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EVALUATING THE EFFECTIVENESS OF
ORIENTATION INDICATORS WITH AN
AWARENESS OF INDIVIDUAL DIFFERENCES
by
Tina Renee Ziemek
A dissertation submitted to the faculty ofThe University of Utah
in partial fulfillment of the requirements for the degree of
Doctor of Philosophyin
Computer Science
School of Computing
The University of Utah
June 2010
Copyright c© Tina Renee Ziemek 2010
All Rights Reserved
THE UNIVERSITY OF UTAH GRADUATE SCHOOL
SUPERVISORY COMMITTEE APPROVAL
of a dissertation submitted by
Tina Renee Ziemek
This dissertation has been read by each member of the following supervisory committeeand by majority vote has been found to be satisfactory.
Co-Chair: William B. Thompson
Co-Chair: Sarah H. Creem-Regehr
Christopher R. Johnson
Thomas Fletcher
Mary Hegarty
THE UNIVERSITY OF UTAH GRADUATE SCHOOL
FINAL READING APPROVAL
To the Graduate Council of the University of Utah:
I have read the dissertation of Tina Renee Ziemek in its final formand have found that (1) its format, citations, and bibliographic style are consistentand acceptable; (2) its illustrative materials including figures, tables, and charts are inplace; and (3) the final manuscript is satisfactory to the Supervisory Committee andis ready for submission to The Graduate School.
Date William B. ThompsonCo-Chair, Supervisory Committee
Date Sarah H. Creem-RegehrCo-Chair, Supervisory Committee
Approved for the Major Department
Martin BerzinsChair/Dean
Approved for the Graduate Council
David S. ChapmanDean of The Graduate School
ABSTRACT
Understanding how users perceive 3D geometric models can provide a basis for
creating more effective tools for visualization in applications such as CAD or 3D
medical imaging. This dissertation examines how orientation indicators affect users’
accuracy in perceiving the shape of a 3D object shown as multiple views. Multiple
views force users to infer the orientation of an object and recognize corresponding
features between distinct vantage points. These are difficult tasks, and not all users
are able to carry them out accurately. A cognitive experimental paradigm is used to
evaluate the effectiveness of four types of orientation indicators on a person’s ability to
compare views of objects presented in different orientations. The orientation indicators
implemented were colocated, non-colocated, static, and dynamic. The study accounts
for additional factors including task, object complexity, axis of rotation, and users’
individual differences in spatial abilities. Results show that a colocated orientation
indicator helps users the most in comparing multiple views, and that the effect is
correlated with a person’s spatial ability. Besides the main finding, this dissertation
helps demonstrate the application of a particular experimental paradigm and analysis
as well as the importance of considering individual differences when designing interface
aids.
“Oh, the places you’ll go! There is fun to be done! There are points to be scored.
There are games to be won.” - Dr. Seuss (Oh, the Places You’ll Go!)
CONTENTS
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
CHAPTERS
1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Three-dimensional visualizations of geometric objects . . . . . . . . . . . . . . 51.1.1 Increasing user accuracy with orientation indicators . . . . . . . . . . . 5
1.1.1.1 Different types of orientation indicators . . . . . . . . . . . . . . . . . 51.1.2 Variables that may influence the effectiveness of a visualization . . 6
1.2 Evaluation via a cognitive paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71.2.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71.2.2 Mental rotation paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.4 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2. BACKGROUND AND RELATED WORK . . . . . . . . . . . . . . . . . . . . . 11
2.1 3D visualizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.1.1 Overview of visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.1.1 Scientific visualization applications . . . . . . . . . . . . . . . . . . . . 122.1.2 Using external representations to facilitate internal cognition . . . . 122.1.3 Are visualizations effective for all users? . . . . . . . . . . . . . . . . . . . . . 132.1.4 Spatial reference frames . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1.4.1 Object-based and viewer-based reference frames . . . . . . . . . . 152.1.4.2 Reference frames in virtual environments . . . . . . . . . . . . . . . . 16
2.2 Increasing effectiveness of visualizations through cognitive support . . . . 172.2.1 Tasks where orientation indicators could benefit users . . . . . . . . . . 18
2.2.1.1 Mechanical CAD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182.2.1.2 Medical visualizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3 Variables that may affect 3D visualizations . . . . . . . . . . . . . . . . . . . . . . 222.3.1 Task, stimuli, axis of rotation, and level of interactivity may affect
task-performance with a 3D visualization . . . . . . . . . . . . . . . . . . . . 222.3.2 Individual differences may affect task-performance with a 3D vi-
sualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3. EXPERIMENT DESIGN FOR EVALUATING ORIENTATION
INDICATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.1 Orientation indicators evaluated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273.1.1 Colocated or non-colocated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273.1.2 Static or dynamic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2 Stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293.3 Subjects’ spatial abilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293.4 Experimental design and procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4.1 Choose-two-of-four task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323.4.2 Same/different task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343.4.3 Subjects and research setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4. EVALUATING ORIENTATION INDICATOR EXPERIMENTS . 42
4.1 Results and discussion of choose-two-of-four experiments . . . . . . . . . . . . 424.1.1 Accuracy score . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.1.1.1 Colocated vs. non-colocated indicators . . . . . . . . . . . . . . . . . 424.1.1.2 Individual differences in spatial ability . . . . . . . . . . . . . . . . . . 434.1.1.3 Class of objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454.1.1.4 Axis of rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.2 Results and discussion of same/different experiments . . . . . . . . . . . . . . . 484.2.1 Accuracy score . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4.2.1.1 Colocated vs. non-colocated indicators . . . . . . . . . . . . . . . . . 484.2.1.2 Individual differences in spatial ability . . . . . . . . . . . . . . . . . . 494.2.1.3 Class of objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524.2.1.4 Axis of rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
4.2.2 Response time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 544.2.2.1 Response time and spatial ability . . . . . . . . . . . . . . . . . . . . . . 56
4.3 Comparison and contrast of the accuracy results of the two tasks . . . . . 58
5. DISCUSSION AND CONTRIBUTIONS . . . . . . . . . . . . . . . . . . . . . . . 60
5.1 Summary of this research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 605.1.1 Type of orientation indicator and spatial ability . . . . . . . . . . . . . . 615.1.2 Dynamic vs. static orientation indicators . . . . . . . . . . . . . . . . . . . . 615.1.3 Factors that influence task-performance with a colocated static
indicator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625.1.3.1 Time pressure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625.1.3.2 Axis of rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625.1.3.3 Spatial ability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635.1.3.4 Ceiling and floor effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.1.4 Object complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 645.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.2.1 Object space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 655.2.2 Room space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665.2.3 Environment space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675.2.4 Evaluation of cognitive support . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685.3.1 Theoretical contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695.3.2 Practical contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
vii
APPENDIX: EXPERIMENTAL INSTRUCTIONS . . . . . . . . . . . . . . . . . 73
REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
viii
LIST OF FIGURES
1.1 The term visualization can describe internal visualizations that occurin the mind, or external visualizations such as those used in scientificvisualization and computer-aided design. . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Visualization of heart and lungs shown as multiple views. The user mustestablish a correspondence between the different points of view. Imagescourtesy and copyright of Scientific Computing Institute, University ofUtah. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Non-colocated static orientation indicator on left, colocated static orien-tation indicator on right. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Theories and methodologies from cognitive science can be used to system-atically evaluate 3D computer applications. Controlled experimentationalso allows us to account for individual differences of users such as spatialability, profession, gender, and age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1 Some users may think relevant information can be seen from a backprojection even if it can only be viewed from a side projection. Imagecourtesy and copyright of Johnson et al. [54]. . . . . . . . . . . . . . . . . . . . . . . 14
2.2 Viewcube orientation indicator implemented in Autodesk products. TheViewcube displays the orientation of the 3D scene in each view. . . . . . . . 19
2.3 Colocated orientation indicator similar to the one implemented by Stullet al. [1]. Stull and colleagues found that the orientation indicator helpedstudents learn anatomy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.4 Computer-aided design is often done using multiple views of a 3D model.Non-colocated orientation indicators are used to indicate object’s orien-tation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.5 Visualization application 3D Slicer is used for surgical planning, image-guided intervention, and clinical studies. Image courtesy and copyrightof David Gering. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.6 Students view 3D structures shown at various orientations to learn anatomy.Images courtesy and copyright of Primal Pictures Ltd. . . . . . . . . . . . . . . . 22
3.1 Example trials: Choose which two of the four objects on the right matchthe target object on the left. Non-colocated orientation indicator on top,colocated orientation indicator below. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.2 Ten stimuli used in experiment. Mechanical parts on top, anatomicalstructures below. Each stimulus shown in 0◦ orientation. . . . . . . . . . . . . . 30
3.3 Examples of paper-and-pencil tests used to measure individual’s spatialability. Paper folding task shown on top, Vandenberg and Kuse [2] mentalrotation task shown on bottom. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.4 Stimuli used in practice trials. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.5 Four axes of rotation were assessed. Clockwise from top left: horizontalaxis, oblique axis one, oblique axis two, vertical axis. All objects areshown rotated 45◦ from initial position. . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.6 Example choose-two-of-four trials with mechanical stimuli rotated aboutoblique axis two. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.7 Example same/different trials: Are the objects the same object shownin different orientations, or are they different objects? Subjects werepresented with one type of aid, all subjects had trials where no aid waspresent. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.8 Example trials. These two objects are different objects. . . . . . . . . . . . . . 38
3.9 Research setting where subjects took experiment. . . . . . . . . . . . . . . . . . . . 41
4.1 Mean score on Experiment 2, with and without colocated static orienta-tion indicator with vertical and horizontal rotations, by spatial ability. . . 46
4.2 Mean score on Experiment 3, with and without colocated static orienta-tion indicator with oblique one rotation, by spatial ability. . . . . . . . . . . . . 46
4.3 Mean score on same/different task with and without non-colocated staticorientation indicator by spatial ability. . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.4 Mean score on same/different task with and without colocated staticorientation indicator by spatial ability. . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.5 Mean score on same/different task with and without colocated staticorientation indicator by axis of rotation. . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.6 Mean response time on same/different task with and without non-colocatedstatic orientation indicator by spatial ability. . . . . . . . . . . . . . . . . . . . . . . 55
4.7 Mean response time on same/different task with and without colocatedstatic orientation indicator. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.1 Three sizes of spaces to analyze in future research. Application areasstated, as well as additional variables to evaluate. . . . . . . . . . . . . . . . . . . 66
x
LIST OF TABLES
3.1 Number of subjects in each experiment by spatial ability and gender.Female (F), Male (M), Total (T). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.1 Accuracy results for the choose-two-of-four experiments. 40 subjects perexperiment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.2 Accuracy results for the same/different experiments. Rotation alwaysabout horizontal axis or vertical axis. 40 subjects per experiment. . . . . . . 50
4.3 Response time (RT) results in seconds for Experiments 4 and 5. . . . . . . 57
ACKNOWLEDGEMENTS
I came to graduate school because I didn’t know any other avenue that would allow
me to study perception. I leave graduate school knowing more about perception, but
also more about myself.
I would like to thank my advisors, Dr. William Thompson and Dr. Sarah Creem-
Regehr, for their guidance. I am grateful to Bill for teaching me to account for the
details, to have concrete arguments for my ideas, and to fly fish. I am grateful to Sarah
for helping me with the details, opening up the world of cognitive science to me, and
showing me ways to measure people’s perception of the world.
I also thank my family. I give gratitude to Sandi, Norbert, Todd and family, Troy
and family, Terry and family, and Tracy and family for their love and light. I especially
thank my father for working extra hard so I could attend school.
I am also grateful for the friendships I made in Utah. I especially thank Scott Alfeld,
Jason Beck, J. Dean Brederson, Jeremy Archuleta, Daniel Murphy, Justin Polchlopek,
Dr. Scott Kuhl, Ben Kunz, Patrick Kelley, J. Dylan Lacewell, Subodh Sharma, Manu
Awasthi, Amlan Ghosh, and Mina Jeong. I also would like to thank my yogi friends,
break dancing crew, and snowboard posse.
I am also grateful for having such wonderful colleagues. I thank my committee
members, Dr. Mary Hegarty, Dr. Chris Johnson, and Dr. Tom Fletcher. I also thank
Dr. Drew Davidson, Dr. Pete Shirley, and my SIGGRAPH friends. I give special
thanks to Dr. Alyn Rockwood for introducing me to the world of computer graphics,
art, and interactive techniques.
Lastly, I am thankful for the support I received while attending the University of
Utah. The School of Computing has wonderful administrative support; thank you to
Karen Feinauer and Jessica Johnson. Special thank you to Dr. Martin Berzins and Dr.
Erin Parker for supporting outreach efforts, and allowing me to be a part of them. I am
also grateful for financial support provided by the National Science Foundation through
grants 0745131 and 0914488. I also thank Google for awarding me a scholarship and
encouraging underrepresented groups to participate in computer science.
CHAPTER 1
INTRODUCTION
Until recently, the term visualization referred to the construction of visual or mental
models that are represented in a person’s mind. In computer science the term has now
adopted a second meaning that refers to external graphical representations of data or
concepts. Such visualizations are external artifacts and can aid in performing a task by
offloading some of the mental processing associated with the task [3, 4]. Visualizations
and three-dimensional (3D) models are now being used in engineering, architecture,
science, and medicine to comprehend large amounts of data, observe the attributes
of data, enable patterns to become apparent, and form hypotheses [4, 5, 6]. Medical
education has already made a dramatic shift toward using 3D visualizations and digital
representations of anatomy in academic curricula. Since visualizations are created to
depict data and communicate information, it is critical that people accurately perceive
the computer generated 3D geometric representations. See Figure 1.1 for example
visualizations.
However, extracting important, relevant information in 3D applications such as
computer aided design (CAD) and visualization tools is a difficult task for some users,
and the literature shows that not all users may benefit from the advantages of a 3D
environment [7, 5]. This present work focuses on the problem of accurately perceiving
visualizations that are shown in multiple, simultaneous views. Multiple views are both
common and useful [8]. Previous research has evaluated multiple views for information
visualization [9, 8], whereas the present research specifically addresses multiple views
of 3D geometric entities.
Multiple views allow users to simultaneously view an object from different view-
points and allow features to be seen that would otherwise be occluded from view [10].
However, multiple views force users to establish a correspondence between perspectives,
keep track of an object’s features between views, and potentially recognize changes
in features across vantage points. For some users, especially users with low spatial
abilities, these tasks may be difficult or not carried out accurately, and they may
2
Figure 1.1. The term visualization can describe internal visualizations that occur inthe mind, or external visualizations such as those used in scientific visualization andcomputer-aided design.
distract from the primary task for which the 3D application is intended. The goal of
this work is to increase a user’s ability to compare and comprehend multiple views of a
3D visualization. See Figure 1.2 for an example of a visualization displayed as multiple
views.
We achieve this goal by evaluating the effectiveness of a selection of orientation
indicators, which are in-scene graphical aids that illustrate rotational changes of an
object. Prior research has raised awareness of the difficulties users may have when
working in a 3D virtual environment [11, 10, 12], and orientation indicators are one
solution to help users maintain orientation in a virtual space [7, 1]. Orientation
indicators may provide users with cognitive support, which can be defined as assistance
from an artifact to help a user to think and solve problems [13], and free cognitive
resources that modeling and visualization applications may unnecessarily impose on
Figure 1.2. Visualization of heart and lungs shown as multiple views. The user mustestablish a correspondence between the different points of view. Images courtesy andcopyright of Scientific Computing Institute, University of Utah.
3
users. We specifically examine the effectiveness of orientation indicators that can be
colocated with the target object or non-colocated (displaced) from the object, and
those that are static or dynamic. See Figure 1.3 for non-colocated static and colocated
static orientation indicators.
To date, there is no guarantee that users will benefit from even the most well inten-
tioned and technically developed tools [14]. Thus, this work presents an evaluation of
orientation indicators with an established cognitive experimental paradigm. Perceiving
shape and spatial relationships are fundamental aspects of visualization tasks [15] and
appropriate visual cues are necessary to accurately perceive spatial relationships in
computer generated images [16]. Decades of work in spatial cognition has demon-
strated that visuospatial thinking and mental representation can be systematically
evaluated [17, 18, 19, 20].
We evaluate users’ abilities to perceive the orientation of 3D objects with the
mental rotation paradigm [19, 2]. Mental rotation tasks are most commonly used
to evaluate the mechanism underlying spatial reasoning and the internal construct
of mental imagery, however many researchers have had success in using the mental
rotation paradigm to evaluate the perception of computer graphics— e.g. [21, 22, 23,
24, 25, 26, 16]. This methodology allows us to use objective, controlled experimentation
to evaluate the influence of an orientation indicator on the perceived orientation of a
3D object. This paradigm also allows us to test several factors that may influence the
effectiveness of an orientation indicator.
