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Supporting focused work on window-based desktops Pilzer, Jan
Abstract
When working with a computer, information workers continuously switch tasks and applications to complete their work. Given the high fragmentation and complexity of their work, staying focused on the relevant pieces of information can become quite challenging in today's window-based environments, especially with the ever increasing size of display technology. To support workers in staying focused, we conducted a formative study with 18 professional information workers in which we examined their computer based and eye gaze interaction with the window environment and devised a relevance model of open windows. Based on the results, we developed a prototype to dim irrelevant windows and reduce distractions, and evaluated it in a user study. Our results show that participants keep an average of 12 windows open at all times, switch windows every 17 seconds, and that our prototype was able to predict and highlight relevant open windows with high accuracy and was considered helpful by the users.
Item Metadata
Title |
Supporting focused work on window-based desktops
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2019
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Description |
When working with a computer, information workers continuously switch tasks and applications to complete their work. Given the high fragmentation and complexity of their work, staying focused on the relevant pieces of information can become quite challenging in today's window-based environments, especially with the ever increasing size of display technology. To support workers in staying focused, we conducted a formative study with 18 professional information workers in which we examined their computer based and eye gaze interaction with the window environment and devised a relevance model of open windows. Based on the results, we developed a prototype to dim irrelevant windows and reduce distractions, and evaluated it in a user study. Our results show that participants keep an average of 12 windows open at all times, switch windows every 17 seconds, and that our prototype was able to predict and highlight relevant open windows with high accuracy and was considered helpful by the users.
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Genre | |
Type | |
Language |
eng
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Date Available |
2019-10-24
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0384561
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2019-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International