A Comparison of Map vs . Text Directions for a Handheld Device in a Campus Setting: A Pilot Study
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Transcript of A Comparison of Map vs . Text Directions for a Handheld Device in a Campus Setting: A Pilot Study
A Comparison of Map vs. Text Directions for a Handheld
Device in a Campus Setting: A Pilot Study
Liz AtwaterDepartment of Psychology
George Mason University
Jason BurkeInstitute for Systems
Research
University of Maryland
Andrea KirkDepartment of Computer
Science
University of Maryland
December 2001
Which one is more effective? – Less time, less errors
Does route complexity have an effect? Use by pedestrians instead of drivers
– Lack of landmarks– No street names, etc.
Map vs. Text Directions
Context-aware, location-aware– Location awareness via GPS, RF, IR, etc.
Provides information depending on:– User profile– Device profile– Location– Context
Useful in many domains– Tourism– Commerce
Rover
Williams studies (1999) – pilots finding nearest airport using maps or text– Maps are faster and more accurate– ERF tasks had better results with track-up– WRF tasks had better results with north-up
Aretz,1991 – ERF vs. WRF– Ego-centered frame track-up– World-centered frame north-up
Butz, 2001 – landmarks at key decision points
Background Research
Experiment – Hypotheses
Hypotheses:– Null: There is no statistical difference between
completion time, consultation time and number of errors between text and map directions, regardless of route complexity.
– H1: Users will complete the tasks faster using map
directions.
– H2:Users will make fewer errors using map
directions.
– H3: Users will need less consultation time using text
directions.
– H4: Completion time will rise with increasing route
complexity.
IVs & Treatments– Direction type: map vs. text– Route complexity: low, medium, high
• Low: 3 decision points, 893 ft • Medium: 5 decision points, 897 ft• High: 7 decision points, 883 ft
DVs– Completion time– Consulting time– Errors
Experiment – Variables
Subjects– 7 male, 5 female– Undergrad & grad UMCP students
Other materials– Pre & post-task questionnaires– VZ-2
Experiment – Materials
Navigate 3 routes using directions Within-subjects for routes Between-subjects for direction type 2 stopwatches Route permutations:
123 132
213 231
312 321
Experiment – Tasks
Screen Shots
Text Implementation Map Implementation
Main effect for route: significant Main effect for direction: ns Interaction effect: ns
Completion Time
0
50
100
150
200
250
300
350
400
High Medium Low
Route complexity
Tim
e (
s)
Map
Text
Results – Completion Time
Main effect for route: significant Main effect for direction: ns Interaction effect: ns
Device Consulting Time
-20
0
20
40
60
80
100
120
High Medium Low
Route Complexity
Tim
e (
s)
Map
Text
Results – Consultation Time
Main effect for route: significant Main effect for direction: ns Interaction effect: ns
Number of Errors
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
High Medium Low
Route Complexity
Nu
mb
er
of
err
ors
Map
Text
Results – Errors
Observations
Learning seemed to have a significant effect on the results
Most errors occurred at non-dead ends
People are different– Huge variance in user performance in
both map and text implementations– Difficulty judging distances in text version– Rotate map for track-up bearings– Looking ahead caused problems
Conclusions
Need many more subjects
Text directions are difficult to describe in college campus environment
Feedback from “real” context-aware equipment could improve performance
Track-up display for map could decrease orientation time
Hybrid to accommodate variations in user cognitive strengths