The present work seeks to answer two questions about users’ task-performance when
viewing visualizations:
1. Can orientation indicators increase a user’s task-performance with
a 3D visualization presented as multiple static views? There are sev-
eral variables that may effect the influence of orientation indicators on object-
orientation judgments of 3D visualizations. In the work presented here, we vary
the task, complexity of an object, axis of rotation, and presence of dynamic
information to determine the effectiveness of an orientation indicator. In partic-
ular, we use two mental rotation tasks, the choose-two-of-four task [2] and the
same/different task [19], to assess users’ performance. The choose-two-of-four
task measures accuracy while the same/different task measures both accuracy
and speed. These tasks allow us to understand 3D applications where the user’s
4
Figure 1.3. Non-colocated static orientation indicator on left, colocated static orien-tation indicator on right.
accuracy is key and 3D applications where the user’s performance may be influ-
ence by time pressure.
2. Do individual differences in visuospatial abilities influence the effective-
ness of an orientation indicator? Individual differences between users may
effect the extent to which he or she benefits from an orientation indicator. Users
with high spatial ability may benefit more or less from an orientation indicator
than users with low spatial ability.
This dissertation seeks to test several scientific hypotheses regarding a user’s task-
performance with visualizations shown as multiple static views. First, we hypothesize
that orientation indicators will help users perform more accurately on two tasks which
assess a user’s ability to maintain the orientation of 3D virtual objects shown on a
desktop display. We believe that different types of orientation indicators will have
different effects on a user’s accuracy; aids that are colocated with an object may be more
effective than aids that are not colocated with an object. Furthermore, the complexity
of the 3D model and the axis of rotation may impact the effectiveness of an orientation
indicator. Users may benefit more from an aid when the 3D object is abstract or when
the axis of rotation is an arbitrary oblique axis. Finally, we hypothesize that a user’s
spatial ability will impact whether he or she benefits from an orientation indicator.
Users with high spatial ability may benefit more from an orientation indicator than
users with low spatial ability. Conversely, users with low spatial ability may benefit
more from an orientation indicator than users with high spatial ability.
5
1.1 Three-dimensional visualizations of geometricobjects
Although there are several types of visualizations, such as information visualiza-
tion and flow visualization, the present work examines scientific visualizations of 3D
geometric entities. In these visualizations the user is viewing 3D geometric shapes
rendered from numerical data and computer generated models.
1.1.1 Increasing user accuracy with orientation indicators
Orientation indicators have the potential to increase users’ accuracy in perceiving
the 3D structure of an object presented as multiple views. These in-scene graphical
aids illustrate rotational changes between views and may compensate for ambiguous in-
formation about an object’s orientation. For instance, without an orientation indicator
users may incorrectly assume which way the object is positioned, they may think they
are looking at the “top” of an object when they are looking at the “bottom”. With
an indicator the user will not have to rely solely on the object to infer the object’s
orientation in space.
It has been shown that individuals can benefit from additional information about
an object’s orientation in a mental rotation task. Hinton et al. [27] found that partic-
ipants benefit from advanced information of an object’s orientation before the object
was presented. Specifically, participants would see an arrow that would indicate the
orientation of an object prior to its appearance. Pani et al. [28] found that participants
were more accurate in rotating an object when it was in a wooden box than an object
that was presented by itself. However, males tended to be able to use the information
the box provided more efficiently than females. The present work builds on these
previous findings by examining the relative effectiveness of different type of indicators
for orientation in an abstract virtual space.
1.1.1.1 Different types of orientation indicators
Various orientation indicators have been implemented in computer aided design
(CAD) and medical imaging software applications. The ViewCube is one orientation
indicator that is implemented in Autodesk, Inc. 3D modeling packages [7]. The
ViewCube is an iconic in-scene aid; the ViewCube’s position in space reflects the 3D
model’s position in space. The user can also click on the “front” face of the cube to
view the front of the 3D model. Prior to the ViewCube, Autodesk, Inc. implemented
other aids to facilitate orientation including the user coordinate system icon and the
6
ViewCompass. The user coordinate system icon displayed the orientation of the major
coordinate system axes, x, y, and z [29]. The ViewCompass provided direct viewpoint
selection [7]. Orientation indicators have been implemented in medial imaging software
in the forms of bounding boxes, virtual human figures, and aids that depict the left,
right, anterior, and posterior sides of an object [30]. To our knowledge these orientation
indicators have not been quantitatively assessed.
We analyze orientation indicators that are either colocated or non-colocated with
the object, and either static or dynamic. This implementation led to four different
types of orientation indicators: colocated static, colocated dynamic, non-colocated
static, and non-colocated dynamic. In all instances the object stimuli were static.
As shown in Figure 1.3, the non-colocated orientation indicator is placed above the
3D object and the colocated orientation indicator shares a center point with the 3D
object. An orientation indicator that is placed apart and not attached to the object
may cause users difficulty because they have to transfer information from the aid to the
object. It may be that a user would benefit more from an orientation indicator which
is colocated with the object since the user is not required to transform information
from the aid to the object. The static aids show the orientation of each 3D object;
the dynamic aids show the path of rotation between two objects.1 The motion from
the dynamic orientation indicator may affect task-performance. A dynamic orientation
indicator may facilitate cognitive processes better than a static orientation indicator.
1.1.2 Variables that may influence the effectiveness of a visualization
There are a variety of possible factors that influence task-performance with a 3D
application. Visualizations could be more or less effective depending on the task being
performed, and the complexity of the rendered 3D model. The present work analyzes
users’ task-performance with two versions of a cognitive paradigm and two classes of
objects that vary in complexity.
A user’s spatial ability may also influence the effectiveness of a visualization. Kozhevnikova
et al. [31, 32, 33] suggest that different people might have different preferences for
how visual imagery is represented. We predict that a subject’s performance with an
orientation indicator will correlate to his or her visuospatial abilities. Visuospatial
abilities are necessary for many common activities and have also been linked to job
1Examples of the dynamic indicator can be viewed at http://www.cs.utah.edu/∼tziemek/dissertation
7
performance in occupations such as engineering, aircraft piloting, and surgery [17]. For
these reasons the present work takes visuospatial abilities into account.
Lastly, the level of interactivity may affect how the visualization is used. There
are various types or levels of interactivity with a 3D visualization. Some 3D tools do
not permit the user to interact with the 3D visualization, they only present informa-
tion. Three-dimensional visualizations can be static (i.e., traditional print and maps),
animated (dynamic motion), or interactive (responds directly to user input).
This dissertation analyzes the utility and ease of use of static visualizations. We
evaluate static visualizations in order to utilize an objective evaluation criteria, and sug-
gest attributes of visualizations that may cause difficulty for users of static, animated,
and interactive visualizations. The present work provides a foundation for future work
which could examine non-interactive dynamic and interactive visualizations. Further-
more, as outlined in Section 2.2.1, there are a variety of applications which present
visualizations as static images. In addition, some visualizations may not be able to be
presented as dynamic or interactive because of the complexity of the underlying data.
Also, it has been suggested that interactivity is not essential for a visualization to be
effective (e.g., Keehner et al. [6]). We do take into account the effectiveness of dynamic
orientation indicators, although the underlying visualization is static.
1.2 Evaluation via a cognitive paradigm
1.2.1 Motivation
Computer applications display information visually in order to communicate infor-
mation to users. However, computer users may fail to extract relevant information from
a display. Despite the designers efforts to make an intuitive and effective interface, users
often do not see a vast amount of information, and this problem is worsened because
users are not aware that they are not seeing all of the information the designer has
made available [34].
It may be that designers think users can process more visual information than they
are actually capable. Research on the visual information a user attends to within an
interface can be used as motivation to evaluate scientific visualizations. It has been
found that users often do not see useful information within an interface, that a user
does not always attend to all of the locations on the screen that contain important
information, and the user wrongly assumes that he or she has an accurate representation
of information that is presented [34]. We cannot assume a user will process and benefit
8
from all of the visual cues within a visualization. Furthermore, it may be that the user
will misinterpret the information shown within a visualization.
For these reasons, it is imperative that we evaluate a user’s experience in a 3D
environment with controlled experimentation. Methodologies from cognitive psychol-
ogy can be used to carry out this experimentation, and the results can be used to
inform the design of 3D computer applications. By objectively measuring a user’s
task-performance we can reduce biases and complexities that would otherwise be in-
troduced if 3D applications were used to measure performance. See Figure 1.4 for a
the types of 3D computer applications we can evaluate using ideas, methodologies,
and theories from cognitive science. Furthermore, evaluating a user’s perception of
information with controlled investigation allows for the analysis of several factors that
may impact a user’s experience with a visualization in a systematic way. It also allows
for testing a user’s own individual differences such as gender, spatial ability, age, and
profession to determine whether these variables influence how a user perceives a 3D
application. For these reasons we have chosen to utilize a class of response measures in
which the perceptual psychology community has much experience, extending this prior
research in ways that are useful in understanding 3D applications.
1.2.2 Mental rotation paradigm
We evaluate the effectiveness of orientation indicators with the mental rotation
paradigm. The tasks we use are similar to the Vandenberg and Kuse [2] and Shepard
Figure 1.4. Theories and methodologies from cognitive science can be used tosystematically evaluate 3D computer applications. Controlled experimentation alsoallows us to account for individual differences of users such as spatial ability, profession,gender, and age.
9
and Metzler [19] mental rotation studies. The established methodology and body of
research on mental rotation provides a basis for its use to evaluate the influence of an
orientation indicator on the perceived orientation of a 3D object.
Through a series of experiments we assess how orientation indicators can help users
understand the orientation of a 3D object in an abstract virtual space. We measure
accuracy and response time to determine the effect the orientation indicator has on
user performance in a 3D desktop environment. The mental rotation paradigm also
allows us to examine variables which may affect the utility of an orientation indicator,
including the difficulty of the task (accuracy or time pressure), complexity of the 3D
objects (simple or complex), a user’s spatial ability (high or low spatial ability), and
the presence of dynamic information (static or dynamic).
1.3 Contributions
There are two main goals of this dissertation. The first is to demonstrate a system-
atic evaluation of visualizations. The second is to demonstrate the benefits of cognitive
support within visualizations. Using a cognitive experimental paradigm, we illustrate
the effectiveness of orientation indicators on visualizations presented as multiple static
views. We found that orientation indicators that are colocated with the 3D object are
more effective than orientation indicators that are non-colocated with the 3D object.
Furthermore, the presence of dynamic information does not increase the utility of an
orientation indicator. Finally, a person’s individual differences in spatial ability are
likely to effect the usefulness of an orientation indicator.
These results can inform the design of 3D applications and are important for four
particular reasons. First, if an individual has difficulty with a 3D application, we show
that a colocated orientation indicator can be used to help alleviate problems. Second,
we found that a non-colocated orientation indicator has less impact in increasing
task-performance than a colocated orientation indicator. Therefore, this research can
help engineers make objective decisions in regards to the type of orientation indicator
to include in 3D software packages. Third, this work highlights the importance of
evaluations based on controlled experimentation using theories and methodologies from
cognitive psychology. Finally, we demonstrate the need to take into account individual
differences and find ways in which all users can benefit from 3D applications.
We intend to show that 3D visualizations can be improved with controlled in-
vestigation of how users perceive the information in a visualization. By identifying
10
the difficulties users may have when working with a visualization and the benefits of
additional information, engineers can implement methods to make 3D visualizations
more effective. The implications from this work extend to 3D CAD and medical
visualization applications, as these applications could be made more accessible to a
broad population of users through the use of in-scene cognitive aids.
At the same time, this work can inform our understanding of the processing of
complex imagery and assess whether human performance can be improved through the
use of a cognitive aid. It has been shown that there is a wide range of people’s spatial
abilities not only in the general population, but also within specialized populations such
as practicing surgeons [35, 17]. Differences in task performance between high spatial
and low spatial users may be interpreted as a “superiority” of high spatial learners.
An alternative interpretation is that the two groups rely on different aspects of
spatial processing to solve the same tasks, leading to apparent behavioral differences.
By understanding these differences we can provide low spatial users with cognitive
aids that allow them to solve a task using a different method than a high spatial
user would. By identifying users’ difficulties with 3D navigation and the benefits
of additional information we can make 3D environments more effective. We aim to
illustrate methods in which 3D visualizations could be made more usable. With hope
this work will encourage additional research on other ways in which 3D visualizations
can be improved.
1.4 Organization
Chapter 2 provides a comprehensive summary of related previous work, variables
that may influence the effectiveness of a visualization, and how these variables may
influence the effectiveness of an orientation indicator. Chapter 3 describes the 3D object
stimuli, methodology, and experiment procedures which were used to measure subjects’
task-performance. Chapter 4 presents the results of the mental rotation experiments
in the present research. Finally, Chapter 5 discusses the mental rotation results as well
as the practical and theoretical contributions of this work.
CHAPTER 2
BACKGROUND AND RELATED WORK
This chapter introduces previous work that evaluated the effectiveness of 3D visu-
alizations. First, I begin with an overview of 3D visualizations and why visualizations
may not be effective for all users. A discussion on frames of reference is included.
Second, I discuss how users might gain information from an in-scene cognitive aid
and research that has implemented techniques to support effective navigation in 3D
tools. Specific applications that can benefit from the present work are given. Third,
I describe variables that could affect users’ experience and task-performance with 3D
visualizations. In particular, I describe how a user’s spatial ability may affect how he
or she benefits from a visualization.
2.1 3D visualizations
Advances in computer graphics such as sophisticated rendering methods and hard-
ware have led to the ability to create complex 3D graphics and visualizations.
2.1.1 Overview of visualization
Visualization includes the areas of computer graphics, image processing, high per-
formance computing, information visualization and scientific visualization. The present
work focuses on scientific visualizations, which can be defined as 3D graphical repre-
sentations which are used to gain an understanding and insight to data [4]. Scientific
visualization does not include presentation graphics, which communicate information
and results in ways that are easily understood (such as a bar chart).
The motivation behind scientific visualization is to allow users to comprehend data
in ways that are not feasible with the raw data. There are four stages of visualizations:
the collection and storage of the data, preprocessing of data to transform it into a form
we can understand, display hardware and graphics algorithms produce an image, and
the human cognitive system perceives the image [4].
12
This dissertation focuses on evaluating how accurately the human perceiver com-
prehends the visualization. There are three stages of the perceptual processing of a
visualization. First the viewer extracts the low-level properties of the scene such as
features, orientation, color, texture, and movement patterns. Second, the viewer uses
contours, regions of the same color, texture, and motion to recognize patterns. Lastly,
the viewer carries out a sequential goal-directed processing [4]. For instance, the viewer
uses visual search strategies to extract information he or she is seeking. The present
work focuses on the low-level property of object orientation.
2.1.1.1 Scientific visualization applications
Many disciplines are using visualizations to analyze data. These areas include:
engineering, fluid dynamics, electronic design, medical imaging, geospatial information
sciences, military, meteorology, and geology. Applications with 3D visualizations give
users the experience of viewing real 3D objects, and enbable both expert and non-expert
users to visually explore data [36]. Visualizations provide data analysis without the
need to formally train users since shapes can be readily perceived [4]. Some practi-
tioners use visualizations to reveal correlations in the data over space and time (see
[37, 36, 4]). Visualizations can also be used in clinical studies (see [38, 39]) and in
pedagogy (see [40, 41, 42]).
2.1.2 Using external representations to facilitate internal cognition
External representations such as visualizations are a visual aid to cognition [43].
A useful framework for understanding how external visualizations facilitate internal
cognition is distributed cognition [5]. Distributed cognition is the theory that certain
tasks require the processing of information that is distributed across both the internal
mind and an external representation [44]. In order to evaluate a distributed task, we
must consider both the internal processing and the external representation because
each facilitates cognition.
Distributed cognition can help us better understand human-computer interaction
by putting the focus on what users do in virtual environments and how they perform ac-
tivities in them [45]. Because the attributes of external representations influence users’
cognition, designers of visualizations should consider the user’s moment-to-moment
actions in a virtual space [5]. Effective interfaces will facilitate cognition by helping
the user decide which action to do next [46].
