Twiddler Typing: One-Handed Chording Text Entry for
Mobile Phones
Kent Lyons, Thad Starner, Daniel Plaisted,
James Fusia, Amanda Lyons, Aaron Drew, E. W. LooneyCollege of Computing and GVU Center
Georgia Institute of Technology
Atlanta, GA 30332-0280 USA{kent,thad,plaisted,visyz,amandal,adrew,ewlooney}@cc.gatech.edu

ABSTRACTAn experienced user of the Twiddler, a one–handed chording keyboard, averages speeds of 60 words per minute withletter–by–letter typing of standard test phrases. This fast typing rate coupled with the Twiddler’s 3x4 button design, similar to that of a standard mobile telephone, makes it a potential alternative to multi–tap for text entry on mobile phones.
Despite this similarity, there is very little data on the Twiddler’s performance and learnability. We present a longitudinal study of novice users’ learning rates on the Twiddler.
Ten participants typed for 20 sessions using two different
methods. Each session is composed of 20 minutes of typing
with multi–tap and 20 minutes of one–handed chording on
the Twiddler. We found that users initially have a faster average typing rate with multi–tap; however, after four sessions
the difference becomes negligible, and by the eighth session
participants type faster with chording on the Twiddler. Furthermore, after 20 sessions typing rates for the Twiddler are
still increasing.
Author Keywords

Text entry, mobile phones, chording, multi–tap, keypad input
ACM Classification Keywords

H.5.2 User Interfaces: Input devices and strategies
INTRODUCTION

With 1.32 billion users, mobile phones have become ubiquitous in many parts of the world [4]. Similarly, the use ofwireless text messaging is becoming widespread, with predictions of a rate of over 1 trillion messages per year being
reached shortly [6, 12]. These statistics are remarkable considering the inefficiencies and poor design of current text entry methods for mobile devices.
With wireless messaging revenues at stake in the tens of billions of US dollars, mobile phone manufacturers can differentiate their products with text entry methods that are faster,easier to learn, less physiologically stressful, or more convenient than competitors’ products. For example, in a recent
survey, 92% of 15-40 year old mobile phone users statedthat speed was important when sending and receiving messages [3]. Increased text entry speed may also open newmarkets for wireless email, which is desired by 81% of consumers surveyed [3]. Wireless email is predicted to drive thenext stage of the industry’s European data revenues [4]. Increased text entry speeds may also help unexpected segmentsof the user population. For example, the Deaf population has
adopted wireless texting as a convenient means of communication within the community.
In this paper, we demonstrate a chording method of text entry
on a 3x4 button keypad where expert rates average 60 wpm
on letter–by–letter entry. We show that chording novices average over 26 wpm after 400 minutes of practice and haverates comparable to their multi–tap rates within 80 minutesof practice. Finally, we discuss how this chording method
may be incorporated into a mobile phone design.
Multi–tap

One common mobile phone text entry method is multi–tap, asystem in which multiple letters are mapped to the same key
and the user presses that key to cycle through the letters until
the desired one appears on the screen. Users hold the keypad towards them and can enter text with one or two hands
using one or two fingers/thumbs. Once the desired letter appears, users can press the next key to start the process again
for the next letter, wait for the timeout, or use a kill key function. This is a feature that deactivates the current key after
a specified amount of time. Previous research has predictedmaximum expert words-per-minute (wpm) typing rates of 20
to 27 wpm [14]. Usability studies have found rates of 15.5
wpm [9] and 5.3-10.5 wpm [5] which are far below manyother keyboard input devices.
Chording

Many wearable computer users [7, 17] type with the HandyKey
Twiddler (Figure 1). This is a mobile one–handed chording
keyboard with a keypad similar to a mobile phone. It has
twelve keys arranged in a grid of three columns and four rows
on the front of the device. Each row of keys is operated by
one of the user’s four fingers. Additionally, the Twiddler has
several modifier buttons such as “Alt” on the top operated by
the user’s thumb. Users hold the device in the palm of theirhand like a cup with the keys facing away from their bodies.
All five fingers on a hand can be used to type. Unlike multi–

tion of the chording layout from the user’s perspective.
We collected data of an expert Twiddler user typing at an
average rate of 60 wpm on a letter–by–letter basis (no multi–
character chords); this is far faster than reported multi–tap
values. This higher achievable text entry maximum coupledwith the affordances of the same button layout as mobile
phones suggests that the Twiddler has great potential as areplacement text entry mechanism for mobile phones.

