Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 635

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Heuristic evaluation of ambient displays

Mankoff, Jennifer, Dey, Anind K., Hsieh, Gary, Kientz, Julie, Lederer, Scott, Ames, Morgan·2003·Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/642611.642642

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

See all 635

Metadata

Authors
Mankoff, J., Dey, A. K., Hsieh, G., Kientz, J., Lederer, S., & Ames, M.
Venue
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2003-04-05
Pages
169-176
OpenAlex
W2078569098
Cited by
635
References
3
FWCI
24.18
Type
conference paper
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Heuristic evaluation of ambient displays. https://app.cochat.ai/papers/10.1145/642611.642642
The paper
Mankoff, J., Dey, A. K., Hsieh, G., Kientz, J., Lederer, S., & Ames, M. (2003). Heuristic evaluation of ambient displays. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/642611.642642

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.