13
The theories of embodied cognition assume that people will minimize internal cog-
nitive processes by utilizing perceptual-motor processes [47]. For example, instead of
imagining an object from a specific viewpoint, users will instead manually rotate the
object to that perspective as a means of simplifying the problem-solving task. Kirsh
and Maglio [48] found that players of the game Tetris, in which falling block shapes
must be rotated and horizontally translated to fit as compactly as possible with already
fallen blocks, would use external rotations and transformations to uncover information
that was difficult to compute mentally. Furthermore, people may use the environment
to solve problems in situations that demand fast responses because the time to mentally
compute processes would be costly [47].
These theories predict that scientific visualizations will aid cognition by offloading
inefficient internal processes onto more efficient perceptual-motor processes, such as
externally rotating an object and observing the changes [5, 49, 50, 46]. However,
distributed cognition is typically examined using simpler tasks than tasks typically
performed by practitioners using scientific visualizations. Therefore, the present work
can contribute to the body of literature on distributed cognition and also benefit from
this theoretical framework.
2.1.3 Are visualizations effective for all users?
Despite the enthusiasm regarding the use of 3D digital representations, research
on how users perceive 3D models and the information users gain from a 3D tool is
to date limited and inconsistent [3, 5]. Even though designers create visualizations
to be aesthetically appealing and intuitive, some users may not understand how to
effectively use them. Some research has shown the presence of a 3D visualization is
beneficial [51, 5], whereas other research shows 3D visualizations do not provide extra
information [52, 3].
Knowing whether a user will benefit from a visualization is a troubling problem
for designers of 3D visualizations. The information being displayed in a visualization
may be very beneficial to users, but users may not be able to comprehend all of the
information shown because the visualization is too complex. For instance, previous
research has indicated that when individuals from a broad population were assigned a
shape-related task that entailed interaction with a 3D visualization, failure correlated
with the inability to find an appropriate orientation from which to view the data [5].
In this research the visualization contained useful and relevant data, however the user
14
did not attend to this information. It may be that users have trouble finding important
information within a visualization, or that they think they have discovered all of the
important information within a visualization when they have not.
It is possible that some users cannot access information from a visualization because
they get disoriented when working in an abstract 3D virtual environment. The concepts
and tools needed to maintain orientation in a 3D scene may be difficult to learn and
some users have even rejected using 3D tools [11, 7]. Kheener, Khooshabeh, and
Hegarty [5] found that not all users were able to find the most “informative view”,
i.e., the view that gives key information within a visualization. Similarly, Velez, Silver,
and Tremaine [53] reported that some individuals thought the most “informative view”
was always the back projection of the object even if it was a side or bottom view. See
Figure 2.1 for example orientations in which visualizations are presented.
It is also possible that some users have difficulty orienting themselves in 3D desktop
environments because many of the cues commonly used to maintain a frame of reference
in the real world are absent in these virtual spaces. There is often no sense of an “up”
direction in an abstract data space, and this can be confusing [55]. In the real world we
can orient ourselves via cues from our bodies, the environment including the horizon,
lighting, and objects in the environment. In 3D virtual environments objects are often
presented in a vacuum of space and users may become easily disoriented with camera
perspectives that are from unfamiliar points of view.
Previous research indicates that imagining an object’s rotation is difficult when only
the object’s initial position is given and no other information is provided [56, 57]. Ware
and Arsenault [55] found that frames of reference can impact the task-performance
Figure 2.1. Some users may think relevant information can be seen from a backprojection even if it can only be viewed from a side projection. Image courtesy andcopyright of Johnson et al. [54].
15
of making two virtual objects parallel (i.e., rotating one object until it matches the
orientation of a target object). Much of the research conducted on perceived direction
has been done in the context of space research to help us understand how people can
best orient themselves in a gravity free environment [55, 58]. Howard et al. [59] found
that the presence of familiar objects with a known normal orientation, such as a chair,
can influence which direction is perceived as up.
2.1.4 Spatial reference frames
Environments that allow for users or objects to move through space are often defined
in terms of a spatial coordinate system. This coordinate system can be defined as
three axes of translation (e.g., X, Y, Z coordinates in 3D space) and three axes of
orientation (yaw, pitch, roll) [60, 61]. The position and orientation of objects in an
environment can be specified by that systems’ frame of reference. For some tasks,
the user may need to use and transform multiple frames of reference. For example, a
construction worker operating a tractor shovel may need to transform the orientation
of the shovel (an angular coordinate system) to the location of the tractor on the
ground (a two-dimensional (2D) Euclidian system). Transformations of visuospatial
mental images depend on multiple spatial reference frames and are important for many
reasoning problems, including navigation, understanding of the structure of data and
the making and using of tools [20, 60].
2.1.4.1 Object-based and viewer-based reference frames
It is necessary to use a frame of reference to adopt a specific viewpoint of an object
or scene [27]. There are two visuospatial transformations that are often dissociated:
object-based transformations in which individual objects are updated relative to the
object’s spatial representations, and viewer-based transformations in which one’s per-
sonal perspective is updated [57, 62]. When someone performs an imagined rotation or
translation using an object-based reference frame the update is done using the object’s
intrinsic coordinate frame. For example, a car may be represented as having an up-down
axis, a front-back axis, and a left-right axis, while an object such as a water bottle may
be represented as only having a major (up-down) axis running from the top to the
base. People appear to rapidly and automatically assign a major axis and hence a
top to objects [20] and such axes play an important role in how we perceive their
orientations space [63, 64, 56].
16
Studies have shown that relationships are updated differently in viewer-based trans-
formations than in object-based transformations and that some tasks may be more eas-
ily solved using one transformation over the other [65, 66, 55, 62, 67, 61]. Object-based
reference frames can help a person define the relationships between various parts of an
object and can also be used to locate an object relative to another object (i.e., “on
the stove”). Zacks et al [20] hypothesized that for a same-different task where subjects
make judgments regarding whether two pictures were identical or mirror images (a
comparison task) subjects would use an object-based transformation to rotate the
reference frame. Research has also found that individuals are able to quickly rotate
objects around the vertical axis perpendicular to the line of sight, suggesting they
are maintaining a “gravitational vertical” or object-based frame of reference [64, 68].
Conversely, Zacks et al. [20] hypothesized that for left-right tasks where subjects make
judgments regarding which arm (left or right) of a pictured figure was extended (a
classification task) subjects would use a perspective transformation.
Individual differences may also impact the frame of reference a person maintains
since difference coordinate systems can lead to different strategies to solve a visuospatial
task. It has been suggested that the ability to manipulate an imagined object with
an object-based transformation and the ability to reorient the imagined self with a
viewer-based transformation are separate abilities [69]. Research has indicated that
individuals may prefer to use either viewer-based or object-based representations in
learning a large-scale environment [70, 71]. Furthermore, high spatial individuals may
be more flexible in the coordinate systems that they are able to maintain. For example,
in solving a mental rotation task, high spatial ability subjects were able to use a frame of
reference that included a nonstandard axis of the world but low spatial ability subjects
were not able to use such an axis [72].
2.1.4.2 Reference frames in virtual environments
One frame of reference particularly relevant to virtual spaces is the display frame.
The display frame, such as the computer screen, is used to define the orientation and
movement of information on a display. This frame of reference might be analogous
to the environmental frame of reference used in the real world. The environment
reference frame is based on the orthogonal directions and planes from floors, walls,
and ceilings [28]. Kozhevnikova et al. [68] found that individuals might maintain
different frames of reference in a virtual environment depending on the display. When
17
performing a mental rotation task, subjects were likely to use a display frame of
reference when viewing objects on a 2D monitor, and a viewer-based frame of reference
when viewing objects in a 3D immersive display [68].
A distinct difference between 3D desktop environments and the real world is that
in the real world objects rarely rotate in space in front of us, instead we often change
our location and move our head to get a different viewpoint [73]. In 3D desktop envi-
ronments objects can be arbitrarily rotated in space, and the user cannot discriminate
whether the view of the object changed because of the motion of the object, or a change
in the observer’s position in space. A user may interpret all changes to the view of
an object as a change due the object moving since the cues used to maintain body
orientation in the real world are absent. One goal for the designer of a visualization
is to ensure the interface does not create unnecessary transformations of information
from one spatial reference frame to another. These transformations are cognitively
demanding and could increase time, error rate, and mental workload [60].
While a viewer-based graphical aid is worth inquiry in future research, we will
focus on an object-based graphical aid. Current industry software packages that
have orientation indicators have implemented indicators which provide an object-based
reference frame (see [11]). It is likely that many 3D visualizations require users to rely
on object-based transformations. When using a visualization users may be prone to
interpreting changes to the view of an object as a change resulting from object-based
movement since the viewer-based cues used in the real world are absent. Furthermore,
many visualizations require users to do comparison tasks, which rely on the user
attending to an object-based frame of reference.
2.2 Increasing effectiveness of visualizations throughcognitive support
Research has shown that techniques can be implemented to address the challenges
users may have when using 3D tools [74, 10, 75, 76, 77, 11, 7, 1]. Brooks et al. [74]
developed haptic displays; Tory and Swindells [75] assessed how multiple viewpoints
aided a user; Feibush et al. [77] designed a viewer for navigating terrain; Firzmaurice
et al. [11] augmented existing navigation tools; and Khan et al. [7] implemented an
orientation indicator called the Viewcube (see Figure 2.2). However, Khan et al. [7]
did not compare task-performance between conditions when the indicator was present
and when it was not present. Stull et al. [1] found that orientation references helped
18
individuals learn anatomy from a 3D visualization. See Figure 2.3 for an indicator
similar to the one implemented by Stull et al. [1]. Orientation indicators have been
implemented in medical imaging software in the forms of bounding boxes, virtual
human figures, and aids that depict the left, right, anterior, and posterior sides of
an object [30, 78]. To our knowledge these orientation indicators have not been
quantitatively assessed.
2.2.1 Tasks where orientation indicators could benefit users
2.2.1.1 Mechanical CAD
An important trend in mechanical CAD is the move towards 3D solid modeling
systems. Prior to the advent of CAD software, mechanical designs of individual parts
and objects were typically specified by drafting on paper a set of orthographic views
(sometimes called multi-view drawings), representing the parallel projection of the
object from various viewing directions. Viewing directions were typically separated
by 90◦ and aligned in some natural way with the object. Research has suggested that
orthographic views provide sufficient information for people to create a full 3D mental
representation of an object [79]. Modern mechanical software automates this drafting
process, and the electronic representation can now be a full 3D description of the object
shape (as shown in Figure 2.4).
These applications allow users to create, manipulate, and view 3D geometry and
scenes on traditional two-dimensional displays [7]. Viewpoints that are difficult to
achieve in the real world, such as a bird’s eye view, are easily attainable in 3D appli-
cations. Users can view objects from any angle and orient the part in any position.
However, controlling the virtual viewpoint and understanding the position of the virtual
camera in relation to an object is a challenging task for users new to virtual 3D
environments [7]. Another consequence is that designers may have to maintain an
association between object features in multiple views. This problem may become even
more complicated when designers are working with complex objects. Multiple views
are used in CAD and modeling software such as Autodesk’s AutoCAD, Maya, and 3D
StudioMax [80]. See Figure 2.4 for one example of how Autodesk implements multiple
views and orientation indicators.
19
Figure 2.2. Viewcube orientation indicator implemented in Autodesk products. TheViewcube displays the orientation of the 3D scene in each view.
Figure 2.3. Colocated orientation indicator similar to the one implemented by Stullet al. [1]. Stull and colleagues found that the orientation indicator helped studentslearn anatomy.
20
Figure 2.4. Computer-aided design is often done using multiple views of a 3D model.Non-colocated orientation indicators are used to indicate object’s orientation.
2.2.1.2 Medical visualizations
Certain subsets of the medical community have adopted 3D visualizations into
clinical practice [38, 39]. Several medical imaging and visualization software packages
allow for multiple views of data. Multiple views are used in visualization software such
as OsiriX, 3D Slicer, Anatomy Browser, Seg3D, and ImageVis3D [81, 82, 83, 84, 85].
These tools can be used for education, image-guided therapy and also pre-surgical
planning and reference [40, 39, 86, 87, 88]. For instance, the application 3D Slicer is
used in image-guided surgery and allows the surgeon to view 3D surface models of key
anatomical and functional structures [78] from preoperative data in the interventional
context. Figure 2.5 shows one way a volume can be oriented in 3D Slicer [38].
Medical education has already made a dramatic shift towards using 3D visualiza-
tions and digital representations of anatomy in academic curricula [89, 42]. Educa-
tors are recommending digital representations for the study of anatomical structure,
function, and spatial relationships [41]. Medical professionals rely on a detailed un-
derstanding of spatial structures in the human body [90], but medical students have
difficulties achieving this level of understanding [41].
It is believed that realistic 3D models will enhance a student’s learning experience
[52]. Dynamic visualizations may provide additional depth cues and convey 3D shape to
21
Figure 2.5. Visualization application 3D Slicer is used for surgical planning, im-age-guided intervention, and clinical studies. Image courtesy and copyright of DavidGering.
22
users better than traditional static 2D representations. The motor commands used in
interactive visualizations may also benefit users because of the correspondence between
their commands and the resulting changes in the object’s orientation [5]. There have
been major initiatives such as the Visible Human Project to acquire spatial data from
human organs and create 3D models which are used for teaching and learning gross
anatomy [42]. Figure 2.6 shows images from a digital learning DVD produced by Primal
Pictures, Ltd [91]. In this application users are shown multiple views of 3D models to
learn anatomy.
Spatial cognition is critical for users to be able to interpret medical images [90].
It has been shown that there is a wide range of individual spatial abilities not only
in the general population, but also within specialized populations such as practicing
surgeons [17, 35]. Prior research has shown that spatial understanding of 3D models
by low spatial individuals can be improved to near that of high spatial individuals with
the use of cognitive aids [1]. Researchers have encouraged the assessment of students’
spatial understanding of 3D anatomical structures [92, 5, 52].
2.3 Variables that may affect 3D visualizations
Published results on the effectiveness of 3D applications are inconsistent. There are
a variety of possible factors that influence task-performance with a 3D application.
2.3.1 Task, stimuli, axis of rotation, and level of interactivity mayaffect task-performance with a 3D visualization
It may be easier to comprehend information within certain visualizations than
others, and this variation may be influenced by four factors. The difficulty of the
task, complexity of the 3D model, axis which the object is rotated about and the level
Figure 2.6. Students view 3D structures shown at various orientations to learnanatomy. Images courtesy and copyright of Primal Pictures Ltd.
23
of interactivity given to a user may affect task-performance with visualizations. For
example, recalling a view of a familiar object may involve different cognitive processes
compared to a task where the user has to find a specific feature of a complex object.
Recalling a feature of a known object may be an easier task for a user than finding a
particular piece of a complex object.
Furthermore, it may be difficult for users to benefit from a visualization when they
cannot make informed decisions. For instance, even if users know they need to find
a specific feature, they may not know the path to take that will lead them to that
feature, and they may not be able to maintain an internal representation of all of the
locations where they have already looked for the feature. In short, it might be difficult
for users to benefit from a visualization when the visualization is causing them to make
decisions to which they do not know the answers.
The axis of rotation may also impact task-performance with a visualization. The
literate shows that people are quickest and most accurate in determining the position
of objects when the objects are oriented around one of their own natural axes [63]. In
particular, people tend to be most efficient at rotating objects when the axis of rotation
is vertical in the environment [63, 18].
In contrast, comparing objects with oblique or diagonal orientations is much more
difficult and people are more prone to make errors [63, 56, 93, 94]. Furthermore, the
angular disparity at which an object has been rotated will likely increase the time
necessary to make an orientation judgment [19]. Larger angles of rotation will lead to
longer response times. This increase in time may interpreted as increased time needed
to rotate an object, or could be the result of an increase in difficulty (see Rock et al. [95]
for discussion).
Lastly, 3D applications either static or dynamic, and some permit the user to inter-
act with the 3D model. While some studies have found that interactivity helps users
achieve faster recognition times of objects, other studies have found that individuals
with interactive control do not perform better than individuals with an animated 3D
model which they cannot control [5, 96]. Furthermore, it has been found that an
animated diagram did not lead individuals to have a greater understanding of a dynamic
process compared to a static diagram [97].
The quality of the information a user gains depends not only on whether they are
permitted to interact with a visualization, but how they interact with it [6]. Moreover,
there have been instances where individuals using an interactive 3D model performed
24
worse than individuals who were not given this control [6]. There are limited principles
on how to design effective dynamic interactive visualizations for instructional use [98].
Several factors may affect the claim that interactive 3D desktop environments make
task-performance better (see Hegarty [99] for discussion).
