Naturalistic decision making and macrocognition:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Aldershot [u.a.]
Ashgate
2008
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XXVI, 411 S. Ill., graph. Darst. |
| ISBN: | 9780754670209 |
Internformat
MARC
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| 020 | |a 9780754670209 |9 978-0-7546-7020-9 | ||
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| 245 | 1 | 0 | |a Naturalistic decision making and macrocognition |c ed. by Jan Maarten Schraagen ... |
| 264 | 1 | |a Aldershot [u.a.] |b Ashgate |c 2008 | |
| 300 | |a XXVI, 411 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 650 | 4 | |a Decision making | |
| 650 | 4 | |a Cognition | |
| 650 | 4 | |a Task analysis | |
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| 700 | 1 | |a Schraagen, Jan Maarten |d 1960- |e Sonstige |0 (DE-588)1191785831 |4 oth | |
| 856 | 4 | 2 | |m Digitalisierung UB Bamberg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016517482&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
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Datensatz im Suchindex
| _version_ | 1804137684235452416 |
|---|---|
| adam_text | Contents
List of Figures
vii
List of Tables
xi
Notes on Contributors
xiii
Foreword
xxv
PARTI ORIENTATION
1
The Macrocognition Framework of Naturalistic Decision Making
3
Jan Maarten
Schraagen, Gary Klein, and Robert R. Hoffman
2
Mind the Gap: A Skeptical View of Macrocognition
27
John M.
Flach
3
Technology and Naturalistic Decision Making: Myths and Realities
41
Kathleen L.
Mos
ier
PART II THE HEARTLAND OF MACROCOGNITION
4
Macrocognition, Mental Models, and Cognitive Task
Analysis Methodology
57
Gary Klein and Robert R. Hoffman
5
Investigative Sensemaking in Criminal Contexts
81
Thomas C. Ormerod, Emma C. Barrett, and Paul J. Taylor
6
Learning from Experience: Incident Management Team Leader Training
103
Margaret T. Crichton,
Kristina Lauche,
and Rhona
Flin
7
Making Sense of Human Behavior: Explaining How Police Officers
Assess Danger During Traffic Stops
121
Laura A. Zimmerman
8
Cultural Variations in Mental Models of Collaborative Decision Making
141
Anna P. McHugh, Jennifer L. Smith, and Winston R. Sieck
9
Athletes, Murderers, and a Chinese Farmer: Cultural Perspectives
on Sensemaking
159
Mei-Hua Lin and Helen
Altman
Klein
vi
Naturalistic Decision Making and Macrocognition
10
Strategies in Naturalistic Decision Making: A Cognitive Task Analysis
of Naval Weather Forecasting
183
Susan Joslyn and David W. Jones
11
Supporting Macrocognition in Health Care: Improving
Clinical Reminders
203
Laura
G
Militello, Emily S. Patterson, Jason J. Saleem, Shilo Anders,
and Steven
Asch
12
Macrocognition and Experiential Learning in Surgical Teams
221
Simon Henderson
13
Macrocognition in Systems Engineering: Supporting Changes
in the Air Traffic Control Tower
251
Peter
Moertl,
Craig Bonaceto, Steven
Estes,
and Kevin Burns
PART III MICRO-MACRO RELATIONSHIPS
14
Bridging
Macrocognitive/Microcognitive
Methods: ACT-R
Under Review
277
Claire McAndrew, Adrian Banks, and Julie Gore
15
Reconceptualizing Expertise: Learning from an Expert s Error
301
Stephen
Deutsch
16
Cognitive Engineering Based on Expert Skill: Notes on Success
and Surprises
317
James J. Staszewski
PART IV ALTERNATIVE APPROACHES
17
Representation of
Spatio-Temporal
Resource Constraints
in Network-Based Command and Control
351
Rogier Woltjer, Kip Smith, and
Erik Hollnagel
18
Situated Cognitive Engineering for Complex Task Environments
373
Mark A. Neerincx and Jasper
Lindenberg
Index of Names
391
Subject Index
399
List of Figures
Figure
1.1
Figure
1.2
Figure
2.1
Figure
3.1
Figure
4.1
Figure
4.2
Figure
5.1
Figure
5.2
Figure
6.1
Figure
6.2a
Figure
6.2b
Figure
6.3
Figure
6.4
Figure
6.5
Figure
7.1
Figure
8.1
Figure
10.1
Figure
10.2
Figure
10.3
Figure
10.4
Figure
11.1
Figure
11.2
Figure
11.3
Figrue
11.4
Figure
11.5
Figure
11.6
Figure
12.1
Figure
12.2
Primary and supporting macrocognitive functions
9
A Concept Map about macrocognition
15
An example of an ambiguous figure
32
High-technology cockpit (Boeing
747) 43
The Base Macrocognitive Model of expertise
71
One of the forecaster models, with annotations from Step
4
oftheMMP
73
