Two-handed input using a PDA and a mouse.
We performed several experiments using a Personal Digital Assistant (PDA) as an input device in the non-dominant hand along with a mouse in the dominant hand. A PDA is a small hand-held palm-size computer like a 3Com Palm Pilot or a Windows CE device. These are becoming widely available and are easily connected to a PC. Results of our experiments indicate that people can accurately and quickly select among a small numbers of buttons on the PDA using the left hand without looking, and that, as predicted, performance does decrease as the number of buttons increases. Homing times to move both hands between the keyboard and devices are only about 10% to 15% slower than times to move a single hand to the mouse, suggesting that acquiring two devices does not cause a large penalty. In an application task, we found that scrolling web pages using buttons or a scroller on the PDA matched the speed of using a mouse with a conventional scroll bar, and beat the best two-handed times reported in an earlier experiment. These results will help make two-handed interactions with computers more widely available and more effective.
INTRODUCTION
Many studies of two-handed input for computers have often
shown advantages for various tasks [1, 3, 7, 9, 15].
However, people rarely have the option of using more than
just a mouse and keyboard because other input devices are
relatively expensive, awkward to set up, and few applications
can take advantage of them. However, increasing
numbers of people now do have a device that they carry
around that could serve as an extra input device for the
computer: their Personal Digital Assistant (PDA). PDAs,
such as 3Com's Palm Pilots and Microsoft's Windows CE
devices, are designed to be easily connected to PCs and
have a touch-sensitive screen which can be used for input
and output. Furthermore, newer PDAs, such as the Palm V
and the HP Jornada 420, are rechargeable, so they are supposed
to be put in their cradles next to a PC when the user
is in the office. Therefore, if using a PDA in the non-dominant
hand proves useful and effective, it should be
increasingly easy and sensible to deploy and configure using
hardware devices that users already have.
Another advantage of PDAs over the input devices studied
in previous experiments is that they are much more flexi-
ble. PDAs have a display on which virtual buttons, knobs
and sliders can be displayed, and they can be programmed
to respond to a wide variety of behaviors that can be well-matched
to particular tasks. However, a disadvantage is
that the controls on the PDA screen are virtual, so users
cannot find them by feel. Research is therefore needed to
assess how well the PDA screen can work as a replacement
for other input devices that have been studied for the left
hand.
This paper reports on several experiments that measure
various aspects of using a PDA as an input device in the
non-dominant hand. Two experiments are new and are designed
to measure the parameters of using a PDA. One
experiment repeats an earlier study but uses a PDA in the
non-dominant hand. Since the actual pragmatics of input
devices can have a large impact on their effectiveness [2,
8], we wanted to determine whether the results seen in
prior experiments would also apply to using PDAs.
In summary, the results are:
x People can quickly and reliably hit large buttons drawn
on the PDA with their left hands without looking. 99%
of the button taps were correct on buttons that are 1-inch
square in a 2x2 arrangement. With a larger number of
smaller buttons, the accuracy significantly decreases:
95% were correct for 16 buttons that are  inch on a
side arranged 4x4. The time from stimulus to button tap
Submitted for Publication