2.3.2 Individual differences may affect task-performance with a 3Dvisualization
Khan et al. [7] stated that navigation in a 3D environment may especially burden
users who have little experience with 3D interaction and visualization. Individual
differences in spatial ability may also affect how a user benefits from a 3D applica-
tion [5]. The term spatial abilities refers to a broad range of skills involving the mental
representation and manipulation of information about geometric entities. Research has
shown there is a natural variation between people in their spatial abilities; individual
differences have been found in a variety of tests of visuospatial abilities [17].
There are three possibilities for how spatial ability could affect the usefulness of a
3D tool for a person [99]. First is the “ability-as-enhancer” hypothesis, which states
that high spatial ability is a necessary prerequisite to using a 3D tool and only high
spatial ability learners will benefit from 3D models because they have enough cognitive
capacity to use them. Second, the “ability-as-compensator” hypothesis indicates 3D
models could be particularly effective for low spatial learners; if low spatial learners
have trouble constructing their own internal model they might benefit if an external
model was given to them. The third hypothesis is that 3D models will benefit everyone
equally [3, 5].
Studies have shown evidence for the “ability-as-enhancer hypothesis”. Findings
show that high spatial ability is correlated with accuracy with a 3D visualization [53].
A three-dimensional tool improved learning for high spatial ability individuals [51], but
put low spatial ability individuals at a significant disadvantage [52]. Huk [3] found that
only students with high spatial abilities benefited from 3D models. Low spatial abilities
learners also have had more difficulty than high spatial abilities learners with complex
geometric objects. Velez et al. [53] reported that low spatial ability participants could
only solve simple geometric objects such as cubes and cones. There is limited research
on whether dynamic spatial abilities, the abilities that are needed to reason about
moving stimuli [17], are required for a user to make accurate inferences with animated
3D models. Research has shown that low spatial ability individuals had more difficulties
25
extracting information from a two-dimensional dynamic animation than high spatial
ability individuals [100].
It is important to examine ways in which all users can benefit from 3D applications.
Three-dimensional graphics are being used in more fields and there is a growing popu-
lation of people who need to learn 3D navigation to perform their job [11]. Moreover,
it has been found that features added to make 3D tools more accessible are not only
popular with novice users but experienced 3D users as well [11]. Several researchers
have argued for the importance of considering individual differences in the design of
human computer interaction systems (e.g., [101, 102, 103, 104, 105, 106, 107, 108, 109]).
One of the few investigations of gender differences in 3D user interfaces concluded
that the purported poor performance of women compared to men in navigating virtual
environments disappeared if users were provided with a wide field of view display [110].
Hubona et al. [111, 112] examined performance on several spatial tasks relevant to
visual interfaces and found a male advantage on mental rotation of abstract objects,
the use of motion-related cues, and on a task that involved moving and positioning
objects. Females were found to be better at estimating relative size. Notably, this work
was conducted on professional engineers and computer scientists, who may already be
experienced at such operations. Work to date on designing other forms of software with
an awareness of the effects of individual differences is also limited (see [113, 114, 115]).
CHAPTER 3
EXPERIMENT DESIGN FOR
EVALUATING ORIENTATION
INDICATORS
This chapter provides a complete discussion of the experimental methodology used
in this work. The experiments were designed to answer four specific questions about a
user’s ability to maintain an understanding of a 3D model when viewed from distinct
orientations.
The first and most important goal of the experiments was to quantitatively measure
the effects of four types of orientation indicators on users’ ability to make object-
orientation judgments of 3D objects. To achieve this goal, we used an experimental
paradigm that is very established in the psychology community. Each subject was
presented with one type of orientation indicator, and they completed the task with
the presence of the indicator and in its absence. Our hypothesis is that the graphical
aids will improve a user’s ability to make same/different judgments on 3D objects
shown in different orientations. We predict that colocated orientation indicators will
help individuals more than non-colocated orientation indicators in determining the
orientation of an object in space.
Second, we considered the possibility that objects of varying complexity may effect
task performance and the effectiveness of an orientation indicator. We used two classes
of 3D objects; mechanical parts that were comprised of distinct pieces, and anatomical
parts that were comprised of abstract parts. We predict that anatomical objects will
be more difficult for individuals than mechanical objects, and the orientation indicators
will help more with anatomical objects than mechanical objects.
Third, we examined the influence of individual differences in visuospatial abilities on
the effectiveness of the orientation indicator. Since spatial ability has been a predictor
in prior research regarding the effectiveness of 3D visualizations, it may be correlated
with the effectiveness of an orientation indicator. A user may prefer one type of aid
27
over another depending on his or her spatial ability. It may be that low spatial learners
need different cues to aid with orientation than high spatial learners. If high spatial
learners outperform low spatial learners when using 3D tools an orientation indicator
may help close the performance gap between groups.
Finally, we used two tasks to measure user performance. The two tasks give
converging evidence on the effectiveness of an orientation indicator. These tasks vary
in difficulty and time pressure. They also provide different quantitative information
for data analysis.
3.1 Orientation indicators evaluated
Orientation indicators were either colocated or non-colocated with the object, and
either static or dynamic. This implementation led to four different types of ori-
entation indicators: colocated static, colocated dynamic, non-colocated static, and
non-colocated dynamic. In all instances the object stimuli were static.
We used an orientation indicator that could be used as either a colocated indicator or
non-colocated indicator in order to maintain a controlled experiment and not introduce
biases. We based the look of the orientation indicator off of the coordinate system icons
often used in CAD programs, but felt additional colored markers would help users who
are not experienced with 3D CAD and visualization systems. Subjects were not given
instruction on how the aid could help to solve the tasks; they were only told the aid
rotated the same amount and direction as the object. In practice, orientation indicators
in the style of bounding boxes, glyphs, or aids labeled anterior, posterior, superior and
inferior could be used; our goal however, was to evaluate differences between colocated
and non-colocated indicators.
3.1.1 Colocated or non-colocated
The non-colocated orientation indicators were placed above the stimuli. The colo-
cated orientation indicators were placed such that the object and the aid shared a
center point. See Figure 3.1 for examples. Each indicator was shown rotated in the
same axis and amount as the object stimuli. Each indicator rotated as an object-based
transformation, in other words it rotated in the same coordinate frame as the object
shown. It could be that an orientation indicator that is placed apart and not attached
to the object leads the user to solve the task first for the aid, and then transform the
information about rotation to the object. In this step the user may have difficulty
28
recovering the information from the aid and translating it to the object. The colocated
indicator was a larger scaled version of the non-colocated indicator. The indicator had
six markers, each had a unique color.
3.1.2 Static or dynamic
The dynamic indicators showed the path of rotation between two objects as opposed
to the two endpoints of rotation. Cues from motion are very prominent visual cues.
Structure from motion is the theory that an object’s shape and spatial relationships can
be recovered from motion through cues such as optical flow [116, 117]. For instance,
when an object is rotating the viewer can use features of the object along with cues
from the object’s direction and velocity to track the movement of the object over time.
The dynamic indicator could help by providing cues to the user as to how the structure
of the object would look from one point in time to the next. This information may
help the user construct an accurate representation of an object’s shape.
Additionally, motion may assist a user in mentally rotating an object because it is
hypothesized that there is a relationship between the representation/processing of an
object in mental rotation and the representation/processing of an object that is seen
visually rotating [118]. A person may find it easier to determine whether two objects
are the same object if they are given a visual rotation. This visual rotation may provide
them with information such that they do not have to create a path of rotation between
the two objects on their own. Instead, they can use the path of rotation given to them
to determine whether the two objects are the same object.
The dynamic aid started in the orientation of one object, rotated into the position
of the second object, then rotated back into the original position.1 Subjects were able
to watch this path of rotation three times before the indicator stopped in the position
of the object on the left. The speed of the indicator was held constant. To account for
varying degrees of rotation between two objects, the distance the indicator translated
was a function of the degree of rotation. The indicator traveled longer distances for
larger degrees of rotation. The minimum amount of time of dynamic movement was 2
seconds; the maximum amount of time of dynamic movement was 10 seconds.
1Examples of the dynamic indicator can be viewed at http://www.cs.utah.edu/∼tziemek/dissertation
29
3.2 Stimuli
We used two classes of objects since object complexity has shown to affect task-
performance with 3D visualizations. One class of objects was mechanical parts that
were constructed of distinct pieces, and the other class of objects was anatomical
structures that represent blood vessels, an aneurysm, or organism that is composed
of abstract parts. These two classes of objects stem from the 3D object perception
experiment conducted by Cole et al. [119]. The authors of this experiment used models
that people could easily infer shape, did not have a lot of self-occlusion, were not too
familiar to subjects, and were somewhat simple without much fine scale detail [119].
We believe this criteria is well suited for both the mental rotation paradigm and also
the application areas of 3D CAD software and medical visualizations. See Figure 3.2
for the ten 3D object stimuli. All stimuli were limited to an object manipulation
space in which the viewer could see the entire silhouette of the object. The anatomical
structures were assembled using digital embryos [120]. All models were modified and
rendered with Autodesk’s Maya 3D software version 8.5. The type of lighting used
were area lights with Blinn shading. The image size of each choose-two-of-four trial
was 1530 x 448 pixels. The image size of each same/different trial was 608×448 pixels.
3.3 Subjects’ spatial abilities
We predict that a subject’s performance with an orientation indicator will correlate
to his or her visuospatial abilities. In each of these experiments, subjects will be
given paper-and-pencil spatial abilities tests. Subjects with high spatial visualization
abilities may use the orientation indicator more or less than subjects with low spatial
visualization abilities. Although a high spatial visualization ability subject may be
able to do the task well without the orientation indicator and not necessarily benefit
from the static aid, the dynamic aid may facilitate performance because the motion
can confirm confirm his or her own mental rotation of the object. Conversely, a subject
with low spatial visualization abilities may benefit equally, or more from the static aid
compared to the dynamic aid. The low spatial visualization subject may not benefit
from a dynamic aid if he or she does not understand the motion of the aid. In other
words, the path between two objects may not correspond to how the subject thought
the rotation occurred since there are an infinite amount of ways to rotate two objects
to be in congruence with one another.
Subjects’ spatial visualization ability was measured using two paper-and-pencil
30
Figure 3.1. Example trials: Choose which two of the four objects on the right matchthe target object on the left. Non-colocated orientation indicator on top, colocatedorientation indicator below.
Figure 3.2. Ten stimuli used in experiment. Mechanical parts on top, anatomicalstructures below. Each stimulus shown in 0◦ orientation.
31
tests: the Paper Folding Test [121] and the Mental Rotation Test [2]. In the paper
folding test, each question illustrated a piece of paper being folded, a hole being punched
in it, and the subject was to identify what the piece of paper would look like when it was
unfolded. See Figure 3.3 for example paper folding task. The subject was to correctly
identify the answer from a series of five possible answers. In the mental rotation test,
each question had a target object and four consecutive objects. The subject was to
correctly identify which two of the four objects matched the target object but were
shown in different orientations. All objects were cubes pieced together to form block
like objects. See Figure 3.3 for example mental rotation task.
Each test had 20 questions and consisted of two parts that were timed for 3 minutes
each. The paper folding test was scored by awarding one point for every correct answer
minus a fraction of a point for every incorrect answer. The mental rotation test was
scored by awarding two points for every correct answer minus two points for every
incorrect answer. Standardized scores (z-scores) were calculated for the two paper-
and-pencil tests, and these were combined to create an aggregate measure for each
subject (280 total: 151 females, 129 males). Subjects were classified as high spatial
ability or low spatial ability based on a natural break in the distribution of scores that
was very close to the median.
Figure 3.3. Examples of paper-and-pencil tests used to measure individual’s spatialability. Paper folding task shown on top, Vandenberg and Kuse [2] mental rotationtask shown on bottom.
32
3.4 Experimental design and procedure
To assess whether orientation indicators affect subjects’ performance we created
a series of seven computer based experiments. In each experiment we varied object
type, axis of rotation, and the presence/absence of an orientation indicator. We
tested whether performance would change as a function of the orientation indicator
and whether effects would differ depending on spatial ability.
Two different designs were used, both of which have been employed extensively in
past studies of mental rotation. The first of these, which we refer to below as the choose-
two-of-four task, presented a target object and four possible matches. Participants had
to pick the two correct matches from the four possibilities [2]. The second design was
a same/different task [19] in which participants decided on each trial whether a pair of
objects was the same or different.
These two designs were used to inform the design of 3D applications that vary
depending on whether a user’s task-performance is based on his accuracy, or his ability
to work quickly and accurately. Some applications allow the user to respond at his
own pace and task-performance is judged solely on accuracy. For instance, a student
learning anatomy may be able to take his time learning from a 3D anatomy tool. Other
applications however may restrict the amount of time a user has to respond or may be
used in circumstances where the user is under time pressure. For instance, a surgeon
may need to act as quickly and accurately as possible while performing an operation
using image-guided therapy.
Although the choose-two-of-four task is time-limited overall, the instructions em-
phasize accuracy and there is no time limit on individual trials. The same/different task
however, measures response time on individual trials, and thus can provide additional
evidence that people are performing mental transformations of the orientations of
objects. It also allows for the evaluation of a dynamic orientation indicator. Together
these two designs provide converging evidence on the effectiveness of an orientation
indicator.
3.4.1 Choose-two-of-four task
In this task participants were shown four objects and they were to decide which two
of the four objects matched a target object (see Figure 3.1). Two of the four objects
were mirror images of the target object and thus were not congruent in shape to the
target object. Experiments 1 and 2 were identical except for the orientation indica-
33
tor. Experiment 1 assessed a non-colocated static indicator; Experiment 2 assessed a
colocated static indicator. Experiments 2 and 3 were identical except for the axes of
rotation. See Table 3.1 for a summary of the experiments.
Experiment 1 had rotations about the vertical axis parallel to the image plane,
hereafter vertical axis, and rotations about the horizontal axis parallel to the image,
hereafter horizontal axis. See Figure 3.5 for examples. In trials with rotation about
the vertical axis mirror objects were made by reflecting the object about the horizontal
axis such that the left and right of the object were reversed. In trials with rotation
about the horizontal axis mirror objects were made by reflecting the object about the
vertical axis such that the top and bottom of the object were reversed. Mirror objects
were made in this manner to prevent subjects from being able to use strategies other
than mental rotation to solve the task. Figure 3.2 shows each object in its original 0◦
position in which reflections and rotations were based from. Mirrored objects were also
rotated from the initial position.
Specifically, there were 40 trials total, 20 of these trials showed the orientation
indicator and the other 20 did not. Trials with the orientation indicator were setup
using the same rotational disparities between the target image and the object choices as
the trials without the orientation indicator. The degrees of disparity between the four
choices were also the same between orientation indicator and no indicator conditions.
Within a condition, 10 trials had rotations about the horizontal axis and 10 trials had
rotations about the vertical axis. Of these 10 trials, 5 were mechanical parts and 5
were anatomical structures. The target objects were always shown in either the 0◦,
15◦, 345◦, 30◦, or 330◦ orientation. The four objects to choose from were shown at 0◦,
15◦, 345◦, 30◦, 330◦, 45◦, 315◦, 60◦, 300◦, 75◦, or 275◦ orientations. Objects and the
mirror distractors were rotated between 15◦ and 75◦ in 15◦ increments from the target
object. Each degree of disparity between the target and four objects was used the
same number of times across all conditions (i.e., presence of aid, class of object, and
axis of rotation). Thus there was no change to the level of difficulty of a trial between
conditions.
Subjects were given four blocks of trials, two blocks were with the orientation indi-
cator, and two blocks did not have the indicator present. Two blocks were mechanical
parts and two blocks were anatomical structures. We counterbalanced the order of
the aid condition and object type condition across subjects and gender to prevent
performance differences attributed to practice effects. Subjects were given four minutes
34
to complete each block of trials, with three short breaks in between blocks. Each block
had 10 trials. It was possible for a participant to time out and not finish a block
of trials. Subjects were also permitted to skip a trial if it was too difficult, and if
time allowed they were given another chance to answer skipped trials. Instructions
emphasized the importance of accuracy over response time.
To ensure subjects understood the task, they were given written and oral instruc-
tions. The experimenter verbally explained the task with two example trials. Subjects
then had a practice period. They were given two blocks of trials that each had 3 trials;
stimuli used in practice periods were not used in the real experiment. See Figure 3.4
for objects used in practice trials. See Section A.1 for instructions.
The task was scored by giving two points for every correct answer and subtracting
two points for every incorrect answer. This scoring method corrects for guessing and
follows the conventional scoring method for Vandenberg and Kuse mental rotation
tests [2, 1]. These scores were then normalized on a scale of 0 to 1. Our main goal was
to test the effectiveness of the orientation indicator. This variable, along with the class
of objects and axis of rotation was varied within subjects to test for differences within
the individual. Spatial ability was a between subjects variable.