Percentage of logical inferences drawn to insurance-related and
general knowledge statements by different participant groups
92
An example of frame divergence in dialogue from
a hijacking incident
95
Example of a drill ship
107
Illustration showing a riser connecting the vessel (in this
case a semi-submersible drilling rig) to the sub-sea wellhead
equipment
108
Riser joints resting on sub-sea wellhead equipment
109
Incident command team structure
110
Response and recovery phases
114
Mean rating of effectiveness during first seven days of the
incident management
114
Data/frame model of sensemaking
124
Comprehensive mental model of collaborative decision making
144
Scene in a naval weather office showing interaction of
flight crew and weather forecaster
185
GOES
10
Infrared Satellite Picture of
0000
UTC
18
February
2002 193
Pattern matching process to evaluate model performance
195
Analytic process to deduce error in pressure prediction by
comparing a past prediction to the observation and
correcting future predictions by that amount
196
Clinical reminder functional taxonomy
206
Typical provider workflow
212
A flexible checklist reminder interface
213
Interface clarifying reminder responsibility
215
Sample feedback tool interface
217
Making reminder logic visible to users
217
The experiential learning cycle
224
Single-, double-, and deutero-learning loops
226
viii
Naturalistic Decision Making and Macrocognition
Figure 12.3a
TSR
Pre-briefing guide (front)
234
Figure 12.3b
TSR
Pre-briefing guide (back)
235
Figure
12.4
Dimensions of team health
237
Figure
12.5
Example
TSR
cards
237
Figure
12.6
Controls for using the
TSR
cards, selected on the basis
of the time available and depth of learning required
238
Figure
12.7
Coding of issues raised through team self-review
239
Figure
13.1
Wake vortex separation requirements for departures on
parallel runways
255
Figure
13.2
Specific wind conditions may eliminate impact of wake
vortices on departure aircraft on parallel runway
256
Figure
13.3
Excerpt from
СТА
258
Figure
13.4
The task event recorder screen
260
Figure
13.5
NGOSML model of transferor communication task
261
Figure
13.6
Cognitive model outputs for tower controller
262
Figure
13.7
Methodology for the assessment of air traffic control tower
coordination
266
Figure
13.8
Example of flight strip coordination in an ATCT
268
Figure
13.9
Example of face-to-face coordination between controller
positions in an ATCT
268
Figure
14.1
Complex RPD strategy
278
Figure
14.2
Simulation scenario
282
Figure
14.3
Example ACT-R trace output (Situation familiar)
289
Figure
14.4
Example ACT-R trace output (Situation unfamiliar)
291
Figure
16.1
The AN/PSS-12 remains as US Army standard equipment for
landmine detection
318
Figure
16.2
The PSS-14 used by a US Army combat engineer in a
countermine operation
319
Figure
16.3
Model of the
PSS-
12
expert s detection procedures showing
his basic macroprocesses and their relations
321
Figure
16.4
Spatial patterns inferred from analyses of the
PSS-
12
expert s
successful detection of mines in performance testing
323
Figure
16.5
E-PDRR HSTAMIDS
325
Figure
16.6
Mine targets used in testing
326
Figure
16.7
Model of the HSTAMIDS expert s basic procedures
328
Figure
16.8
HSTAMIDS sensor output pattern for an
M
16
(AP-M)
329
Figure
16.9
HSTAMIDS sensor output pattern for an M14 (AP-LM-S)
329
Figure
16.10
HSTAMIDS sensor output pattern for an
M
15
(AT-M)
330
Figure
16.11
HSTAMIDS sensor output pattern for a TM62P3 (AT-LM)
331
Figure
16.12
Prototypical HSTAMIDS footprints for mine categories
332
Figure
16.13
PSS-Otest
1
results
335
Figure
16.14
HSTAMIDS test
1
and
2
results
336
Figure
16.15
Pre-test and post-test performance as a function of mine type for
non-commissioned officers trained at the Joint Readiness
Training Center, Ft Polk, LA, in August
2001 337
Figure
16.16
Pre-test and post-test detection rates
339
List of Figures
ix
Figure
16.17
Relations between detection and false alarm rates for
CEBES-trained
PSS-
12
operators and HSTAMIDS operators
achieved in the same test environment
341
Figure
17.1
An example of a state space
353
Figure
17.2
FRAM-module description of function aspects and hexagonal
function representation
359
Figure
17.3
An overview of the C3Fire microworld setting used in the study