Figure 1: On the left, typing using multi–tap on the Twiddler keypad. On the right, chording with the Twiddler
one–handed keyboard typing the letter ‘s’ (M0L0).
tap, the Twiddler is a chording keyboard. Instead of pressing
keys in sequence to produce a character, multiple keys arepressed simultaneously. Each letter of the alphabet can be
typed on the Twiddler by pressing one or two keys concurrently. The Twiddler also has the feature of multi–character
chords (MCCs). For instance, the keyboard has chords forsome frequent words and letter sets such as ‘and’, ‘the’, and‘ing’. Users can also define their own MCCs. This has positive implications for the number of keystrokes per character(KSPC) needed to type [8].
Fingers
L000
0L00
00L0
000L
M000
0M00
00M0
000M
R000
0R00
00R0
000R

Char
a
b
c
d
e
f
g
h
Space
DeleteBackspaceEnter

Fingers

Char

Fingers

Char

RL00
R0L0
R00L

i
j
k

ML00
M0L0
M00L

r
s
t

RM00
R0M0
R00M

l
m
n

MM00
M0M0
M00M

u
v
w

RR00
R0R0
R00R

o
p
q

MR00
M0R0
M00R

x
y
z

We present a longitudinal study comparing the usability ofmulti–tap and chording on the Twiddler with ten participants.
We gathered data and evaluated the two methods for learnability, crossover values of performance, and typing rates.
We discuss the design implications from the data and discuss
the viability of the Twiddler as a high–speed text input device
for mobile phones.

Figure 2: Layouts: multi–tap (left), chording (right)
RELATED WORK

Table 1: Keymap for chording on the Twiddler.

Several studies compare text entry techniques to multi–tap[9, 18, 1, 5]. Table 2 provides a summary including the results of this study. Where it could be derived, the experiencecolumn shows the approximate number of minutes the novice
user spent typing with the given method before the maximum
words per minute were calculated. Studies that were not longitudinal in nature but characterized subjects as “novice” or“expert” are marked accordingly.

Table 1 shows the default chording layout for the Twiddler.
The four character string under the Fingers column denotes
what keys to press for a chord, one character for each row
on the Twiddler. ‘L’ is for the left column of buttons, ‘M’
the middle and ‘R’ the right. A ‘0’ denotes the corresponding button is not pressed. The designation for ‘a’ is ‘L000’
which indicates the user should press the left button on the
top row. To generate ’m’ (‘R0M0’), the user would press theright key on the top row and the middle key on the third row
at the same time. Note that the designation of left to rightis from the user’s perspective of holding the keypad facing
away. This creates a left–to–right mirror between the table
and Figure 1 (right). Figure 2 (right) shows the representa-

The study presented here has a very similar method to theLetterWise [9] and Opti keyboard layout studies [11]. These
works were designed to determine the learning rates of different typing methods using longitudinal studies. The Opti
study was designed to test different soft keyboard layouts andused a within subject 2x20 factorial design of keyboard layout (2) and session (20). The LetterWise study tested two
different input techniques that both rely on the 3x4 grid ofa mobile phone keypad. This study did not use an actual
mobile phone keypad, opting for a different keypad with thesame layout. The study is also a 2x20 factorial design employing a within subjects session factor and a between subjects typing method.

Method
Chording, MCCs
Chording
Chording
LetterWise [9]T9 [5]
Multi-tap
Multi–tap [9]TiltText [18]Multi–tap [18]T9 [5]
Multi–tap [5]Multi–tap [5]Multi–tap [1]Two key [1]Keyboard
Twiddler
Twiddler
Twiddler
desktop keypad
Nokia 3210
phone
Twiddler
desktop keypadMotorolai95cl phone
Motorolai95cl phone
Nokia 3210
phone
Nokia 3210
phone
Nokia 3210
phone
desktop keypad
desktop keypadExperience
expertexpert
400 min
550 minexpert

WPM
65.3
59.7
26.2
21.0
20.36

400 min
550 min
165 min

19.8
15.5
13.57

165 min11.04

novice9.09

novice7.98

expert

7.93

n/a
n/a

7.2
5.5

Table 2: Comparison of text entry rates for mobile phone
keypads.
METHOD
Participants