Experiment 3 assessed whether colocated static orientation indicators improved
subjects’ performance when object stimuli were rotated about oblique axes of rotation.
Two oblique axes were evaluated, see Figure 3.5 for example rotations. See Figure 3.6
for example trials. Mirror objects were made by reflecting the object about the vertical
axis such that the top and bottom of the object were reversed.
3.4.2 Same/different task
In this task participants were shown two objects and they were to decide whether
these two objects were the same object but shown in different orientations, or whether
they were different objects (see Figure 3.7). If they were different objects one object
was a mirror image of the other (see Figure 3.8). See Table 4.1 for a summary of the
experiments that used the same/different task. All same/different experiments were
identical except for the orientation indicator implemented.
Each experiment assessed whether an orientation indicator improves subjects’ per-
formance on a same/different task with static objects. Each experiment used rotations
35
Figure 3.4. Stimuli used in practice trials.
Figure 3.5. Four axes of rotation were assessed. Clockwise from top left: horizontalaxis, oblique axis one, oblique axis two, vertical axis. All objects are shown rotated45◦ from initial position.
36
Figure 3.6. Example choose-two-of-four trials with mechanical stimuli rotated aboutoblique axis two.
about the vertical axis and rotations about the horizontal axis. Mirror objects were
made identical to that of Experiment 1.
There were 160 trials total, 80 of these trials showed the orientation indicator and
the other 80 did not. Trials with the orientation indicator were setup using the same
rotational disparities between the two objects as trials without the orientation indicator.
Within a condition, 40 trials had rotations about the horizontal axis and 40 trials had
rotations about the vertical axis. Of these 40 trials, 20 were mechanical parts and
20 were anatomical structures. Of these 20 trials, 10 were same objects and 10 were
different objects.
The objects were shown at 0◦, 15◦, 345◦, 30◦, 330◦, 45◦, 315◦, 60◦, 300◦, 75◦, or
275◦ orientations. Objects and the mirror distractors were rotated between 15◦ and
75◦ in 15◦ increments from each other. The same object stimulus was used for a
given disparity, axis of rotation, and same/different condition. Additionally, one of
the objects was shown in the same orientation across aid and no aid condition. For
example, for a 15◦ disparity using an anatomical object rotated about the vertical
axis for a same pair, anatomical object number five was shown in the aid condition at
orientations 45◦ and 30◦ and in the no aid condition at 45◦ and 60◦. Each degree of
disparity was used the same number of times across all conditions (ie., presence of aid,
class of object, axis of rotation, same/different pair). Thus there was no change to the
level of difficulty of a trial between conditions.
Subjects were given two blocks of trials, and within these two blocks trials were
presented randomly. We counterbalanced the two blocks across subjects and gender to
37
Figure 3.7. Example same/different trials: Are the objects the same object shown indifferent orientations, or are they different objects? Subjects were presented with onetype of aid, all subjects had trials where no aid was present.
38
Figure 3.8. Example trials. These two objects are different objects.
39
prevent performance differences. Subjects were given 12 seconds per trial; if they
exceeded this time limit they were not given a chance to respond and they were
presented with the next trial. Subjects were given one short break between blocks
of trials. Subjects were not allowed to skip a trial. Instructions emphasized the
importance of both accuracy and response time. The same/different task was scored
by awarding one point for every correct answer. These scores were then normalized on
a scale of 0 to 1. The orientation indicator, class of objects, and axis of rotation were
varied within subjects. Spatial ability was a between subjects variable.
To ensure subjects understood the task, they were given written and oral instruc-
tions. The experimenter verbally explained the task with two example trials. Subjects
then had a practice period. They were given 10 practice trials; stimuli used in practice
periods were not used in the real experiment. See Figure 3.4 for objects used in practice
trials. See Section A.2 for instructions.
3.4.3 Subjects and research setting
Subjects had short breaks during the computer portion; during these breaks they
read articles from the popular press to prevent them from devising cognitive strategies
to solve the task. At the end of the computer portion of the experiment subjects were
given a written survey regarding the experimental task similar to the one given in
Peters et al. [93]. The survey asked questions regarding strategies the subject used to
solve the task, whether the subject was concerned about time pressure, and whether
the subject felt more confident when the indicator was present. See section A.3 for
complete survey. Subjects’ spatial visualization ability was measured using the two
paper-and-pencil tests mentioned prior.
See Table 3.1 for numbers of participants in each experiment by spatial ability and
gender. All subjects were University of Utah students who were given either psychology
course credit or compensation of 10 dollars for their participation. All subjects read and
signed Institutional Review Board consent forms prior to the experiment. Subjects were
not allowed to participate in multiple experiments. Subjects performed the experiment
individually in a controlled experiment room where lighting was held constant. The
experiment was run on a Windows machine using E-Prime software with a 19 inch
monitor. See Figure 3.9 for a picture of the research setting. Viewing position was
also held constant with the observer’s head located approximately 31 inches from the
monitor. Although subjects were instructed to remain seated in one location, head
40
movement was not controlled for. Subjects responded with a button box. For the
choose-two-of-four task, buttons were spatially mapped to the object choices on the
monitor.
41
Low Ability High Ability All SubjectsF M T F M T F M T
Exp 1 13 4 17 8 15 23 21 19 40
Exp 2 15 4 19 9 12 21 24 16 40
Exp 3 14 3 17 7 16 23 21 19 40
Exp 4 17 4 21 4 15 19 21 19 40
Exp 5 13 8 21 9 10 19 22 18 40
Exp 6 15 8 23 6 11 17 21 19 40
Exp 7 16 8 24 5 11 16 21 19 40
Table 3.1. Number of subjects in each experiment by spatial ability and gender.Female (F), Male (M), Total (T).
Figure 3.9. Research setting where subjects took experiment.
CHAPTER 4
EVALUATING ORIENTATION
INDICATOR EXPERIMENTS
This chapter describes the results of the orientation indicator experiments which
were conducted using the procedures described in Chapter 3. Three experiments used
the choose-two-of-four task and four experiments used the same/different task. Note
that the choose-two-of-four experiment scores should not be directly compared to
same/different experiment scores because of the intrinsic difference in how the two
tasks are scored.
4.1 Results and discussion of choose-two-of-fourexperiments
A 2(orientation indicator)×2(class of objects)×2(axis of rotation)× 2(spatial abil-
ity) ANOVA was performed on the mean scores for each experiment. Cohen’s d was
calculated as a measure of effect size for the presence/absence of the aid, defined as the
difference between the two group means divided by the pooled standard deviations of
the two groups. Cohen’s d effect size can be indicative of a small effect (.2), a medium
effect (.5), and a large effect (.8). All three experiments presented static orientation
indicators because of the nature of the choose-two-of-four task.
4.1.1 Accuracy score
4.1.1.1 Colocated vs. non-colocated indicators
The colocated orientation indicator increased subjects’ accuracy in Experiment
2; this experiment used rotations about the vertical and horizontal axes. Subjects’
increase in task-performance is shown by a statistically significant overall effect of the
indicator. Participants showed an increase in accuracy with the colocated aid (.76)
versus without the aid (.73). The effect size of the indicator is .25, indicating a small
effect. See Table 3.1 for statistics associated with the main effect of the indicator.
43
Neither Experiment 1, using a non-colocated orientation indicator with rotations
about the vertical and horizontal axes, or Experiment 3, using a colocated indicator
with oblique rotations, showed a main effect of the orientation indicator. In Experiment
1, participants scored nearly the same with the aid (.77) versus without the aid (.76).
In Experiment 3, participants scored slightly higher with the aid (.79) versus without
the aid (.76). The effect size for each experiment was .08 and .27, respectively; which
indicate the aids did not have a strong influence on users’ accuracy. The results from
these three experiments suggest that a colocated aid is more effective than a non-
colocated aid, especially when objects are rotated about the vertical and horizontal
axes. See Table 3.1 for statistics associated with the main effect of the indicator.
4.1.1.2 Individual differences in spatial ability
Individuals’ spatial abilities did impact the extent to which they benefited from an
orientation indicator. The two experiments with colocated indicators (Experiments 2
and 3) both showed facilitatory effects of spatial ability and orientation indicator. As
Figure 4.1 shows, it is clear that the effect of the indicator in Experiment 2 was driven
by low spatial learners. The low spatial group showed an increase in accuracy with
the aid (.69) versus without the aid (.62), whereas the high spatial group showed no
change (.83) for both conditions. The effect size was much higher for the low spatial
group (.73) versus the high spatial group (.04), indicating the aid had a strong effect
for the low spatial group and no effect for the high spatial group. The results from
Experiment 2 indicate that low spatial ability users can benefit from a colocated aid
when objects are rotated about the vertical and horizontal axes. See Table 3.1 for
statistics associated with the interaction between spatial ability and indicator.
We also found that high spatial learners can benefit from a colocated aid. In
Experiment 3, a statistical interaction among spatial ability, aid, and axis indicated
that the aid was particularly beneficial for high spatial learners for rotations about
oblique axis one. As Figure 4.2 shows, it is clear that the effect of the indicator and
axis of rotation in Experiment 3 was driven by high spatial learners. The high spatial
group showed an increase in accuracy with the aid (.85) versus without the aid (.76),
whereas the low spatial group showed a smaller increase with the aid (.73) versus
without the aid (.70). The effect size was much higher for the high spatial group (.90)
versus the low spatial group (.26), indicating the aid had a strong effect for the high
spatial group and a small effect for the low spatial group. The results from Experiment
44
Choose-Two-of-Four Rotation Effect of Indicator Average Scores Statistics Effect Size
no overall .76 without aid F (1,38) = .5.08
Exp 1: non-colocated horizontal effect .77 with aid p = .5static vertical significant effect .73 without aid F (1,38) = 8.4
.35for horizontal .77 with aid p < .01
Exp 2: colocated static
significant .73 without aid F (1,38) = 8.5.25
overall effect .76 with aid p < .01horizontal significant effect high spatial: .83 both without and with aid F (1,38) = 10.1 .04vertical by spatial ability low spatial: .62 without aid, .69 with aid p < .01 .73
significant effect .71 without aid F (1,38) = 18.3.64
for horizontal .79 with aid p < .01
Exp 3: colocated static
no overall .76 without aid F (1,38) = 1.7.27
effect .79 with aid p = .2oblique one high spatial: .76 without aid, .85 with aid F (1,38) = 3.0 .90
oblique one by spatial ability low spatial: .70 without aid, .73 with aid p < .10 .26oblique two significant effect mechanical objects: .82 without aid F (1,38) = 4.9
.47for object type .87 with aid p < .05significant effect .73 without aid F (1,38) = 7.5
.56for oblique one .80 with aid p < .01
Table 4.1. Accuracy results for the choose-two-of-four experiments. 40 subjects per experiment.
45
3 indicate that high spatial ability users can benefit from a colocated aid when objects
are rotated about an oblique axis. See Table 3.1 for statistics associated with the
interaction between spatial ability, indicator, and axis of rotation.
Lastly, in all three experiments there was an overall difference in accuracy between
high spatial ability and low spatial ability groups, p < .01. On average, the high spatial
group scored higher (.82) than the low spatial group (.69).
4.1.1.3 Class of objects
Each experiment also showed a significant effect on the class of objects, p < .01.
Objects that were mechanical parts were easier for subjects to visualize than objects
that were anatomical parts. On average, subjects scored higher on trials that presented
mechanical objects (.82) versus anatomical objects (.71).
Only one experiment, Experiment 3 using a colocated aid with oblique rotations,
showed an interaction between class of objects and orientation indicator. This result
indicated that the orientation indicator helped more with mechanical parts versus
anatomical parts. For mechanical parts, participants showed an increase in accuracy
with the aid (.87) versus without the aid (.82). The effect size is .47, indicating the aid
had a medium sized effect for mechanical objects. For anatomical parts, participants
scored nearly the same with the aid (.70) versus without the aid (.71). These results
indicate that if a distinct object is rotated about an oblique axis users may benefit from
a colocated static indicator. See Table 3.1 for statistics associated with the interaction
between class of objects and indicator.
Finally, the effect of the class of objects was modulated by the axis of rotation in
Experiments 1 and 2, which used non-colocated and colocated aids with vertical and
horizontal rotations, respectively. In each experiment the results indicated that vertical
rotations were easier than horizontal rotations for anatomical parts. Participants in
Experiment 1 showed an increase in accuracy with anatomical objects rotated about the
vertical axis (.75) versus the horizontal axis (.69), F (1,38) = 3.7, p < .1. For mechanical
parts, participants scored nearly the same with objects rotated about the vertical axis
(.80) versus the horizontal axis (.81). Participants in Experiment 2 showed an increase
in accuracy with anatomical objects rotated about the vertical axis (.71) versus the
horizontal axis (.68), F (1,38) = 6.6, p < .05. For mechanical parts, participants showed
an increase in accuracy for objects rotated about the horizontal axis (.81) versus the
vertical axis (.77).
46
Figure 4.1. Mean score on Experiment 2, with and without colocated static orienta-tion indicator with vertical and horizontal rotations, by spatial ability.
Figure 4.2. Mean score on Experiment 3, with and without colocated static orienta-tion indicator with oblique one rotation, by spatial ability.
47
These results suggest that people have more difficulty when mentally rotating
anatomical parts than mechanical parts. It may be that people have trouble creating
a mental representation of an object that is composed of abstract pieces. People may
be more accurate at creating a mental representation of an object that is composed of
distinct pieces. Furthermore, if an individual has difficulty mentally rotating a complex
object, it may be easier for him or her to perceive the object rotating about the vertical
axis versus the horizontal axis. Whereas, if an individual can efficiently mentally rotate
a simple object, he or she may be able to perceive the object rotating about the vertical
axis with the same ease as the object rotating about the horizontal axis.
4.1.1.4 Axis of rotation
As indicated from previous results, the axis of rotation that an object is rotated
about may influence task-performance. We found that the axis of rotation influenced
a user’s accuracy in two experiments. Experiments 1 and 3, which used non-colocated
and colocated aids, each showed a significant effect of the axis of rotation on task-
performance. In Experiment 1, which assessed vertical and horizontal axes of rotation,
participants showed an increase in accuracy with objects rotated about the vertical axis
(.78) versus the horizontal axis (.76). F (1,38) = 3.3, p < .01. In Experiment 3, which
assessed two oblique axes of rotation, participants showed an increase in accuracy with
objects rotated about oblique axis two (.79) versus oblique axis one (.77). F (1,38) =
4.1, p < .1.
These results suggest that individuals may have an easier time perceiving the
structure of an object when it is rotated about certain axes. The axis of rotation
may impact a user’s ability to effectively use a visualization. In particular, people may
find it easier to rotate an object about the vertical axis or an axis which produces
rotations that are familiar to them. People may find it more difficult to rotate an
object about the horizontal axis or an axis which produces rotation that are unfamiliar
to them.
Finally, the orientation indicator effect was modulated by the axis of rotation in all
three experiments. For Experiments 1 and 2 which involved horizontal and vertical axes
of rotation, the presence of the indicator led to increased accuracy for objects rotated
about the horizontal axis, but no difference for the vertical axis. In Experiment 1 for
rotation about the horizontal axis, participants scored higher with the aid (.77) versus
without the aid (.73). The effect size for the horizontal axis was .35, indicating a
48
mediocre sized effect. For rotation about the vertical axis, participants scored higher
without the aid (.79) versus with the aid (.76). In Experiment 2 for rotation about
the horizontal axis, participants scored higher with the aid (.79) versus without the aid
(.71). The effect size for the horizontal axis is .64, indicating a good sized effect. For
rotation about the vertical axis, participants scored higher without the aid (.75) versus
with the aid (.73).
In Experiment 3, which involved two different oblique axes, the indicator helped
performance in one axis of rotation, but not the other. For rotation about oblique axis
one, participants scored higher with the aid (.80) versus without the aid (.73). The
effect size for oblique axis one is .56, indicating a medium sized effect. For rotation
about oblique axis two, participants scored higher without the aid (.79) versus with
the aid (.78). See Table 3.1 for statistics associated with the interaction between axis
of rotation and indicator.
The axis of rotation which an object is rotated about may influence whether a user
will benefit from an orientation indicator. The results indicate that when an object is
rotated about an axis that is familiar to a user, such as the vertical axis, the user may
not need the cognitive support provided by the indicator. However, when an object is
rotated about an axis that is difficult for a user, such as the horizontal axis, the user
may benefit from cognitive support provided by the indicator.