361
Figure
17.4
Functional modeling
(FRAM)
analysis of a small part of the
task in the C3Fire microworld
363
Figure
17.5
Sample state space for the variables distance to the nearest
fuel-providing unit and fuel range for fire trucks and
water trucks
365
Figure
17.6
Conceptual idea of illustrating behavior and representing
constraints in state spaces
367
Figure
18.1
Design guidance for intelligent user interfaces of naval ships
375
Figure
18.2
Adaptive support interface in the confirm mode:
joint machine-operator procedure execution to handle high
oil-pressure alarm
379
Figure
18.3
Design guidance for intelligent user interfaces of space stations
381
Figure
18.4
SCOPE showing a successful completion of a cooperative
diagnosis process (status bar at top), procedure generation
(left), and reference documentation (right)
384
Figure
18.5
SCOPE showing a joint machine-astronaut procedure
(left) and control panel (right)
385
|
| adam_txt |
Contents
List of Figures
vii
List of Tables
xi
Notes on Contributors
xiii
Foreword
xxv
PARTI ORIENTATION
1
The Macrocognition Framework of Naturalistic Decision Making
3
Jan Maarten
Schraagen, Gary Klein, and Robert R. Hoffman
2
Mind the Gap: A Skeptical View of Macrocognition
27
John M.
Flach
3
Technology and "Naturalistic" Decision Making: Myths and Realities
41
Kathleen L.
Mos
ier
PART II THE HEARTLAND OF MACROCOGNITION
4
Macrocognition, Mental Models, and Cognitive Task
Analysis Methodology
57
Gary Klein and Robert R. Hoffman
5
Investigative Sensemaking in Criminal Contexts
81
Thomas C. Ormerod, Emma C. Barrett, and Paul J. Taylor
6
Learning from Experience: Incident Management Team Leader Training
103
Margaret T. Crichton,
Kristina Lauche,
and Rhona
Flin
7
Making Sense of Human Behavior: Explaining How Police Officers
Assess Danger During Traffic Stops
121
Laura A. Zimmerman
8
Cultural Variations in Mental Models of Collaborative Decision Making
141
Anna P. McHugh, Jennifer L. Smith, and Winston R. Sieck
9
Athletes, Murderers, and a Chinese Farmer: Cultural Perspectives
on Sensemaking
159
Mei-Hua Lin and Helen
Altman
Klein
vi
Naturalistic Decision Making and Macrocognition
10
Strategies in Naturalistic Decision Making: A Cognitive Task Analysis
of Naval Weather Forecasting
183
Susan Joslyn and David W. Jones
11
Supporting Macrocognition in Health Care: Improving
Clinical Reminders
203
Laura
G
Militello, Emily S. Patterson, Jason J. Saleem, Shilo Anders,
and Steven
Asch
12
Macrocognition and Experiential Learning in Surgical Teams
221
Simon Henderson
13
Macrocognition in Systems Engineering: Supporting Changes
in the Air Traffic Control Tower
251
Peter
Moertl,
Craig Bonaceto, Steven
Estes,
and Kevin Burns
PART III MICRO-MACRO RELATIONSHIPS
14
Bridging
Macrocognitive/Microcognitive
Methods: ACT-R
Under Review
277
Claire McAndrew, Adrian Banks, and Julie Gore
15
Reconceptualizing Expertise: Learning from an Expert's Error
301
Stephen
Deutsch
16
Cognitive Engineering Based on Expert Skill: Notes on Success
and Surprises
317
James J. Staszewski
PART IV ALTERNATIVE APPROACHES
17
Representation of
Spatio-Temporal
Resource Constraints
in Network-Based Command and Control
351
Rogier Woltjer, Kip Smith, and
Erik Hollnagel
18
Situated Cognitive Engineering for Complex Task Environments
373
Mark A. Neerincx and Jasper
Lindenberg
Index of Names
391
Subject Index
399
List of Figures
Figure
1.1
Figure
1.2
Figure
2.1
Figure
3.1
Figure
4.1
Figure
4.2
Figure
5.1
Figure
5.2
Figure
6.1
Figure
6.2a
Figure
6.2b
Figure
6.3
Figure
6.4
Figure
6.5
Figure
7.1
Figure
8.1
Figure
10.1
Figure
10.2
Figure
10.3
Figure
10.4
Figure
11.1
Figure
11.2
Figure
11.3
Figrue
11.4
Figure
11.5
Figure
11.6
Figure
12.1
Figure
12.2
Primary and supporting macrocognitive functions
9
A Concept Map about macrocognition
15
An example of an "ambiguous figure"
32
High-technology cockpit (Boeing
747) 43
The "Base Macrocognitive Model" of expertise
71
One of the forecaster models, with annotations from Step
4
oftheMMP
73
Percentage of logical inferences drawn to insurance-related and
general knowledge statements by different participant groups
92
An example of frame divergence in dialogue from
a hijacking incident
95
Example of a drill ship
107
