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ONR Principle Investigators:

Dr. Joe DiVita, Code 244209 joseph.divita@navy.mil

Dr Glenn Osga, Code 2441 glenn.osga@navy.mil

Dr. David Kieras - University of MichiganDr. Tom Santoro - NSMRL Groton CTMr. Rob Morris, Code 244209 rob.morris@navy.mil

Contributors:Dr. Hung T. Nguyen- New Mexico State University

Modeling of Human-Computer Interaction:Application to Command & Control

Presented at Systems Design Technical Group MeetingHFS Annual Conference, Denver Colorado, Oct. 2003

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Based upon Stepwise models as defined in: Psychology of Human-Computer Interaction, Card, Moran, and Newell (1983).

Goals: What Must be Accomplished Operators: Elementary Perceptual, Motor,

or Cognitive Acts.

Methods: Step by Step Procedure for a Goal

Selection Rules: Basis for Choosing Methods

GOMS Components

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GLEAN: GOMS Language Evaluation and Analysis Tool

Simulated Interaction

Devices Auditory Input

Declarative and Procedural Knowledge in Long Term memory

Visual Input

Cognitive

Processor

GOMS Language

Interpreter

Working

Memory

Auditory

Processor

Visual

Processor

Vocal Motor

Processor

Manual Motor

Processor

Task Environment

Kieras, D.E., Wood, S.D., Abotel, K., & Hornof, A. (1995). GLEAN: A Computer-BasedTool for Rapid GOMS Model Usability Evaluation of User Interface Designs. InProceeding of UIST, 1995, Pittsburg, PA, USA. November 14-17, 1995. New York:ACM. pp. 91-100.

Model-based Evaluation David Kieras University of Michiganto appear in J. Jacko & A. Sears (Eds), Human-Computer Interaction Handbook, Lawrence Erlbaum Associates, in press

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• Define the Goals:• How are they accomplished ?• How might they be accomplished?• What are the alternatives?

2. Write the Methods in GOMSL,

3. Build the HCI and Task Environment in C++,

4. Run the Scenario(s) & Review Results.

1. Task Analysis

Using Models for Design Trade-Off Studies

Analysis Procedure:

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Display Design Components

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Task Task Manager Manager Task Task QueueQueue

Task Task Manager Manager Task Task QueueQueue

Systems StatusCommunicationsCommunicationsCommunicationsCommunications

Task Manager & Status DisplayTask Manager & Status Display

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Strike Plan Overview Task

Progress

Process Visualization - Tactical Tomahawk

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Avg Time Avg Time Method for Goal Frequency FrequencySPOKEN SYNTHETIC SPOKEN SYNTHETIC

28.445 20.418 Respond_to New_Air 76 7622.248 16.662 Update_Air Trk 168 242 7.355 7.344 Review Air_ID 244 318 2.208 2.727 Review Track_profile 124 160 4.598 5.402 Conduct Threat_Assessment 124 160 14.228 14.285 Request Escort 9 1015.150 12.675 Request Visual ID 2 814.790 3.491 Issue Query 10 1916.075 4.644 Issue Warning 12 1814.545 3.500 New_Track_Verbal_Rpt 76 7614.427 3.536 Update_Track_Verbal_Rpt 74 105 2.015 2.094 Hook Track 244 318

Comparison Results

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AWC operator selects task

Task arrives on TM display

AWC operator sends report

Text to Speech completed

AWC receives acknowledgment

Mean Waiting time in the queue

Team 1 data = 51.2 s

GOMSL Model = 55.2s

Mean Service Time

Team 1 data = 6.7 s

GOMSL Model = 10.3 s

Mean time = 10.1 s

GOMSL Model = 5.5 s

GOMSL Model = 52.26 GOMSL Model = 9.43 GOMSL Model = 9.10

Actual Team ResultsGOMSL Model Results GOMSL Model with fast working memory

Example: New Track Report Task Flow

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AWC

Operator

IQC1

Operator

AIC

Operator

Tasks performed - Output Flow

Tasks performed - Output flow

Network Queueing Model of Team 1 Task Flow. Level I* & II*,

ordered to send.

VID

Level I & II’s

Tasks Entering: New track Report Update track Report Level 1Query Level II Warn VID Cover Engage Illuminate

Tasks Entering: New track Report Update track Report Level 1Query Level II Warn VID Cover Engage Illuminate

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AWC

IQC1

AIC

1

2

3

1

incoming

tasks

General Open Network Queueing Model

Tasks passed between operators

2 incoming

tasks

3 incoming

tasks

Load to each node:

i=

i

i

i =

i +

j pji

i = the effective arrival rate to node i.

pji = probability that a task, after receiving

service by node j, proceeds to node i. Ave #, N, of tasks in

the whole system:

i - N=

i /( i)

Ave time, T, of tasks

in the system:

i - 1 T=

i /( i)

i

Network Stats:

i= service time of task

ñ) = i) i

ni (1-P(

Probability of a particular state (n1, n2, n3) tasks:

i

= rate of incoming tasks

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Queue Time for New Track Reports

0

10

20

30

40

50

60

70

80

90

1 2

Teams

Secon

ds

Team 2 takes 36% longer to complete New Track Reports

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Modeling Plans

• Expand Models• Basic models constructed for Air Defense mission and Land Attack

with Tomahawk.

• Models based upon future HCI designs being incorporated into Tomahawk.

• Expand individual models into tactical team models.

• Design Feedback• Provide design feedback on best features to improve performance.

• Team Design• Compare team work allocation, flow, process with various team

configurations for future systems.