was about 0.7 sec for the large buttons and 0.9 seconds
for the smaller buttons.
x In a task where the subjects had to move both hands
from the keyboard to the PDA and the mouse and then
back, we found that it took an average of 0.791 seconds
to move both hands from the devices to the keyboard.
This was about 13% longer than moving one hand from
the mouse to the keyboard (which took 0.701 sec).
Moving to a PDA and mouse from the keyboard took an
average of 0.838 seconds, which is about 15% longer
than moving one hand to the mouse (0.728 seconds).
x In a repeat of the experiment reported in [15], subjects
were able to scroll large web pages and then select a link
on the page at about the same speed using buttons or a
scroller on a PDA compared to using the mouse with a
conventional scroll bar. The times we found for scrolling
with buttons on the PDA were faster than any of the
times in the earlier study, including the 2-handed ones.
RELATED WORK
There have been many studies of using input devices for
computers in both hands, but none have tested PDAs in the
left hand, and we were unable to find measurements of
homing times from the keyboard to devices for two-handed
use.
One of the earliest experiments measured the use of two
hands in a positioning and scaling task and for scrolling to
known parts of a document [3]. This study found that people
naturally adopted parallel use of both hands and could
scroll faster with the left hand. Theoretical studies show
that people naturally assign different tasks to each hand,
and that the non-dominant hand can support the task of
the dominant hand [6]. This has motivated two-handed
interfaces where the non-dominant hand plays a supporting
role, such as controlling other drawing tools [9] and
adjusting translation and scaling [3, 15]. Other studies
have tested two-handed use for 3D interaction [1, 7] and
found the extra input to be useful.
There has been prior work on using PDAs at the same time
as regular computers for various tasks including meeting
support [11], sharing information [12], and to help individuals
at their desks [10], but we found no prior work on
measuring performance of non-dominant hand use of
PDAs.
Two new studies were performed. In the first, the subjects
did five tasks in a row. The first task was a typing test to
see how fast the subjects could type. Next, they performed
a button size task to measure the error rates and speeds
when tapping on different size buttons on the PDA. Next,
the subjects performed a homing speed task where we
measured the how quickly the subjects moved among the
keyboard and the devices. Finally, they performed a
scrolling task using a variety of devices, which is a repeat
of an earlier experiment [15]. The subjects reported a
number of problems with the scrolling devices on the PDA
in the last task, so we redesigned the scrolling devices, and
in a second study with new subjects, we evaluated the performance
of the new scrollers on the same task. Each of
these experiments is described below.
Apparatus
Subjects sat at a normal PC desktop computer that was
running Windows NT. On the right of the keyboard was a
mouse on a mouse pad. On the left was an IBM WorkPad
8602-30X PDA (which is the same as a Palm IIIx). In the
first study, we put the WorkPad in its cradle. Subjects
complained that the WorkPad was wobbly it its cradle, so
for the second study, the new subjects used a WorkPad
resting on a book and connected by a serial cable to the
PC. There were no further comments about the positioning

The WorkPad has a 3-inch diagonal LCD display screen
(about 2  inches on a side) which is touch sensitive. It is
pixels. Figure 1 shows a picture of the full Work-
Pad.
The software running on the WorkPad was the Shortcutter
program [10] that allows panels of controls to be created so
that each control sends specified events to the PC. The
software on the PC consisted of various applications specifically
created for this experiment (except in the scrolling
task, which used the Netscape browser running a custom
JavaScript program to collect the data).
Typing Test
We used a computerized typing test called "Speed Typing
Test [14]. The subjects were asked to type a paragraph
displayed on the screen as quickly as possible.
Button Size Task
In this task, the PDA displayed between 4 and 16 buttons
in eight different arrangements: 2 rows by 2 columns, 2x3,
3x2, 2x4, 4x2, 3x4, 4x3, and 4x4 (see Figure 1). To control
for ordering effects, half of the subjects used the order
shown above, and the other half used the reverse order
(4x4 first down to 2x2 last). In the 2x2 condition, the buttons
were about one inch square, and in the 4x4, they were
about  inch square.
At the beginning of each condition, a picture was displayed
on the PC screen showing the corresponding layout
of the buttons (with the same size as the PDA). Then one
of the buttons was shaded black (see Figure 2). The subjects
were asked to tap on the corresponding button on the
WorkPad as quickly and accurately as possible with a finger
on their left hand. The stimulus button was then
cleared on the PC and the next stimulus button was shaded
500 milliseconds later. The stimuli appeared in random

order. A total of 48 stimuli were used in each condition.
Every button appeared the same number of times. For ex-
ample, for the layout of 2 rows by 2 columns, each button
appeared 12 times, while for the layout of 3 rows by 4 col-
umns, each button appeared 4 times. There was a break
after each condition. Our hypotheses were that people
could more accurately select among fewer, larger buttons,
and that people could make selections without looking at
the WorkPad.

Figure

1. Left: a picture of a Palm Pilot (the WorkPad is simi-
lar) showing the 2x2 layout of buttons. Right: the screens for
3x2, 2x3, 4x3 and 4x4. The other layouts are similar.

