Toward a Theory of Situation Awareness in Dynamic Systems
Abstract
This chapter presents a theoretical model of situation awareness (SA) based on its role in dynamic human decision making in a variety of domains. SA is presented as a predominant concern in system operation, based on a descriptive view of decision making. The chapter shows the importance of situation awareness in decision making in dynamic environments and the utility of using a model of decision making that takes SA into account. It also shows a theory of SA that expands on prior work in this area. The chapter presents a model of SA, including various mechanisms and factors hypothesized to be important for its generation. As a matter of consistent terminology, it is first necessary to distinguish the term situation awareness , as a state of knowledge, from the processes used to achieve that state. A model of SA has been presented in relation to decision making in complex systems.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Situation Awareness theory conceptualizes reasoning as a progression through three stages: Perception, Comprehension, and Projection.
“Situation Awareness (SA) theory conceptualizes reasoning as a progression through three stages: Perception (noticing elements), Comprehension (interpreting their meaning), and Projection (anticipating consequences) [21, 22].”
From Criticmate: Stagewise Human–AI Co-Critique in Single-Screen UI Evaluation (2026) · cites this paper as [22]
Expert evaluators naturally distribute their work across Perception, Comprehension, and Projection, weaving together global and local reasoning and gradually moving from surface checks toward root-cause diagnosis.
“expert evaluators naturally distribute their work across Perception , Comprehension , and Projection [21, 22], weaving together global and local reasoning and gradually moving from surface checks toward root-cause diagnosis.”
From Criticmate: Stagewise Human–AI Co-Critique in Single-Screen UI Evaluation (2026) · cites this paper as [22]
Cited by
Sorted by citations
Criticmate: Stagewise Human–AI Co-Critique in Single-Screen UI Evaluation
Ko, J., Choi, J., Morales, C., Kim, D., & Ko, M. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790929 · Cited by 1 · see citing works
- Authors
- Endsley, M. R.
- Corresponding author
- Endsley, Mica R
- ORCID
- Endsley, Mica R
- Venue
- Situational Awareness
- Publisher
- Routledge
- Published
- 2017-07-05
- Pages
- 9-42
- OpenAlex
- W4239895564
- Cited by
- 348
- References
- 0
- Citations by year
- 2026: 58 · 2025: 9 · 2024: 21 · 2023: 52 · 2022: 40 · 2021: 28 · 2020: 25 · 2019: 23 · 2018: 12 · 2017: 7 · 2016: 15 · 2015: 10 · 2014: 7 · 2013: 7 · 2012: 8
- FWCI
- 70.67
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Physical Sciences › Engineering › Control and Systems Engineering › Military Strategy and Technology
- Social Sciences › Decision Sciences › Management Science and Operations Research › Complex Systems and Decision Making
- Keywords
- situational awareness, dynamical systems, human decision-making, decision models, complex systems, dynamic environments
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
