Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 9

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Using Eye-Tracking Video Data to Augment Knowledge Elicitation in Cognitive Task Analysis

Seagull, F Jacob, Xiao, Yan·2001·Proceedings of the Human Factors and Ergonomics Society Annual Meeting

Abstract

Cognitive task analysis (CTA) is a process to determine cognitive activities required to accomplish a given task. Different methods have been proposed and advocated in performing CTA. In this paper, we report a pilot trial using eye-tracking data to facilitate CTA. A mobile eye-tracking device was used in surgical operating rooms to acquire eye-tracking data from an operator during a highly complex, taxing procedure: tracheal intubation. A desktop task analysis was performed to establish visual cues and their associated goals during tracheal intubation. Eye tracking data were reviewed by Subject Matter Experts (SMEs) as memory recall cues. The advantage of such use of eye tracking data was that the SMEs did not have to provide frame-by-frame analysis of the fixations, since they provided speculation on fixations and mental processes, cued by the eye tracking data. Pilot trials showed the value of eye tracking data in CTA in terms of knowledge elicitation. Future exploration of such methodology is highly suggested given the increasing feasibility of deploying eye-tracking devices.

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 · 10.1177/154193120104500429

Cites

1 of 1 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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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

Research works printed but not linked: 14

  1. Dominguez C. (1998). Expertise in laparoscopic surgery: anticipation and affordances. In: Proceedings of Naturalistic Decision Making 4 Warrenton VA, May 1998.
  2. DuBois D., 1995, Cognitively diagnostic assessment, 189
  3. Ericsson KA, 1984, Protocol Analysis: Verbal reports as data
  4. Flach J., 2000, Cognitive Task Analysis
  5. 10.21236/ADA303654 · DOI
  6. 10.1006/obhd.1995.1039 · DOI · Paper page
  7. Klein G. A., 1989, Advances in man machine systems research, 5
  8. Klein G., 1999, Sources of Power: How People Make Decisions
  9. 10.1177/154193129904300323 · doi:10.1177/154193129904300323
  10. 10.2466/pms.1994.79.3f.1411 · DOI
  11. 10.1080/00140138608967247 · doi:10.1080/00140138608967247
  12. 10.4324/9781410605795 · DOI · Paper page
  13. Seagull FJ, Xiao Y. (1999). Monitoring behavior: A pilot study using an ambulatory eye-tracker in surgical operating rooms. Annual Meeting of the Human Factors and Ergonomics Society, 1999. · doi:10.1037/e575792012-003
  14. Via DK, Kyle R, Xiao Y., Seagull J., Mackenzie CF. (2001). Eye tracking system improves evaluation of performance during simulated anesthesia events. Proceedings of the annual meeting of the Society for Technology in Anesthesia (in press)

Cited by

See all 9

Metadata

Authors
Seagull, F. J., & Xiao, Y.
Affiliations
University of Maryland
Venue
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2001-10
Volume
45
Issue
4
Pages
400-403
ISSN
  • 1071-1813
  • 2169-5067
Cited by
9
References
1
Language
en
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)

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

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.