Illustration showing a riser connecting the vessel (in this
case a semi-submersible drilling rig) to the sub-sea wellhead
equipment
108
Riser joints resting on sub-sea wellhead equipment
109
Incident command team structure
110
Response and recovery phases
114
Mean rating of effectiveness during first seven days of the
incident management
114
Data/frame model of sensemaking
124
Comprehensive mental model of collaborative decision making
144
Scene in a naval weather office showing interaction of
flight crew and weather forecaster
185
GOES
10
Infrared Satellite Picture of
0000
UTC
18
February
2002 193
Pattern matching process to evaluate model performance
195
Analytic process to deduce error in pressure prediction by
comparing a past prediction to the observation and
correcting future predictions by that amount
196
Clinical reminder functional taxonomy
206
Typical provider workflow
212
A flexible checklist reminder interface
213
Interface clarifying reminder responsibility
215
Sample feedback tool interface
217
Making reminder logic visible to users
217
The experiential learning cycle
224
Single-, double-, and deutero-learning loops
226
viii
Naturalistic Decision Making and Macrocognition
Figure 12.3a
TSR
Pre-briefing guide (front)
234
Figure 12.3b
TSR
Pre-briefing guide (back)
235
Figure
12.4
Dimensions of team health
237
Figure
12.5
Example
TSR
cards
237
Figure
12.6
Controls for using the
TSR
cards, selected on the basis
of the time available and depth of learning required
238
Figure
12.7
Coding of issues raised through team self-review
239
Figure
13.1
Wake vortex separation requirements for departures on
parallel runways
255
Figure
13.2
Specific wind conditions may eliminate impact of wake
vortices on departure aircraft on parallel runway
256
Figure
13.3
Excerpt from
СТА
258
Figure
13.4
The task event recorder screen
260
Figure
13.5
NGOSML model of transferor communication task
261
Figure
13.6
Cognitive model outputs for tower controller
262
Figure
13.7
Methodology for the assessment of air traffic control tower
coordination
266
Figure
13.8
Example of flight strip coordination in an ATCT
268
Figure
13.9
Example of face-to-face coordination between controller
positions in an ATCT
268
Figure
14.1
Complex RPD strategy
278
Figure
14.2
Simulation scenario
282
Figure
14.3
Example ACT-R trace output (Situation familiar)
289
Figure
14.4
Example ACT-R trace output (Situation unfamiliar)
291
Figure
16.1
The AN/PSS-12 remains as US Army standard equipment for
landmine detection
318
Figure
16.2
The PSS-14 used by a US Army combat engineer in a
countermine operation
319
Figure
16.3
Model of the
PSS-
12
expert's detection procedures showing
his basic macroprocesses and their relations
321
Figure
16.4
Spatial patterns inferred from analyses of the
PSS-
12
expert's
successful detection of mines in performance testing
323
Figure
16.5
E-PDRR HSTAMIDS
325
Figure
16.6
Mine targets used in testing
326
Figure
16.7
Model of the HSTAMIDS expert's basic procedures
328
Figure
16.8
HSTAMIDS sensor output pattern for an
M
16
(AP-M)
329
Figure
16.9
HSTAMIDS sensor output pattern for an M14 (AP-LM-S)
329
Figure
16.10
HSTAMIDS sensor output pattern for an
M
15
(AT-M)
330
Figure
16.11
HSTAMIDS sensor output pattern for a TM62P3 (AT-LM)
331
Figure
16.12
Prototypical HSTAMIDS footprints for mine categories
332
Figure
16.13
PSS-Otest
1
results
335
Figure
16.14
HSTAMIDS test
1
and
2
results
336
Figure
16.15
Pre-test and post-test performance as a function of mine type for
non-commissioned officers trained at the Joint Readiness
Training Center, Ft Polk, LA, in August
2001 337
Figure
16.16
Pre-test and post-test detection rates
339
List of Figures
ix
Figure
16.17
Relations between detection and false alarm rates for
CEBES-trained
PSS-
12
operators and HSTAMIDS operators
achieved in the same test environment
341
Figure
17.1
An example of a state space
353
Figure
17.2
FRAM-module description of function aspects and hexagonal
function representation
359
Figure
17.3
An overview of the C3Fire microworld setting used in the study
361
Figure
17.4
Functional modeling
(FRAM)
analysis of a small part of the
task in the C3Fire microworld
363
Figure
17.5
Sample state space for the variables "distance to the nearest