Figure

2. Part of the PC screen showing the stimulus during the
4x3 condition of the button task.
Homing Speed Task
The purpose of this task was to measure the times to move
the hands back and forth from the keyboard to the mouse
and WorkPad as the subjects switch between two-handed
selection operation and two-handed typing. We compared
moving a single hand to and from the keyboard to moving
both hands.
There were three conditions with three trials in each. In
each trial, 14 textboxes were shown on the screen with a
label in front of each. The conditions were that the subjects
had to first select a text box by either clicking in the field
with the mouse in the usual way, tapping on a full-screen
button on the WorkPad (which therefore worked like a
"TAB" key and caused the cursor to jump to the next
field), or tap on the WorkPad and click the mouse at the
same time. In other words, the selection operation in this
last condition was like a "Shift-Click" operation in which
the button on the WorkPad was treated as a Shift key. After
the textbox was selected, the subjects typed the word
indicated on the left of the textbox. The word was either
"apple" or "peach" (in alternating order). These words
were chosen because they are easy to type and remember,
and they start and end with keys that are under the opposite
hands. The user could not exit the field until the word
was typed correctly. After typing the word correctly into
the textbox, the subject then continued to perform the same
selection-typing operation in the next textbox. The trial
ended when all 14 textboxes on the screen were filled in.
There was a break after each trial. We measured the time
from the mouse and WorkPad click to the first character
typed, and from the last character typed to the first movement
of the mouse or tap on the WorkPad. We did not
count the time spent actually typing, and we eliminated the
times for the first and last words, because they were biased
by start-up and transients.
We hypothesized that moving to the WorkPad and the
mouse would not take much longer than moving one hand
since people would move both hands at the same time. We
were also interested in the actual numbers for the time
measurements. These might be used with future models of
human performance for two-handed homing tasks.
(a) (b) (c)

Figure

3. (a) The button scroller on the WorkPad used in the
first experiment. (b) The Slide Scroller and (c) Rate scroller used
in both experiments.
Scrolling Task
For this task, we were able to replicate the conditions of a
previous experiment [15] exactly. 1 The purpose of this task
was to evaluate and compare subjects' performance in
scrolling web pages in a standard browser using different
scrolling methods. The web pages contain text from an
IBM computing terminology dictionary, and each page is
about 12 screen-fulls of text. In each web page a hyperlink
with the word "Next" is embedded at an unpredictable lo-
cation. The subjects were asked to find the target hyperlink
by scrolling the web page using the different scrolling
mechanisms. Once the link was visible, they used the
mouse in the conventional way to click on it. Clicking on
the hyperlink brought the subject to the next web page. For
each condition, the subjects first performed a practice run
of pages, during which they were asked to try out the
scrolling method without being timed. Then, the subjects
did two consecutive trials of 10 pages each as fast as they
could.
Thanks very much to Shumin Zhai of IBM for supplying the experimental
material from the earlier study.
(a) (b)