4.2 Results and discussion of same/different experiments
A 2(orientation indicator) × 2(class of objects) × 2(axis of rotation) × 2(spatial
ability) ANOVA was performed on the mean scores for each experiment.Cohen’s d was
calculated as a measure of effect size for the presence/absence of the aid, defined as
the difference between the two group means divided by the pooled standard deviations
of the two groups. Cohen’s d effect size can be indicative of a small effect (.2), a
medium effect (.5), and a large effect (.8). Two experiments presented static orientation
indicators and two presented dynamic orientation indicators.
4.2.1 Accuracy score
4.2.1.1 Colocated vs. non-colocated indicators
All four experiments showed effects of the orientation indicator. The static ex-
periments showed stronger effects versus the dynamic experiments. The colocated
experiments showed stronger effects versus the non-colocated experiments.
49
In Experiment 4 using a non-colocated static indicator, participants showed an
increase in accuracy with the aid (.74) versus without the aid (.69). The effect size for
the non-colocated static aid was .51, indicating a medium sized effect. In Experiment
5 using a colocated static indicator, participants showed an increase in accuracy with
the aid (.75) versus without the aid (.67). The effect size for the colocated static aid
was .78, indicating a large sized effect. In Experiment 6 using a non-colocated dynamic
indicator, participants showed an increase in accuracy with the aid (.69) versus without
the aid (.67). The effect size for the non-colocated dynamic aid was .19, indicating a
small sized effect. In Experiment 7 using a colocated dynamic indicator, participants
showed an increase in accuracy with the aid (.73) versus without the aid (.69). The
effect size for the colocated dynamic aid was .44, indicating a mediocre sized effect.
See Table 4.1 for statistics associated with the main effect of the indicator.
These results suggest that the effectiveness of an orientation indicator depends on
the type of orientation indicator implemented. Our results show that static indicators
are more effective than dynamic indicators. We also found that colocated indicators are
more effective than non-colocated indicators. Accordingly, a colocated static indicator
was the most helpful to users, and a non-colocated dynamic indicator was the least
helpful to users.
4.2.1.2 Individual differences in spatial ability
Individual’s spatial ability may impact task-performance with a non-colocated static
orientation indicator. When individuals’ spatial ability was taken into account, Ex-
periment 4 using a non-colocated static indicator, showed facilitatory effects of the
indicator. As seen in Figure 4.3, the effect of the non-colocated static indicator was
driven by high spatial learners. The high spatial group showed an increase in accuracy
with the aid (.81) versus without the aid (.73), whereas the low spatial group showed
a smaller increase with the aid (.67) versus without the aid (.65). The effect size
was much higher for the high spatial group (1.05) versus the low spatial group (.27),
indicating the aid had a strong effect for the high spatial group and a small effect
for the low spatial group. See Table 4.1 for statistics associated with the interaction
between spatial ability and indicator.
In contrast, there was no statistically significant interaction between spatial ability
and indicator in Experiment 5 which used a colocated static indicator. As Figure 4.4
shows, the colocated static indicator helped both spatial ability groups. The ex-
50
Same/Different Task Effect of Indicator Average Scores Statistics Effect Size of Aid
Exp 4: non-colocated static
significant .69 without aid F (1,38) = 18.1.51
overall effect .74 with aid p < .01significant effect high spatial: .73 without aid, .81 with aid F (1,38) = 6.1 1.05by spatial ability low spatial: .65 without aid, .67 with aid p < .05 .27
Exp 5: colocated static
significant .67 without aid F (1,38) = 41.5.78
overall effect .75 with aid p < .01significant effect anatomical objects: .60 without aid F (1,38) = 12.4
1.04for object type .71 with aid p < .01significant effect .64 without aid F (1,38) = 5.4
.90for horizontal axis .75 with aid p < .05
Exp 6: non-colocated dynamicsignificant .67 without aid F (1,38) = 5.5
.19overall effect .69 with aid p < .05
Exp 7: colocated dynamicsignificant .69 without aid F (1,38) = 13.6
.44overall effect .73 with aid p < .01
Table 4.2. Accuracy results for the same/different experiments. Rotation always about horizontal axis or vertical axis. 40 subjectsper experiment.
51
Figure 4.3. Mean score on same/different task with and without non-colocated staticorientation indicator by spatial ability.
Figure 4.4. Mean score on same/different task with and without colocated staticorientation indicator by spatial ability.
52
periments with dynamic indicators also did not result in a statistically significant
interaction between spatial ability and indicator.
These results confirm the need to evaluate individual differences in spatial ability.
It may be that high spatial ability users are able to use a non-colocated static aid more
effectively than low spatial ability users. However, both spatial ability groups are able
to effectively use a colocated static aid.
There was also an interaction between class of objects and spatial ability in both
non-colocated indicator experiments. Experiment 4, F (1,38) = 9.7, p < .01. Experi-
ment 6, F (1,38) = 4.4, p < .05. These two experiments indicated high spatial learners
scored significantly higher on trials that presented mechanical objects versus trials that
presented anatomical objects. On average, the high spatial group showed an increase
in accuracy with mechanical objects (.82) versus anatomical objects (.69), whereas the
low spatial group showed a smaller increase in accuracy with mechanical objects (.68)
versus anatomical objects (.63). These results suggest that people with high spatial
ability will be more accurate at perceiving distinct objects than people with low spatial
ability.
Furthermore, in Experiment 7 using a colocated dynamic indicator, there was a
significant interaction between spatial ability and axis of rotation. F (1,38) = 8.6,
p < .01. The high spatial ability group showed an increase in accuracy with objects
rotated about the vertical axis (.77) versus objects rotated about the horizontal axis
(.74), whereas the low spatial ability group showed a smaller increase in accuracy with
objects rotated about the vertical axis (.70) versus objects rotated about the horizontal
axis (.69). This result may imply that objects rotated about the vertical axis will be
easier for high spatial ability users than low spatial ability users.
Lastly, in all four experiments there was an overall difference in accuracy between
high spatial ability and low spatial ability groups, p < .01. On average, the high spatial
group scored higher (.76) than the low spatial group (.65).
4.2.1.3 Class of objects
Each experiment also showed a significant effect on the class of objects, p < .01.
Objects that were mechanical parts were easier for subjects to visualize than objects
that were anatomical parts. On average, subjects scored higher on mechanical objects
(.75) versus anatomical objects (.65).
Only one experiment, Experiment 5 using a colocated static indicator, showed an
53
interaction between class of objects and orientation indicator. This result indicated
that the orientation indicator helped more with anatomical parts versus mechanical
parts. For anatomical parts, participants showed an increase in accuracy with the aid
(.71) versus without the aid (.60). The effect size is 1.04, indicating the aid had a large
sized effect for anatomical objects. For mechanical parts, participants showed a smaller
increase with the aid (.79) versus without the aid (.74). See Table 4.1 for statistics
associated with the interaction between class of objects and indicator.
Users may have more difficulty when mentally rotating anatomical parts than
mechanical parts. The results also indicate that if a complex object is rotated about
the vertical and horizontal axes users may benefit from a colocated static indicator.
If a less complex object is rotated about the vertical and horizontal axes, users may
benefit less from a colocated aid.
4.2.1.4 Axis of rotation
The axis of rotation that an object is rotated about influenced task-performance in
three experiments. Experiments 4, 5, and 6 each showed a significant effect of the axis
of rotation on task-performance, p < .10. All experiments used rotations about the
vertical axis and horizontal axis, and the objects that rotated about the vertical axis
were easier for users than objects that rotated about the horizontal axis. On average,
participants showed an increase in accuracy with objects rotated about the vertical
axis (.72) versus the horizontal axis (.69).
Furthermore, the effect of the colocated static indicator was modulated by the axis
of rotation. As shown in Figure 4.5, the presence of the indicator made a larger impact
for objects rotated about the horizontal axis than objects rotated about the vertical
axis. The effect size is .90, indicating the aid had a large size effect for objects rotated
about the horizontal axis. See Table 4.1 for statistics associated with the interaction
between axis of rotation and indicator.
These results suggest that users may have an easier time perceiving the structure
of an object when it is rotated about the vertical axis. Users may have a harder time
perceiving the structure of an object when it is rotated about the horizontal axis.
Accordingly, a colocated static indicator may be more beneficial to users when objects
are rotated about a difficult axis such as the horizontal axis and less beneficial to users
when objects are rotated about a more familiar axis such as the vertical axis.
54
4.2.2 Response time
Response time was analyzed to determine if users took a longer amount of time
to respond to trials when the indicator was present than trials when the indicator
was absent. The analysis of response time also allows us to compare the response
time functions to that of prior research on mental rotation. Typically researchers find
response times for mental rotation to be linear; subjects take longer to respond with
greater degrees of disparity between objects.
Response time was analyzed from Experiments 4 and 5 because participants ben-
efited the most from static aids. A 2(orientation indicator) × 5(degree of rotation) ×
2(spatial ability) ANOVA was performed on response time from trials that participants
got correct and that presented subjects with two objects that were the same. Data
from 36 subjects (18 low ability, 18 high ability) was analyzed from Experiment 4,
which used a non-colocated aid, because four subjects did not get at least one trial
correct per orientation indicator and degree of rotation. Data from all 40 subjects was
analyzed from Experiment 5, which used a colocated aid. Class of objects and axis of
rotation could not be analyzed because the majority of subjects did not get at least
one of these trials correct for each degree of rotation.
In both experiments the orientation indicator had a statistically significant effect
on response time. In Experiment 4, subjects had increased response time with the
aid (4.8 seconds) versus without the aid (4.2 seconds). In Experiment 5, subjects had
increased response time with the aid (5.6 seconds) versus without the aid (4.5 seconds).
The orientation indicators could increase response time for three reasons. One, users
may decide on a response without using the aid and then validate their response with
the aid. Two, users may use the aid as features of the object and thus take longer to
respond because there are more features to compare. Or three, users may use the aid to
develop another strategy to solve the task such as using the aid to eliminate incorrect
responses. See Figures 4.6 and 4.7 for graphs of response times in each condition. See
Table 4.3 for statistics associated with effects of the indicator.
Each experiment also showed increased response times with greater degree of rota-
tion between the two objects. This finding is typical of mental rotation experiments
that present same/different tasks. In Experiment 4, response times were higher for
disparities of 75◦ (4.9 seconds) versus disparities of 15◦ (4.3 seconds). In Experiment 5,
response times were higher for disparities of 75◦ (5.4 seconds) versus disparities of 15◦
(4.8 seconds). These results could be interpreted as increasing time needed to mentally
55
Figure 4.5. Mean score on same/different task with and without colocated staticorientation indicator by axis of rotation.
Figure 4.6. Mean response time on same/different task with and without non-colo-cated static orientation indicator by spatial ability.
56
rotate one object to match the other, or it could be an indication of an overall increase
in difficulty with greater disparity. See Figures 4.6 and 4.7 for graphs of response times
for each degree of disparity. See Table 4.3 for statistics associated with effects of the
degree of disparity on response time.
4.2.2.1 Response time and spatial ability
Furthermore, Experiment 4, which used a non-colocated static indicator showed a
main effect of spatial ability. High spatial ability participants showed increased response
times (4.9 seconds) versus low spatial ability participants (4.1 seconds). Low spatial
ability users took less time to respond than high spatial ability users, both when the
non-colocated aid was present and when it was absent. See Figure 4.6 for response
time by spatial ability.
This result could stem from low spatial ability subjects using different strategies
to solve the task than high spatial ability subjects. Qualitative results from written
surveys (see section A.3) showed that 58% of subjects used various strategies to solve
the task, and 25% used a specific approach. There was no difference between low and
high spatial groups in whether they tried various approaches or a specific approach.
There was however, a difference between spatial ability groups in whether users men-
tally rotated the whole figure or whether users mentally rotated a section of the figure
when making a comparison. Low spatial users preferred to mentally rotate the whole
figure (86%) versus a section of the figure (10%). High spatial users did not have as
strong of a preference to mentally rotate the whole figure (58%) versus a section of the
figure (37%).
Additionally, subjects from both spatial groups reported using verbal strategies and
visual strategies to solve the task. Verbal strategies involve solving the task verbally in
the mind (i.e., “shorter part up and longer part down”). Visual strategies rely mainly
on visualizing the figures and users do not talk themselves through the steps. Both low
spatial users (48%) and high spatial users (42%) reported that they thought through
the steps verbally in their minds. Low spatial users were less likely to visualize the
figures (43%) versus high spatial users (58%). These results indicate that both spatial
groups may process information verbally, but high spatial users are slightly more likely
to process information visually than low spatial users.
Lastly, Experiment 5, which used a colocated static indicator did not show a main
effect of spatial ability. Recall that the colocated static aid increased all users accuracy.
57
Figure 4.7. Mean response time on same/different task with and without colocatedstatic orientation indicator.
Experiment Variable Average RT Statistics
Experiment 4non-colocated 4.2 seconds without aid F (1,34) = 30.7
indicator 4.8 seconds with aid p < .01
Experiment 5colocated 4.5 seconds without aid F (1,38) = 147.5indicator 5.6 seconds with aid p < .01
Experiment 4degree of 4.3 seconds at 15◦ F (1,136) = 7.8rotation 4.8 seconds at 75◦ p < .01
Experiment 5degree of 4.7 seconds at 15◦ F (1,152) = 9.2rotation 5.5 seconds at 75◦ p < .01
Table 4.3. Response time (RT) results in seconds for Experiments 4 and 5.
58
Qualitative results from written surveys (see section A.3) showed that high spatial
ability subjects were slightly more likely to use various approaches to solve a task (47%)
compared to low spatial ability subjects (38%). Both high spatial ability subjects (37%)
and low spatial ability subjects (33%) stated they used a specific strategy to solve the
task. More low spatial ability subjects said they did not have a specific strategy to
solve the task (29%) versus high spatial ability subjects (16%).
There was also a difference between spatial ability groups in whether users mentally
rotated the whole figure, or whether users mentally rotated a section of the figure. With
the colocated static aid, low spatial users preferred to mentally rotate the whole figure
(71%) versus a section of the figure (29%). High spatial users did not have as strong
of a preference to mentally rotate the whole figure (58%) versus a section of the figure
(42%).
Furthermore, subjects from both spatial groups reported using verbal strategies
and visual strategies to solve the task. Both low spatial users (38%) and high spatial
users (37%) reported that they thought through the steps verbally in their minds. Low
spatial users were slightly less likely to visualize a figure (57%) than high spatial users
(63%).
The qualitative results differed between Experiment 4, which used a non-colocated
static aid, and Experiment 5, which used a colocated static aid. First, the difference
for low spatial users in whether they rotated the whole figure or a section was not as
prominent with the colocated aid as it was with the non-colocated aid. Second, both
spatial groups may process information verbally, but subjects that were presented a
colocated static aid were more likely to use visualization strategies than subjects that
were presented a non-colocated static aid. In particular, low spatial users may use
visualization strategies more when presented with a colocated static indicator versus a
non-colocated static indicator.
4.3 Comparison and contrast of the accuracy results ofthe two tasks
Two tasks were used to analyze a user’s performance with orientation indicators.
One task used a choose-two-of-four paradigm and the other used a same/different
paradigm. The choose-two-of-four task placed an emphasis on accuracy, while the
same/different task placed an emphasis on both accuracy and response time. The
dynamic aids were not analyzed with the choose-two-of-four experiments because of
59
the nature of the task. In both tasks, the colocated static aid was more effective than
the non-colocated static aid.
Users’ performance with the colocated static aid was correlated with spatial ability
in the choose-two-of-four experiments, but not in the same/different experiments. In
the choose-two-of-four experiments, low spatial users benefited from a colocated aid
with rotations about the vertical and horizontal axes and high spatial users benefited
from a colocated aid with rotation about an oblique axis. In the same/different
experiment, all users benefited from a colocated aid with rotations about the vertical
and horizontal axes.
The difference in performance between the two tasks, spatial ability, and effective-
ness of the colocated aid could stem from time pressure. As noted, in the same/different
task users were told to respond quickly and accurately, and each trial had a time limit
of 12 seconds. This time pressure could have made the same/different task difficult
for users and users may have relied on the aid to respond as quickly and accurately as
possible.
The difference in performance could also be related to different strategies being
used to solve the choose-two-of-four task and the same/different task. The choose-two-
of-four task allows for strategies that cannot be used to solve the same/different task.
For example, in the choose-two-of-four task users can eliminate incorrect answers to
arrive at the correct responses. Also, users did not have to compare objects to the
target object; they could find a match and then compare the rest of the options to that
match. These strategies are not possible in the same/different task.
