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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Sensing Interruptibility in the Office: A Field Study on the Use of Biometric and Computer Interaction Sensors |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | CHI 2018 |
| Event Type | conference |
| Event Location | Montreal |
| Event Start Date | April 21 - 2018 |
| Event End Date | April 26 - 2018 |
| Place of Publication | Montreal, QC, Canada |
| Publisher | s.n. |
| Abstract Text | Knowledge workers experience many interruptions during their work day. Especially when they happen at inopportune moments, interruptions can incur high costs, cause time loss and frustration. Knowing a person's interruptibility allows optimizing the timing of interruptions and minimize disruption. Recent advances in technology provide the opportunity to collect a wide variety of data on knowledge workers to predict interruptibility. While prior work predominantly examined interruptibility based on a single data type and in short lab studies, we conducted a two-week field study with 13 professional software developers to investigate a variety of computer interaction, heart-, sleep-, and physical activity-related data. Our analysis shows that computer interaction data is more accurate in predicting interruptibility at the computer than biometric data (74.8% vs. 68.3% accuracy), and that combining both yields the best results (75.7% accuracy). We discuss our findings and their practical applicability also in light of collected qualitative data. |
| Digital Object Identifier | 10.1145/3173574.3174165 |
| Other Identification Number | merlin-id:16315 |
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