fuel-providing unit" and "fuel range" for fire trucks and
water trucks
365
Figure
17.6
Conceptual idea of illustrating behavior and representing
constraints in state spaces
367
Figure
18.1
Design guidance for intelligent user interfaces of naval ships
375
Figure
18.2
Adaptive support interface in the confirm mode:
"joint machine-operator" procedure execution to handle high
oil-pressure alarm
379
Figure
18.3
Design guidance for intelligent user interfaces of space stations
381
Figure
18.4
SCOPE showing a successful completion of a cooperative
diagnosis process (status bar at top), procedure generation
(left), and reference documentation (right)
384
Figure
18.5
SCOPE showing a "joint machine-astronaut" procedure
(left) and control panel (right)
385 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author_GND | (DE-588)1191785831 |
| building | Verbundindex |
| bvnumber | BV023333587 |
| callnumber-first | B - Philosophy, Psychology, Religion |
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| callnumber-search | BF448 |
| callnumber-sort | BF 3448 |
| callnumber-subject | BF - Psychology |
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| ctrlnum | (OCoLC)173683580 (DE-599)BVBBV023333587 |
| dewey-full | 153.8/3 |
| dewey-hundreds | 100 - Philosophy & psychology |
| dewey-ones | 153 - Conscious mental processes & intelligence |
| dewey-raw | 153.8/3 |
| dewey-search | 153.8/3 |
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| discipline | Psychologie |
| discipline_str_mv | Psychologie |
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| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV023333587 |
| illustrated | Illustrated |
| index_date | 2024-07-02T20:58:37Z |
| indexdate | 2024-07-09T21:16:07Z |
| institution | BVB |
| isbn | 9780754670209 |
| language | English |
| lccn | 2007039710 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016517482 |
| oclc_num | 173683580 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-12 |
| owner_facet | DE-473 DE-BY-UBG DE-12 |
| physical | XXVI, 411 S. Ill., graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Ashgate |
| record_format | marc |
| spelling | Naturalistic decision making and macrocognition ed. by Jan Maarten Schraagen ... Aldershot [u.a.] Ashgate 2008 XXVI, 411 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Decision making Cognition Task analysis Entscheidung (DE-588)4014904-3 gnd rswk-swf Kognition (DE-588)4031630-0 gnd rswk-swf Problemlösen (DE-588)4076358-4 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Entscheidung (DE-588)4014904-3 s Kognition (DE-588)4031630-0 s Problemlösen (DE-588)4076358-4 s DE-604 Schraagen, Jan Maarten 1960- Sonstige (DE-588)1191785831 oth Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016517482&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Naturalistic decision making and macrocognition Decision making Cognition Task analysis Entscheidung (DE-588)4014904-3 gnd Kognition (DE-588)4031630-0 gnd Problemlösen (DE-588)4076358-4 gnd |
| subject_GND | (DE-588)4014904-3 (DE-588)4031630-0 (DE-588)4076358-4 (DE-588)4143413-4 |
| title | Naturalistic decision making and macrocognition |
| title_auth | Naturalistic decision making and macrocognition |
| title_exact_search | Naturalistic decision making and macrocognition |
| title_exact_search_txtP | Naturalistic decision making and macrocognition |
| title_full | Naturalistic decision making and macrocognition ed. by Jan Maarten Schraagen ... |
| title_fullStr | Naturalistic decision making and macrocognition ed. by Jan Maarten Schraagen ... |
| title_full_unstemmed | Naturalistic decision making and macrocognition ed. by Jan Maarten Schraagen ... |
| title_short | Naturalistic decision making and macrocognition |
| title_sort | naturalistic decision making and macrocognition |
| topic | Decision making Cognition Task analysis Entscheidung (DE-588)4014904-3 gnd Kognition (DE-588)4031630-0 gnd Problemlösen (DE-588)4076358-4 gnd |
| topic_facet | Decision making Cognition Task analysis Entscheidung Kognition Problemlösen Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016517482&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT schraagenjanmaarten naturalisticdecisionmakingandmacrocognition |