Figure

4. (a) The revised button scroller on the WorkPad used
in the second experiment. (b) The "absolute scroller".
The condition with the fastest time in the previous experiment
used a "pointing stick" joystick to scroll, but we were
not able to reproduce this condition. 2 The conditions we
used in our first experiment were:
x Scrolling using the mouse and the regular scroll bar.
x Scrolling using a "scroll wheel" mounted in the center
of the mouse (a Microsoft "IntelliMouse"). We were
careful to explain to the subjects the three different ways
the wheel can be used, including rolling the wheel, or
tapping or holding the wheel down to go into "scroll
mode" where the further you move the mouse from the
tap point, the faster the text scrolls. The subjects could
choose which methods to use.
x Scrolling using buttons on the WorkPad (see Figure 3a).
There were 6 buttons that scrolled up and down a line,
up and down a page, and left and right (which were not
needed for this experiment). The buttons auto-repeated
if held down.
x Scrolling using a "slider" on the WorkPad (see Figure
3b). Putting a finger on the slider and moving up or
down moved the text the corresponding amount. If you
reach the edge of the slider, then you need to lift your
finger and re-stroke. Tapping on the slider has no effect
since only relative movements are used.
x Scrolling using a "rate scroller," which acted like a rate-controlled
joystick with three speeds (see Figure 3c).
Putting a finger on the WorkPad and moving up or
down started the text moving in that direction, and
moving the finger further from the start point scrolled
faster.
The order of the conditions was varied across subjects.
Revised Scrolling Task
We received a number of complaints and suggestions about
the scrollers on the WorkPad in the first session, so we re-designed
some of them and repeated the scrolling task in a
second study with new subjects. In this study, we only used
four buttons for the button scroller (since the left and right
We did not have a pointing stick to test, and anyway, it would have been
difficult to connect one to the computers we had, which illustrates one of the
claims of this paper-it can be difficult to connect multiple conventional
input devices to today's computers. Since the experimental set up was identical
to the original experiment [15], it should be valid to compare our times
with the times reported there.
buttons were not needed-see Figure 4a). We also tried to
improve the rate scroller, by adjusting the scroll speeds
and the areas where each speed was in affect. Finally, we
added a new (sixth) condition:
x Scrolling using an "absolute scroller," where the length
of the scroller represented the entire document, so putting
a finger at the top jumped to the top of the
document, and the bottom represented the bottom (see
Figure 4b). The user could also drag up and down to
scroll continuously. Therefore, it was as if the scroll
bar's indicator was attached to the finger. The motivation
for this scroller was that we noticed that most
people in the mouse condition of the first session
dragged the indicator of the scroll bar up and down, and
we wanted to provide an equivalent WorkPad scroller.
Subjects
There were 12 subjects in the first study, which took about
an hour and they were paid $15 for participating. 12 different
subjects did the second study, which took about
hour and they were paid $10. All subjects were Carnegie
Mellon University students, faculty, or staff. 25% (6 out of
were female, and the age ranged from 19 to 46 with a
median of 26. All were moderately to highly proficient
with computers, and half had used PDAs. The data from
some extra subjects were eliminated due to technical diffi-
culties. The measures from two subjects who were left-handed
are not included in the data, but informally, their
numbers did not look different.
General
Pearson product-moment correlation coefficient between
typing speed and tap speed in the button size task (namely
the mean tap speed across all 8 layouts) was .60, which
means the faster typists were somewhat faster at tapping.
The correlation coefficient between typing speed and the
speed for moving one hand to the keyboard in the homing
task was .79 which means, as expected, subjects who were
better typists could put their hands in the home position
more quickly. There was little correlation of typing speed
to the other measures in the homing task. The correlation
coefficient between typing speed and scrolling speed (in
the revised scrolling task) across all 6 conditions and both
trials was 0.32, which means there was little correlation
for the scrolling task.
Age and gender did not affect the measures.
Button Size Task

Figure

5 shows the times to tap on the button measured
from the time the stimulus appeared on the PC monitor.
These numbers only include correct taps. There were two
orders for the trials, so each condition was seen by some
subjects early in the experiment, and by other subjects
later. The chart presents the data for the early and late
cases along with the average of both.
msec
Ear ly Late Ave r age

Figure

5. Times to tap each button depend on the size. The
times are shown for the subjects who saw each condition later.

Figure

6. Plot of all times for the 2x2 layout shows (on the left)
learning happening for those subjects who saw this condition
first, but not (on the right) for those who saw it last.

Figure

6 shows the times to tap on a button in the 2x2 trial
for each of the buttons for each of the subjects. The left
graph is of those subjects who saw the 2x2 condition first,
and roughly matches the power law of practice. However,
for those subjects who did the 2x2 condition last, there was
no apparent learning during that trial, and the times are
flat. Therefore, we feel it is more valid to use the times
from only the subjects who saw the condition later. The
average time for just the second set is 593msec.
As shown in Figure 5, and predicted by Fitts's law [5, p.
55], the time to tap on a button is inversely proportional to
the size of the button, ranging from 593 msec in the 2x2
condition to 867 msec in the 4x4 (for those the subjects
who saw each condition later).
The times to tap differ significantly among different numbers
of buttons There is significant
interaction between button number and order of conditions
(2x2->4x4 or 4x4->2x2) but the
learning effect is most prominent among layouts with
small number of buttons. The Tukey Test at .05 significant
level indicates that there is no significant difference between
the 4-button condition and the 6-button condition,
between the 6-button and 8-button, or between the 8-button
and 12-button. However, the 12-button condition is faster
than the 16-button condition by a statistically significant
margin.
The times for different layouts of the same number of buttons
is not statistically significant, however: the Tukey
Test at .05 significant level indicates that times for the 2u3
are not statistically different from 3u2, 2u4 compares to
4u2, and 3u4 compares to 4u3.

