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Heuristic evaluation of ambient displays
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Proceedings of the SIGCHI conference on Human factors in computing systems table of contents
Ft. Lauderdale, Florida, USA
SESSION: Peripheral and ambient displays table of contents
Pages: 169 - 176  
Year of Publication: 2003
ISBN:1-58113-630-7
Authors
Jennifer Mankoff  UC, Berkeley, Berkeley, CA
Anind K. Dey  Intel Research, Berkeley, CA
Gary Hsieh  UC, Berkeley, Berkeley, CA
Julie Kientz  University of Toledo, Toledo, OH
Scott Lederer  UC, Berkeley, Berkeley, CA
Morgan Ames  UC, Berkeley, Berkeley, CA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 34,   Downloads (12 Months): 358,   Citation Count: 41
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ABSTRACT

We present a technique for evaluating the usability and effectiveness of ambient displays. Ambient displays are abstract and aesthetic peripheral displays portraying non-critical information on the periphery of a user's attention. Although many innovative displays have been published, little existing work has focused on their evaluation, in part because evaluation of ambient displays is difficult and costly. We adapted a low-cost evaluation technique, heuristic evaluation, for use with ambient displays. With the help of ambient display designers, we defined a modified set of heuristics. We compared the performance of Nielsen's heuristics and our heuristics on two ambient displays. Evaluators using our heuristics found more, severe problems than evaluators using Nielsen's heuristics. Additionally, when using our heuristics, 3-5 evaluators were able to identify 40--60% of known usability issues. This implies that heuristic evaluation is an effective technique for identifying usability issues with ambient displays.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  41
 
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Jennifer Mankoff: colleagues
Anind K. Dey: colleagues
Gary Hsieh: colleagues
Julie Kientz: colleagues
Scott Lederer: colleagues
Morgan Ames: colleagues

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