Users’ task-performance with the non-colocated static aid did not have strong effects
in either task. In the choose-two-of-four tasks, there was no overall effect of the non-
colocated static aid, and a small effect for objects rotated about the horizontal axis.
In the same/different task, there was a small overall effect of the aid, and this effect
was driven by high spatial users. These results suggest that the non-colocated aid was
either too difficult for users to effectively use, or that users did not feel they needed
cognitive support to accurately perform the task so they ignored the aid.
CHAPTER 5
DISCUSSION AND CONTRIBUTIONS
This chapter summarizes the results of the present research. The results are dis-
cussed both in terms of their theoretical and practical contributions; we can gain
additional insight into how the human perceptual system processes cues that help
us maintain the orientation of a 3D object in an abstract virtual space and we can
use this knowledge to create more effective 3D applications. This chapter also covers
possible ways this work could be extended for future research.
5.1 Summary of this research
Users have a difficult time maintaining the orientation of 3D objects shown on a 3D
desktop display. In the present work, we have evaluated whether users can benefit from
additional information provided by in-scene cognitive aids when viewing multiple static
visualizations simultaneously. We achieved this goal by using a cognitive experimental
paradigm which has been extensively used in the psychology community. By using this
paradigm we were able to systematically evaluate users’ perceptions of the orientation
of 3D objects in ways that are meaningful to engineers designing 3D applications.
Specifically, we used the mental rotation paradigm to evaluate a user’s ability to
maintain the orientation of a 3D object shown as multiple static views (see Chapter 3).
We evaluated whether four types of orientation indicators increased a user’s ability
to perceive the orientation of a 3D object as a function of the task being performed,
the complexity of the object, the axis of rotation, and the presence of dynamic in-
formation. Additionally, we took users’ spatial abilities into account because a user’s
abilities/spatial abilities may influence whether he or she benefits from an orientation
indicator. Different types of orientation indicators were evaluated because users may
benefit from the different cues they provide such as proximity to the 3D object and
dynamic motion. Chapter 4 presents the results in detail, and Tables 4.1, 4.2, and 4.3
provide brief summaries of the effects of the orientation indicators.
61
5.1.1 Type of orientation indicator and spatial ability
As anticipated, the type of orientation indicator implemented and spatial ability
influenced users’ abilities to make object orientation judgments of 3D geometric objects
shown as multiple views. Little improvement was shown for users presented with
non-colocated orientation indicators, although high spatial ability users did show some
benefit. Colocated aids helped all users.
These results are reflected in the qualitative data collected. Low spatial users
stated that they tried to use the non-colocated static aid, but that they were not sure
whether it helped them. They made comments such as, “The aid added another level
of complexity to the task, I first had to solve for the aid and then the object, and that
was difficult for me,” and “The aid was just another thing to compare.” High spatial
users said that they were “able to use the aid, but felt the task was the same level
of difficulty throughout the experiment.” In general, users who were presented with
the colocated static aid felt it helped them. Users from both spatial ability groups
commented that the colocated aid helped “because the colors showed me how to rotate
the object.” Some subjects stated that they “always wanted the aid to be there.”
5.1.2 Dynamic vs. static orientation indicators
Dynamic aids were not as effective as static aids. Users from both spatial ability
groups made comments that the dynamic aids were confusing, distracting, and in some
instances they thought the aid was “lying to them”. It may be that individuals use
different paths of rotation to solve the same task, so showing one particular path may
not help everyone solve the task. Furthermore, people do not necessarily always use
the shortest path between two objects to mentally rotate one object to determine if
it is congruent with another object [64, 56]. For instance, if there is 90◦ of disparity
between two objects, a user may first rotate the object 90◦ about the picture plane and
then another 90◦ about the vertical axis instead of rotating the object 90◦ about the
horizontal axis to determine if the two objects are the same.
The dynamic aids did not increase users’ accuracy as much as anticipated. Our
hypothesis was that the dynamic aid would increase users’ accuracy more than the
static aid because motion is a very prominent cue, but this result did not occur. Instead,
users were confused by the dynamic aid, and the visual information it provided was
not an effective method to communicate information to the user. This result gives
additional evidence that not all visual information may benefit users, and that users
62
may not be able to extract relevant information from visual imagery. In general, users
preferred the static aids over the dynamic aids.
5.1.3 Factors that influence task-performance with a colocatedstatic indicator
The following discussion will focus on a colocated static aid because all users had
an increase in performance when presented with a colocated static aid. Task-difficulty
may characterize how much a user benefits from an aid, and the difficulty of the task
can be a function of time pressure, axis of rotation, and individuals’ spatial ability.
Each of these factors may effect whether a colocated static aid can help a user.
5.1.3.1 Time pressure
The task being performed may affect whether a user benefits from an orientation
indicator. Specifically, if the task involves time pressure, then all users may benefit from
an orientation indicator. Our results showed that all participants had improved accu-
racy with an orientation indicator in a task with time pressure. In the same/different
task, users were told to respond quickly and accurately, and each trial had a time
limit. Subjects reported that they felt pressured to respond as quickly and accurately
as possible.
Tasks with time pressure may be inherently difficult for all users. In these tasks
users may need to perform as fast as possible without sacrificing accuracy because of
time restrictions. For instance, doctors may not be able to dedicate as much time to
an application compared to medical students. Furthermore, applications may be used
in circumstances where time is constrained, such as in image-guided surgery.
However, as the response time data showed, orientation indicators increased users’
time to complete a task. On average, users showed a 1.1 second increase in response
time when presented with a colocated static indicator. In some applications, this
increase in response time from a colocated aid may be justified by the increase in
accuracy. For instance, surgeons may feel comfortable with a slight increase in response
times in non-emergency operations. In contrast, surgeons may not want any increase
in response times in operations when the patient’s life is in jeopardy.
5.1.3.2 Axis of rotation
Our results indicate that the axis of rotation may impact a user’s performance
with a visualization. Previous research has stated that people are inherently better
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at mentally rotating objects about certain axes of rotation, and familiar axes may be
the easiest for people to visualize. For example, objects rotated about the vertical axis
usually require the least amount of time for people to imagine objects being rotated
about. It may be that the vertical axis of rotation is the most familiar to people and
more ecologically valid than other axes of rotation [64, 56].
It is also known that oblique rotations are difficult for both spatial ability groups [56,
93]. People may have difficulty perceiving the orientations of two objects rotated about
an arbitrary axis because the plane of rotation is not familiar to them. Furthermore,
the objects we assessed had initial orientations that we thought would be intuitive to
users. See Figure 3.2. Had we used initial orientations in which parts of the objects
were not aligned to a natural coordinate frame subjects may have had greater difficulty
and might have benefited from the orientation indicator more than they did.
Furthermore, the axis of rotation may influence how much a user benefits from a
colocated aid. Certain axes of rotation cause more self-occlusion of an object than
other axes of rotation, and the amount of occlusion could impact the effectiveness of
a colocated indicator. Greater amounts of occlusion could cause the colocated aid
to be more effective for a user. The colocated static indicator particularly helped
when objects were rotated about the horizontal axis and oblique axis one. As seen in
Figure 3.5, these axes caused more of the object to be occluded from view than the
vertical and oblique two axes.
5.1.3.3 Spatial ability
A user’s spatial ability influenced his or her performance and whether they benefited
from an orientation indicator. High spatial ability users outperformed low spatial
ability users. High spatial ability users had an increase in task-performance when
using the non-colocated aid. All users, however, had success in using the colocated aid.
As discussed, the axis of rotation can impact the difficulty of a task, and the axis of
rotation and spatial ability can also contribute to the difficulty of a task. Low spatial
users had difficulty rotating objects about the horizontal and vertical axes; high spatial
users had difficulty rotating objects about an oblique axis. Accordingly, low spatial
users benefited from a colocated aid with objects rotated about the horizontal and
vertical axes, and high spatial users benefited from a colocated aid with objects rotated
about an oblique axis.
It has been shown that there is a wide range of people’s spatial abilities not only
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in the general population, but also within specialized populations such as practicing
surgeons [35, 17]. It is imperative that all users are able to benefit from a 3D visual-
ization. Three-dimensional applications are being used in a variety of fields and need
to be accessible to a broad population of users.
5.1.3.4 Ceiling and floor effects
Our results suggest that users may not be able to benefit from a colocated aid if
they are performing at a ceiling or a floor. We found that a user’s ability to benefit
from an aid is effected by the level of difficulty of the task. If the task is too easy, or
too difficult, the user may not benefit from a colocated indicator.
If the task is too easy, the user may be performing at a ceiling. The aid may
not be able to assist the user because he or she is performing at his or her highest
threshold. For example, high spatial users did not benefit from a colocated aid in the
choose-two-of-four task with rotation about the vertical or horizontal axis.
If the task is too difficult, the user may be performing at a floor. The aid may
not be able to assist the user because he or she is having extreme difficulty in solving
the task. For example, low spatial users did not benefit from a colocated aid in the
choose-two-of-four task with rotation about an oblique axis.
In some trials the colocated aid did not provide sufficient information to help users.
Specific variables that we found to influence the difficult of a task include time pressure,
axis of rotation, and spatial ability. However, other forms of cognitive support may
be able to break these barriers and provide users with the necessary information to be
able to score higher regardless of whether they are at a ceiling or a floor.
5.1.4 Object complexity
Objects may have varying degrees of complexity. Users from both spatial ability
groups said that the “abstract” shapes were more difficult than the objects with
“distinct pieces”. In the non-colocated same/different tasks high spatial users were
able to solve mechanical parts easier than low spatial users.
The complexity of an object may effect the difficulty of a task, but this factor
is not as important as time pressure, axis of rotation, or individuals’ spatial ability in
determining the effectiveness of an orientation indicator. For example, a user may have
increased performance with an indicator when shown a simple object that is rotated
about an oblique angle. In contrast, a user may have increased performance with an
indicator when shown a complex object that is rotated about the horizontal axis.
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5.2 Future work
It would be beneficial if future research evaluated and increased the utility of
3D computer graphics for a broad population of users through the use of cognitive
experimental paradigms. As shown in the present work, variables such as orientation
indicators, tasks, axes of rotation, and the presence of dynamic information may impact
task-performance. Another variable that may impact task-performance is the size of
the virtual space. There are three broad areas for future work based on the size of
the virtual environment. These areas require users to maintain a frame of reference,
and span several application areas (see Figure 5.1). The three areas to assess relate to
applications ranging from computer-aided design, medical and scientific visualizations,
architecture, and 3D videogames.
5.2.1 Object space
First, 3D computer generated geometric entities that are categorized in the object
space should be evaluated. Object space is the smallest of the 3D virtual spaces to
evaluate; it encompasses objects which can be seen in their entirety from one vantage
point. Despite the small scale of the space, object space is cognitively demanding for
some users. As in the present work, future work should measure users’ abilities to
perceive 3D geometric entities and test methods to increase their accuracy in task-
performance.
The present work could be expanded by evaluating tasks that vary in difficulty,
including axes of rotation and object complexity, along with the presence of dynamic
and interactive displays. Future research should analyze visualizations that are pre-
sented as static images, dynamic animations, and fully interactive objects that respond
to user input. Fully interactive environments may not be necessary, and may be more
cognitively demanding for some users than dynamic displays which do not respond to
user input. Furthermore, some objects may be computationally expensive to animate
and interactivity may not always be possible. For these reasons it is important to assess
the three levels of interactivity in which objects can be presented to users.
The object manipulation space can also be used to determine whether the frame
of reference an individual maintains can improve his or her task-performance (see
Section 2.1.4 for a discussion on frames of reference). Users can either use an object-
based or viewer-based frame of reference as a basis for spatially updating an object.
Previous research has found that frames of reference can impact performance in a
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Size of Space Room Space Environment Space
Level of Interactivity Static, Animatedand Fully Interactive
Object−based
Application Areas Computer−Aided Designand Visualizations
or Viewer−based
Computer−Aided Design,Visualizations,
Object−based
Visualizations,Architecture,
and Architecture
Static, Animated,and Fully Interactive
Animatedand Fully Interactive
and 3D Videogames
or Viewer−based
Object Space
RequiredFrame of Reference
or Viewer−basedObject−based
Figure 5.1. Three sizes of spaces to analyze in future research. Application areasstated, as well as additional variables to evaluate.
virtual environment.
Users’ task performance could be affected depending on whether they use an object-
based or viewer-based reference frame in a virtual space. It is likely that object spaces
require users to rely on object-based transformations. Thus, an object-based cognitive
aid may be of more benefit to an individual than a viewer-based cognitive aid in
maintaining orientation in object space. Future research should test a viewer-based
aid to determine its effectiveness on a user’s ability to maintain the orientation of an
object.
5.2.2 Room space
The second component of future work could be to evaluate spaces that are larger
than the human body, but can still be perceived without substantial movement. This
scale of space, which is referred to as room space, is most closely tied to architecture.
Users’ task-performance with room sized virtual spaces that are presented as static
images, dynamic animations, and fully interactive spaces that respond to user input
could each be analyzed. As with object spaces, interactivity may not be a prerequisite
for users to gain information from a 3D virtual space. A static or dynamic scene may
provide sufficient information for a user to accurately perceive a room space.
Evaluation of object-based and viewer-based reference frames in the room space
would also be beneficial. It may be that when users are in a room space they interpret
the changes to the view of the room as viewer-based transformations. Room spaces
may require users to make judgments that involve their perspective in the room, which
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would cause a user to update his or her coordinate frame. Users’ may perform more
accurately in a room space when shown a cognitive aid that promotes a viewer-based
frame of reference. However, if an avatar is present and the user is viewing the room
from a third person perspective, an object-based reference frame may be used instead
of a viewer-based reference frame. In a third person perspective, the user may update
the avatar’s position in relation to other objects instead of updating his or her own
coordinate frame.
5.2.3 Environment space
Future research should also evaluate environments that require movement in order
to fully comprehend their size and structure. This environment space is applicable
to architecture (buildings, collections of buildings), visualizations (medical such as a
colon), and videogames (educational, serious games used for training). Since move-
ment is necessary in the environment space, evaluation is only necessary for dynamic
movement that uses passive animation and interactive movement that responds to user
input.
As with the other two sizes of spaces, users may perform better or just as accurate
with passive animation than with interactive manipulations. Some users may not
discover the most efficient way to navigate in the space and interactivity may distract
them from the purpose in which the application was intended. Again, evaluation of
how the frame of reference impacts a user’s ability to maintain orientation should be
considered. Since movement is required, a user may perform more accurately with
cognitive support that provides a viewer-based reference frame rather than an object-
based reference frame.
5.2.4 Evaluation of cognitive support
It is important to evaluate and quantify user performance in these three spaces
which range in size, complexity, level of dynamic information, and possibly frames of
reference. In each of these spaces users’ could benefit from cognitive support provided
by an in-scene visual aid. Various cognitive aids could be assessed, such as aids that
are presented as bounding boxes, avatars, or verbal cues such as words.
It is also important to take into account the variables analyzed in the present
research, including task, time pressure, axis of rotation, and users’ individual differences
in spatial abilities. We found that each of these factors may influence task-performance
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and the extent to which a user benefits from cognitive support. Future work could also
assess objects that are rotated more than 75◦. It may be that users have more difficulty
with objects that have larger degrees of disparity than objects that have smaller degrees
of disparity. For instance, a user may find that cognitive support is more beneficial for
objects with degrees of disparity of 145◦ than objects with degrees of disparity of 45◦.
Another variable to consider is the strategy a user takes to solve a task. The present
research indicates that users may utilize different strategies to solve the same task. Low
spatial users may rely on strategies that use cognitive support more than high spatial
users. Additionally, high spatial users may be able to more effectively use a wider
variety of strategies. Researchers could use eye tracking software to better evaluate
how strategies differ between high and low spatial abilities.
Lastly, evaluation of cognitive support with real applications can validate the em-
pirical findings found in this controlled experimentation. Future work could find that
cognitive support is more beneficial when implemented in a real 3D application than a
task-specific environment conducted using a systematic cognitive paradigm. By taking
these variables into account future research could increase the utility and effectiveness
of 3D computer graphics applications.
5.3 Contributions
The present research has demonstrated the use of a controlled methodology to
investigate users’ perceptions of visual imagery. Specifically, we have evaluated how
accurate users are at perceiving the orientation of 3D objects shown as multiple static
views. We implemented four different types of aids to determine which cues are most
effective in helping users maintain the orientation of an object displayed on a 3D
desktop display. We found that colocated aids are more effective than non-colocated
aids, and that static aids are more effective than dynamic aids.