Figure

7 shows the error rates for the various configura-
tions, which varies from 1.04% to 4.17% for the subjects
who saw each condition later. The error rates do not differ
significantly among different layouts
among different numbers of buttons p=.07). For
the 4u4 layout, 45% of the errors were in the wrong row,
48% were in the wrong column, and 7% were wrong in
both (on the diagonal from the correct button). There was
no consistent pattern of where the problematic buttons
were located (see Figure 8).
1.04 2.08 4.17 2.43 2.08 2.43 4.17020406080100
percent
Ea r ly La te Ave ra ge

Figure

7. Error rates for each condition of the button task.
Numbers shown are for the subjects who saw each later.

Figure

8. Percent of the taps in each button that were in error in
the 4x4 layout.
Homing Speed Task

Figure

9 shows the times for moving each hand in the
various conditions of the homing speed task. When moving
only one hand at a time (top 4 rows), the subjects took
728 msec to move to the mouse and 701 msec to move
back to the keyboard from the mouse. The times to move to
the PDA were 744 msec to the PDA and 639 back.
When required to move both hands, the subjects took only
slightly longer, requiring about 15% more time to acquire
both the PDA and the mouse (838msec), and about 12%
more time to acquire the keyboard (791 msec).
1H Keyboard->Mouse 728
1H Keyboard->PDA 744
1H Mouse->Keyboard 701
1H PDA->Keyboard 639
Keyboard -> Mouse&PDA 838 15.1%
Mouse&PDA -> Keyboard 791 12.8%

Figure

9. Times in milliseconds to move hands. "1H" means
when only one hand is moving. The third column shows the percent
slowdown of moving both hands compared to the
corresponding one-handed mouse time.
Scrolling Task
As in the study we reproduced [15], the time for the first
trial with each input device was for practice, so Figure 10
shows the times for the second and third trials.
8.33%
5.56%
2.78%
Key:
Rates:
msec
msec
.2
.3
8 9 .4
s ec
ous e S cro W heel B ut ton S cr ol er S de S cro er R at e S cr ol er

Figure

10. Times in seconds to scroll through 10 pages in trials
2 and 3 of the first version of the web page scrolling task using
different input devices.
.4
.3
.3
ous e Scr ol W hee B u tton S cr ol er
l de Scr ol er R ate Scr ol er

Figure

11. Ratings of the various input methods by the subjects
in the first version of the scrolling experiment. We used the same
scale as [15].
A repeated measure variance analysis shows that subjects'
completion time was significantly affected by input method
significantly faster
than Trial 2 showing a learning ef-
fect. However, this improvement did not alter the relative
performance pattern of the input method
Taking the Mouse condition as the reference and averaging
over both trials, the scroll wheel, the Slide Scroller,
and the Rate Scroller conditions were 28, 11, and 48 percent
slower. The Tukey Test at .05 significant level
indicates that the difference between mouse and scroll
wheel conditions, between the mouse and button scroller,
and between the mouse and slide scroller conditions were
not significant, while the difference between mouse and
rate scroller conditions was significant.

Figure

11 shows the subjects' ratings of the various scrol-
lers using a rating scale from Zhai et. al. [15]. Contrary to
the results of that previous study, the Tukey Test at .05
significant level indicates that the difference between ratings
of mouse and scroll wheel was not significant.
Subjects gave the mouse a significantly higher rating than
the slide scroller, while the difference between ratings of
mouse and button scroller and the difference between ratings
of between mouse and rate scroller were not
significant. Subjects gave the scroll wheel a significantly
higher rating than slide scroller and rate scroller, while the
difference between ratings of scroll wheel and button
scroller was not significant. The differences of ratings
among the three Pebbles scrollers were not significant.
Revised Scrolling Task
We were not happy with the performance of the scrollers
on the PDA, and the subjects provided useful feedback on
ways to improve them. Therefore, we performed iterative
design on the software, and tried the scrolling task again
with 12 new subjects. Figure 12 shows that we were able to
improve the performance of the new versions of the button
scroller, but the rate scroller may be worse. The new absolute
scroller was quite fast. The ratings of the new
versions are shown in Figure 13 and parallel the performance

6 9 .4
.3
sec
Mouse S cr ol Wheel B ut t onS cr ol er S deS cr ol er R ateS cr ol
l er AbsS cr ol er

