workers. We used an iterative, user-feedback-driven development approach (N=20) and a survey (N=413) to infer design elements for workplace self-monitoring, which we then implemented as a technology probe called WorkAnalytics. We field-tested these design elements during a three-week study with software development professionals (N=43). Based on the results of the field study, we present design recommendations for self-monitoring in the workplace, such as using experience sampling to increase the awareness about work and to create richer insights, the need for a large variety of different metrics to retrospect about work, and that actionable insights, enriched with benchmarking data from co-workers, are likely needed to foster productive behavior change and improve collaboration at work. Our work can serve as a starting point for researchers and practitioners to build self-monitoring tools for the workplace.

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Crossref · 10.1145/3134714

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  • Researchers have started building retrospective dashboards for developers and other knowledge workers, usually visualizing data at the level of applications or application categories, but suggesting that a per-task level would be more beneficial.

    “Recently, researchers started building retrospective dashboards for developers [42], [65], [79], [80] and other knowledge workers [66], [81], [82], usually by visualizing data on the level of applications or application categories, but suggesting that a per-task level would be more beneficial.”

    From Detecting Developers' Task Switches and Types (2022) · cites this paper as [42]

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Authors
Meyer, A. N., Murphy, G. C., Zimmermann, T., & Fritz, T.
Affiliations
  • University of Zurich, Zurich, Switzerland
  • University of British Columbia (CA)
  • Microsoft (United States) (US)
Venue
Proceedings of the ACM on Human-Computer Interaction
Published
2017-12-06
Volume
1
Issue
CSCW
Pages
1-24
ISSN
2573-0142 (ISSN-L)
OpenAlex
W2774782036
Cited by
60
References
66
Citations by year
2026: 5 · 2025: 9 · 2024: 8 · 2023: 10 · 2022: 3 · 2021: 8 · 2020: 10 · 2019: 3 · 2018: 4
FWCI
5.75
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the ACM on Human-Computer Interaction (publishedVersion)
  • Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
  • Zurich Open Repository and Archive (University of Zurich)
Funders
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (156997)
  • Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (RGPIN-2016-03758)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Social Sciences › Decision Sciences › Information Systems and Management › Personal Information Management and User Behavior
  • Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
Keywords
knowledge workers, software developers, productivity, self-awareness, ecological momentary assessment, productivity indicators, benchmarking, behavior change, collaboration, design guidelines, technology probe

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