Our results also suggest that variables such as axis of rotation, time pressure,
and a user’s spatial abilities may impact the effectiveness of a visualization. These
characteristics could effect the ease of use of a visualization; it is possible that a
visualization could be too difficult for a user to effectively gain information from
it. In order to overcome the difficulties users may have, it is imperative we evaluate
visualizations and the benefits of cognitive support.
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5.3.1 Theoretical contributions
The present work demonstrates how external visualizations can benefit from ideas,
principles, and methodologies from cognitive psychology. In turn, the present work
can also contribute to this area of research. We have validated several claims made by
researchers studying visuospatial thinking. First, we found that people have an easier
time mentally rotating objects about axes that are familiar in nature such as the vertical
axis. Second, we used the mental rotation paradigm in a novel way by evaluating objects
that are typically associated with medical visualizations and computer-aided design.
Our results are consistent with response time functions found in research conducted by
Shepard and Cooper [18] which used abstract blocks. Lastly, our results contribute to
the body of literature on individual differences in spatial ability.
Studying individual differences in task-performance is an established area of re-
search that is worth inquiry. We have found that differences in a person’s spatial skill
could transfer to his or her ability to use a 3D application such as a scientific visual-
ization. Many researchers have focused on individual differences in various contexts.
Snow [122] researched how an individual’s differences may influence the strategy
he or she uses to solve a problem. Snow [122] suggested that individuals use different
strategies to solve the same task. Additionally, an individual may use different strate-
gies as he or she adapts to solving a particular task. For example, with the paper
folding test (as explained in Section 3.3), one strategy to arrive at a response involves
the subject creating a mental image of the answer and then comparing his or her mental
image to the possible answers. This strategy is referred to as constructive matching.
Another strategy, called response elimination, involves a process of comparing features
of each possible answer and eliminating incorrect alternatives to arrive at the correct
answer by default [122].
Previous research suggests that high spatial ability learners will tend to use con-
structive matching and that constructive matching may be used more frequently on
easier test questions. Low spatial ability learners, however, may tend to use response
elimination and response elimination may be used more frequently on difficult test
questions. However, many subjects will use both strategies. Subjects may first attempt
to use constructive matching and then switch to response elimination as necessary.
Subjects may also switch back and forth between strategies. Whether a subject utilizes
different strategies and the extent to which they use different strategies may depend
on the range of difficulty of task items, the task, and a subject’s individual differences.
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The present research may validate these empirical findings. Whether or not a
subject used the orientation indicator depended on the difficulty of the trial, the task,
and his or her individual differences in spatial ability. High spatial ability learners may
be able to use certain strategies more effectively and a wider spectrum of strategies
than low spatial ability learners. For example, when the task is easy, high spatial
learners may not use the aid, whereas if task is difficult, they may switch their strategy
to a method that involves using the orientation indicator. Low spatial learners may
have consistently used strategies which included the colocated orientation indicator to
solve the task. However, when the trial was too difficult the orientation indicator may
not have provided an effective strategy to solve the task.
Furthermore, we found that low spatial ability subjects response times with a non-
colocated static aid were lower than high spatial ability subjects response times. This
result could be because low spatial subjects were using different strategies to solve the
task than high spatial subjects. Low spatial subjects may have been relying more on
response elimination strategies than high spatial subjects.
Low spatial ability subjects response times with a colocated static aid were the same
as high spatial subjects response times. This result may imply that the colocated aid
allowed low spatial subjects to solve the task using the same strategies that high spatial
subjects used. Cognitive support may be able to provide subjects with strategies that
are not feasible when the support is not present.
One way to view the results is to label high spatial users as “superior” to low
spatial users. However, a more appropriate stance may be to think of people as having
different cognitive styles of processing information. Kozhevnikova et al. [32] suggest
that there are three different types of cognitive styles, including people who prefer to
process information verbally, people who prefer to process visual information in terms
of the object properties (such as shape and color), and people who prefer to process
visual information in terms of spatial properties (such as location and spatial relations).
This three-dimensional cognitive style model is more appropriate than labeling people
as either verbal or visual as in the traditional bipolar Visual-Verbal cognitive style
model [123].
It may be that these three different groups rely on different aspects of visual imagery
to solve the same task. However, it is possible that individuals that prefer one cognitive
style may be able to use another cognitive style when given cognitive support. Our
results suggest that both spatial ability groups were more likely to visualize an object
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and not use verbal strategies when presented with a colocated static aid. In particular,
low spatial subjects may have been able to use visualization strategies more effectively
with a colocated aid versus a non-colocated aid.
5.3.2 Practical contributions
Designers can use the theories and results from empirical studies to improve the
design of 3D applications. The implications from this work extend to 3D computer-
aided design and medical visualization applications, as these applications could be made
more accessible to a broad population of users through the use of in-scene cognitive
aids. It is not sufficient for the designer to use his or her intuition alone when designing
3D applications. Even designers with the best intentions may over estimate the amount
of information a user attends to within a visualization. Designers may also assume a
user will look in a specific location within a scene, however users often do not see all
of the locations on the screen that contain relevant information.
To further complicate matters, users might make errors because they think they
have attended to all of the relevant information displayed and that they have an
accurate representation of an object. We found that users do not always attend to
visual cues which could help them solve a task. Furthermore, users may rely on different
strategies and various aspects of visual imagery to solve a task.
If users rely on different properties of an image to solve the same task, it is up
to the designer to provide relevant information that is accessible to everyone. By
understanding individual differences we can create better cues that will allow people
with various cognitive styles to effectively use a visualization. It is feasible to provide
visual cues to all users such that they can process information effectively. For instance
those who prefer to use object properties may take a holistic view and attend to the
entire image, whereas those who prefer to use spatial properties may segment an image
and attend to specific parts of a scene. Furthermore, those who prefer verbal processing
may benefit from additional instructions and cognitive aids that are verbal.
The present work demonstrates that users can benefit from additional information
to help them solve a task. In particular, we found that visualizations may vary in
difficulty because of time pressure, axes of rotation, and a user’s spatial ability. Each
of these factors could be addressed by providing users with cognitive support. We have
shown that colocated static indicators can benefit users viewing multiple static views
of an object. Additional methods could be created to support users in 3D desktop
72
environments.
The results of the present work not only give evidence for the need to evaluate 3D
applications with an awareness of individual differences, they also highlight the need to
quantitatively assess users’ performance in 3D virtual environments. We used a con-
trolled experimental paradigm to evaluate factors that may influence the effectiveness
of a visualization. This methodology allowed us to systematically determine the effects
of various orientation indicators and other characteristics that may impact a user’s
task-performance.
Using controlled experimentation allows practitioners to make informed decisions
when designing 3D tools. Evaluating the effectiveness of visualizations using only
commercial 3D applications could introduce unmanageable complexity from extraneous
variables, such as a user’s training and familiarity with 3D applications, design of the
user interface, and ability to modify the appearance of the interface. However, assessing
performance using both controlled experiments and user studies that evaluate real 3D
applications could be used together to ensure users will benefit from cognitive support
and 3D tools.
A user’s task performance will not necessarily improve simply because cognitive
aids such as orientation indicators are implemented. Three-dimensional environments
and orientation indicators can be improved by investigating users’ perceptions of the
3D geometric information. We have demonstrated the use of a cognitive experimental
paradigm for static images, but a similar methodological approach could be extended to
systematically evaluate non-interactive and interactive dynamic displays. This research
provides a basis for future studies that evaluate the use of orientation indicators.
By identifying users’ difficulties with 3D navigation and the benefits of additional
information we can make 3D environments more effective.
APPENDIX
EXPERIMENTAL INSTRUCTIONS
Prior to the experiment subjects were given written and oral instructions to the
task. A practice period followed these instructions.
A.1 Choose-two-of-four instructions
A.1.1 Written instructions
Welcome to the experiment.
At the start of every trial, you will see a cross followed by a set of images.
Your task is to compare the objects and determine which two objects are the same
as the target image.
Do the task as accurately as possible.
You will respond with the button box, you are to press the two keys on the button
box that map to two objects which are the same as the target image.
You will start with a series of practice trials.
A.1.2 Oral instructions
There will be five images on the screen, the leftmost image is the target image.
Your task is to determine which two out of the four images match the target image.
Begin by reading these written instructions, and then you will do two practice trials
with me. You are to respond as accurate as possible with each trial.
<experimenter advances screen>
At the start of each trial you will see a screen like this with a plus on it.
<experimenter advances screen>
Objects that you are to compare will then appear, your task is to determine which
two objects are the same as the target object. Here you can see that there are four
objects to the right of the target object, two of these objects are the same shape as the
target object but shown in different orientations. The other two objects are different
objects. There will always be two correct answers, there are no “tricks”.
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The shape of the two matching objects will be the same as the target object but
the objects may be rotated, meaning they are in a different orientation, or look look
lighter or darker.
We will do these first few examples together. You can respond with the button box
but nothing will happen since this is an example trial. You will notice there are four
buttons that map to each of the four images to the right of the bar. The last button is
labeled “skip”, you can use this button if you do not know one or both answers to the
trial. If you use this button, you will later be given a chance to retry that trial if time
permits.
First example: which two objects are the same as the target object? (correct
answers are 1 and 4) Good, you can see that objects 1 and 4 are the same as the target
object but are rotated, the other two objects are not the same as the target image. So,
had you been responding with the button box, you would click the 1st and 4th button.
DO NOT click both buttons at the same time!
Second example: In some trials you will be shown an orientation indicator. The
direction and amount of rotation of the indicator will correspond to the direction and
amount of rotation of the object. Notice that when the orientation of the object has
changed, so has the indicator. (correct answers are 1 and 3) Good, you can see that
objects 1 and 3 are the same as the target object but are in a different orientation,
the other two objects are different than the target image. The order you respond with
your answers does not matter, so for example you could have pressed the 3 and then
the 1. When you respond with your first answer a light will come on for the button
you pressed.
You will be given blocks of trials and each block has a specific time limit. You are
to correctly answer as many trials as you can in each block, however you may time out
and not finish a block of trials and that is OK.
So, respond as quickly as possible with two answers per trial and if you get stuck
you can respond with one answer and then press skip, or you can press the skip button
to exit the trial completely. If time permits you will have a second chance at answering
the skipped trials.
We do not want you to guess, respond when you are reasonably sure your answer
is correct. You will only be allowed to retry a skipped trial, so choose your responses
wisely.
You will now have two sets of practice trials that are just like the real experiment
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but shorter, however I will not give any feedback as to the correct responses. You can
use both hands to respond on the button box, and you can move the button box to a
position that is more comfortable for you if needed.
<let subject hit spacebar to continue with practice trials>
Any questions?
I will now leave the room and the real experiment will begin. You will have three
short breaks that will come between blocks of trials. During the breaks you are to read
these articles, you do not need to complete all three articles. When each break is over
you will be prompted to hit the spacebar to continue the experiment. This portion of
the experiment will take about 20 minutes.
You will see a screen that says thank you and goodbye, you can then come out and
find me. If at any time you have any questions or something goes wrong please come
out and find me.
Hit the spacebar to begin the experiment.
A.2 Same/different instructions
A.2.1 Static orientation indicator written instructions
Welcome to the experiment.
At the start of every trial, you will see a cross followed by a set of images.
Two objects will appear, your task is to determine whether the two objects are the
same or different.
Do the task as quickly and accurately as possible.
You will respond with the button box. Press either the ”same” or ”different” key.
You will start with examples and then a series of practice trials.
A.2.2 Static orientation indicator oral instructions
At the start of each trial you will see a screen like this with a plus on it.
<advance to next screen>
Two objects that you are to compare will then appear, your task is to determine
whether the two objects that follow are of the same object but they may be shown in
different orientations, or whether they are different objects.
So, the shape of same objects will be the same but they may be rotated (meaning
they are in a different orientation), and they may look lighter, darker, or brighter
depending on their orientation.
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<advance to next screen>
Can you tell me whether these objects are the same or different? This is an example
of two objects that are different. You cannot rotate one object to make it fit with the
other. No matter how you rotate the objects they will not be the same. Do you
understand why these two objects are different?
Yes − > advance to next example
No − > say no matter how you rotate them, they cannot be rotated into congruence
(fit) with each other
In some trials you will be shown an orientation indicator. The direction and amount
of rotation of the indicator will correspond to the direction and amount of rotation of
the object. Notice that when the orientation of the object has changed, so has the
indicator.
Here is an example of two objects that are the – <let subject try to respond> –
same. You can rotate one object to make it fit and match with the other object. Do
you understand how these two objects are the same?
Yes − > advance to practice
No − > say they are the same shape, only differ by a rotation
Next you will have a series of practice trials. You are to respond as fast and accurate
as possible with each trial.
There is a time limit for each trial, if you reach that limit the computer will advance
to the next trial.
I will stay in the room for the practice trials.
<subject does practice>
I will now leave the room and the real experiment will begin. It will take you about
20 minutes to complete. You will have one break, it is 2 minutes long. The break will
come halfway through the experiment. During the break you are to read these short
articles, you do not need to complete all the articles. When the break is over you will
be prompted to hit the spacebar to continue the experiment.
Any questions?
You will see a screen that says thank you and goodbye, you can then come out and
find me. If at any time you have any questions or something goes wrong please come
out and find me.
A.2.3 Dynamic orientation indicator written instructions
Welcome to the experiment.
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At the start of every trial, you will see a cross followed by a set of images.
Two objects will appear, your task is to determine whether the two objects are the
same or different.
In some trials you will be shown an orientation indicator. In those trials the
indicator will show the path of rotation between the two objects.
Do the task as quickly and accurately as possible.
You will respond with the button box. Press either the ”same” or ”different” key.
You will start with examples and then a series of practice trials.
A.2.4 Dynamic orientation indicator oral instructions
At the start of each trial you will see a screen like this with a plus on it.
<advance to next screen>
Two objects that you are to compare will then appear, your task is to determine
whether the two objects that follow are of the same object but they may be shown in
different orientations, or whether they are different objects.
So, the shape of same objects will be the same but they may be rotated (meaning
they are in a different orientation), and they may look lighter, darker, or brighter
depending on their orientation.
Can you tell me whether these objects are the same or different? This is an example
of two objects that are different. You cannot rotate one object to make it fit with the
other. No matter how you rotate the objects they will not be the same. Do you
understand why these two objects are different?
Yes − > advance to next example No − > say no matter how you rotate them,
they cannot be rotated into congruence (fit) with each other
As you will see in this next example, in some trials you will be shown an orientation
indicator. This indicator will be animated and show you the path of rotation between
the two objects.
<advance to next screen>
Do you think these two objects are the same or different?
As you saw the direction and amount of rotation of the indicator corresponded to
the direction and amount of rotation because the two objects are the same.
You can use the indicator to rotate one object to see if it fits and match with the
other object.
Do you understand how these two objects are the same?
78
Yes − > advance to practice
No − > say they are the same shape, only differ by a rotation
Next you will have a series of practice trials. You are to respond as fast and accurate
as possible with each trial.
There is a time limit for each trial, if you reach that limit the computer will advance
to the next trial.
I will stay in the room for the practice trials.
<subject does practice>
I will now leave the room and the real experiment will begin. It will take you about
20 minutes to complete. You will have one break, it is 2 minutes long. The break will
come halfway through the experiment. During the break you are to read these short
articles, you do not need to complete all the articles. When the break is over you will
be prompted to hit the spacebar to continue the experiment.
Any questions?
You will see a screen that says thank you and goodbye, you can then come out and
find me. If at any time you have any questions or something goes wrong please come
out and find me.
A.3 Written survey
At the end of the computer portion of the experiment each subject completed this
written survey that is similar to the survey given in Peters et al. [93]. Subjects were
asked to check one answer per question.
1. I rotated the whole figure in my mind when making the comparison
I rotated a section of the figure in my mind when making the comparison
I am not sure how I did it
Other (explain)
2. I thought through the steps verbally in my mind (i,e. ”shorter part up and
longer part down”)
I relied mainly on visualizing the figures and did not talk myself through the
steps
I am not sure
79
3. I used movements of my finger, hand, and/or head to help me with the task
I did not use movements of my finger, hand, and/or head to help me with the
task
4. I developed a specific approach to solve the problems
I tried various approaches to solve the problems
I had no specific approach
5. I was more concerned with getting the right answers than I was about the time
limit
I was more concerned with getting all the answers completed than I was about
getting the correct answers
I did not care how I did
6. My confidence level remained the same throughout the experiment
My confidence level was higher with the orientation indicator
My confidence level was higher without the orientation indicator
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