Figure

12. Times in seconds to scroll through 10 pages in trials
2 and 3 of the second version of the web page scrolling task.
ous e Scr ol W hee B u tton
Scr ol er
de Scr ol er R ate Scr ol er Abs S cr ol er

Figure

13. Ratings of the various input methods by the subjects
in the second version of the scrolling experiment.
A repeated measure variance analysis showed that subjects
completion time was significantly affected by input method
Taking the Mouse condition as the
reference and averaging over both trials, the button scroller
was 8 percent faster but the Tukey Test at .05
significant level indicates that such difference is not sig-
nificant. The scroll wheel, the absolute scroller, the slide
scroller, and the rate scroller conditions were 31, 7, 12,
and 64 percent slower than the standard mouse condition.
The Tukey Test at .05 significant level indicates that the
difference between mouse and scroll wheel conditions and
the difference between mouse and rate scroller conditions
were significant, while the difference between mouse and
absolute scroller conditions and between Mouese and slide
scroller conditions were not significant.
great
very good
good
poor
very poor
terrible
great
very good
good
poor
very poor
terrible

DISCUSSION
Button Size
The subjects were able to hit buttons quite accurately with
their left hand, especially for small numbers of buttons.
The predicted decrease in performance with decreased
button size was observed. There seems to be a threshold of
about 12 buttons before there is any affect due to the size.
We believe that we achieved expert performance (the
learning curve flattened out) by the end of the experiment,
so we tried using the times in models of expert human
performance. One candidate is Fitts's law, but we do not
know exactly where the subjects' fingers were when they
started to move to tap. Assuming a movement of about 2
inches and a target size of 1 inch (in the 2x2 case), Fitts's
law as formulated in [5, p. 55] predicts a movement time
of about 150msec, compared to our measurement of
593msec. In our task, however, there is also perception
and thinking time. For the smaller buttons ( inch in the
predicts an increase in time of
about 100msec, but we saw an increase of about 275msec.
We observed that subjects looked back and forth from the
monitor to the PDA, at an increasing rate depending on
the number of buttons to choose from. Therefore, we believe
the performance cannot be modeled simply as a
Fitts's law task, but we were unable to find an appropriate
alternative model.
Our results showing that users can tap up to 12 buttons accurately
and quickly with the left hand is relevant since
there are a number of applications where having several
buttons on the PDA would be useful. Examples include
scrolling with buttons (Figure 3a and Figure 4a), and panels
created with the Shortcutter tool for controlling a
compiler, playing music on the PC, reading mail, etc. [10].
Homing Times
Our one-handed homing time to move from the mouse to
the keyboard (701 msec - see Figure 9) is longer than the
time to move from the PDA to the keyboard (639 msec).
This may be because the physical distance to the mouse
from the home position on the keyboard is longer (14
inches compared to 7 inches) due to the number-pad and
arrow keys sections of the PC keyboard. In the other direc-
tion, the increased time to acquire the PDA may be due to
the unfamiliarity of homing to this kind of device.
In the classic study of text selection devices [5, p. 237], the
homing time to move from the space bar to the mouse was
measured as 0.36 seconds. This was measured from
videotapes of subjects moving. An average homing time of
0.4 seconds was incorporated into the Keystroke Level
Model [4]. However, we measured one-handed homing
times of around 0.7 seconds, which is substantially longer.
Our time was measured from the time of the mouse click
to the time that the first keystroke was recognized. Our
typing test shows that the average time per keystroke was
seconds, so this might be subtracted from our measured
time to get the predicted 0.4 seconds.
An important observation is that, as predicted, subjects
moved both hands simultaneously, and this did not penalize
the movement time much. The sum of the one-handed
times to move from mouse and PDA to the keyboard is
1340msec (701+639). This is much larger than the time to
move from both mouse and PDA to the keyboard in the
two handed case which is 791 msec (1340msec is 69%
larger). A similar relationship holds for the movement
from the keyboard to the PDA and mouse
(728+7443=1473 > 838; 76% larger).
it takes only about 15% longer to acquire both the
mouse and the PDA than just to acquire the mouse, and it
takes only about 13% longer to get back to the keyboard
from both devices than from just the mouse.
We were not able to find any prior studies of the time to
acquire two devices at the same time. Most studies of two-handed
use of input devices (including our button-size and
scrolling tasks) allow the subjects to stay homed on the de-
vices. We found that moving both hands slowed down each
hand a little, but there was substantial parallel movement.
Realistic tasks are likely to include a mix of keyboard and
other input device use, so homing issues may be important.
Scrolling
Our measured times for scrolling the web pages with the
mouse (about 60 seconds) is a little faster than the time
reported in [15], and in the revised web task, the time for
scrolling with the button scroller is 45.9 sec (average of
trial 2 and trial 3) which is faster than the time for scrolling
with the in-keyboard isometric joystick (around 50
sec). This shows that using the PDA can match or beat the
speed of other non-dominant hand devices.
An interesting comparison is between their joystick, our
Rate Scroller (Figure 3c) and the scroll wheel used in its
most popular manner as a rate-controlled scroller. All provide
the same rate-controlled style of scrolling, but they
have significantly different performances and ratings by
users. Our attempt to improve the rate scroller obviously
did not help, showing that further work is needed to make
this scrolling method effective. We observed that the fast
speed was much too fast, but the medium speed was too
slow. The popularity of the scroll wheel and the success of
the pointing stick give us reason to keep trying. Further-
more, IBM did significant experimentation and
adjustments before the pointing stick had acceptable performance
[13]. Therefore, an important conclusion from
the scrolling experiment is that the specific design and
pragmatics of the input methods has a very important influence
on the performance.
Another interesting result is that our subjects quite liked
the scroll wheel (average rating of 1.7 | very good),
whereas in the earlier study it was rated much worse (-1 |

poor) [15]. This may be due to the increased experience
people have with a scroll wheel (many of our subjects have
a scroll wheel on their own mouse), and because most of
our subjects used it in its rate-controlled joystick mode,
whereas most of the earlier study's subjects used the rolling
mode.
An interesting observation about this Web scrolling task in
general is that it primarily tests scrolling while searching
for information, so the scrolling must go slow enough so
the subjects can see the content go by. This is why the
methods that provided the best control over the speed are
preferred. The low rating of the rate scroller on the PDA is
because the fastest speed was much too fast to see the text
go by, and the medium and slow speeds were rated as too
slow. However, other scrolling tasks, such as those tested
by [3], require the user to go to a known place in the
document, and then a method that can move long distances
very quickly may be desirable.
CONCLUSIONS
Many studies have shown the effectiveness of two-handed
input to computers in certain tasks. One hindrance to two-handed
applications has been that there may be only a few
tasks in which using both hands is beneficial, and the
benefits are relatively minor. Another problem is that although
it is interesting to study custom devices for use by
the non-dominant hand, in order for there to be wide-scale
use, it is better to provide mechanisms that users can easily
get and configure. Since increasing numbers of people
have PDAs that are easy to connect to PCs, it makes sense
to see if PDAs can be used effectively in the non-dominant
hand. The research presented here shows that PDAs can be
used as buttons and scrollers, and that the time to home to
two devices is only slightly longer than for one. Our study
of one application shows that at least for the scrolling task,
a PDA can match or beat other 1-handed and 2-handed
techniques. Because there is no incremental cost for the
PDA since users already own it, and since the PDA is connected
to the PC anyway, even small efficiencies many be
sufficient to motivate its use as a device for the non-dominant
hand. Our studies and many others have emphasized
the importance of the pragmatics and the exact
behavior of controls. Because the PDA can be programmed
with a variety of controls with various properties, further
research is required to determine the most effective ways
that a PDA can be used to control the PC in both the
dominant and non-dominant hand.

ACKNOWLEDGMENTS

For help with this paper, we would like to thank Rob Miller,
Bernita Myers and Shumin Zhai.
The research reported here is supported by grants from DARPA, Microsoft,
IBM and 3Com. This research was performed in part in connection with
Contract number DAAD17-99-C-0061 with the U.S. Army Research Labo-
ratory. The views and conclusions contained in this document are those of the
authors and should not be interpreted as presenting the official policies or
position, either expressed or implied, of the U.S. Army Research Laboratory
or the U.S. Government unless so designated by other authorized documents.
Citation of manufacturer's or trade names does not constitute an official endorsement
or approval of the use thereof.



--R

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ubiquitous computing;two-handed input;hand-held computers;Windows CE;personal digital assistant PDAs;palm pilot;pebbles;smart environments