Twelve participants were recruited from the Institute’s student body. All of the subjects were informed of the significant time commitment required for the study and werecompensated for their participation calculated at the rate of$1 x WPM x Accuracy over the entire session, with a minimum of $8 per session. Two participants dropped out within
8 sessions due to time constraints. Of the ten subjects thatcompleted the study, eight are male and nine right–handed.
Eight of the participants reported that they owned or used amobile phone on a regular basis, and none of the subjects
had used a Twiddler before this study. We chose only native
English speakers as our test phrases were in English. We
also recruited participants without long fingernails that might
have impeded typing speed.
Equipment and Software

The experiment was conducted in the College’s usability laboratory. This was a stationary test where participants sat at acomputer running our test software developed in Java. The
computer stations were Pentium III based PCs. The Twiddler
was attached to the computer via a serial cable and continually sent the state of all of its buttons to the computer at 2400
baud, resulting in a key sample rate of approximately 45Hz.
The software parsed the serial stream as text input.
The faceplates of the three Twiddlers used for this study weremodified to have labels for multi–tap. Labels are appropriate
since multi–tap is designed to be used while the keypad is

Figure 3: Experimental software showing the chording
layout, phrase and statistics.
facing the user; however, when chording, the Twiddler keypad faces away from the user. To prevent subjects from turning the chording keypad to look at the keys, the chording labels on the Twiddler were covered. The labels also posed another potential problem due to left and right mappings. The
test software displays key presses to the user as if the Twiddler were held as intended. If they turned the keypad aroundfor the chording condition, the participants would have tomirror the image in their heads.
DesignThe experiment is a 2 x 20 within–subjects factorial design.
We presented the participants with two conditions: multi–
tap and chording during 20 sessions over the course of three
weeks. Sessions were scheduled Monday through Friday
where each session was separated by at least two hours andno more than two days. Each session lasted approximately
45 minutes and consisted of two parts delineated by typing
condition. Participants were randomly assigned to a condition (balanced across participants) for the first session. Thiscondition was tested first followed by the second condition.
The order of presentation alternated from session to session.
Depending on the condition under test, the testing softwarepresents the participants with the key layout for either multi–
tap or chording (Figure 2) and statistics of performance. A
phrase is presented on the screen and beneath that the transcription that resulted from the subject’s key presses (Figure
3).
Each half session began with a warm–up round. The warm–
up consists of typing the two phrases, “abcd efgh ijkl” “mnopqrst uvwx yz” twice. During the warm–up phase the program also highlights the correct buttons to press to type thenext letter in the phrase. The warm–up data was not usedin measuring performance. Once the warm–up phase ended,the highlighting was turned off but the key layout remained.
The subjects were instructed to begin typing for the trials,
and data recording began.
Each half session consisted of several blocks of trials. Eachblock contained ten text phrases of approximately 28 char-acters each and were selected randomly from the set of 500
phrases developed by MacKenzie and Soukoreff [10]. Theseare phrases specifically designed as representative samplesof the English language. The phrases contain only lettersand spaces, and we altered the phrases to use only lower caseand American English spellings.
The experimental software presented blocks of phrases until twenty minutes had expired. As participants’ typing rates
increased throughout the study, the number of blocks completed also increased. In the first session, participants typed
5 to 8 blocks total and completed 12 to 21 blocks by the final
session.
During the first and last sessions, we also asked each participant to type using a standard desktop QWERTY keyboard
for two blocks for a total of 40 phrases. We collected thisdata as a baseline typing rate for each participant.
The software collects data at the level of button presses. Every key press and release is recorded to a log file. Whena button is pressed or released, the system logs the time–stamp (obtained with Java’s System.currentTimeMillis() system call), the character generated (if any), and the state of
all of the Twiddler’s buttons. The current text entry method
is logged as well as the phrases presented to the participant.
With this data we can determine when each key was pressed
and released, the duration each button was held, the time between releasing one button and pressing the next, and theresulting transcribed text.
Procedure

Each participant was given written, verbal, and visual instructions explaining the task and goal of the experiment.
The researcher explained how to type for both methods on
the Twiddler and demonstrated how to hold the device foreach condition. He also explained its key layout mimics amobile phone, mapping number keys to Twiddler keys. Finally, he showed the participants how to press each letter of
the alphabet for both methods. For multi–tap, he explainedthat the keypad is held facing the participants. The participants were informed they could wait for the timeout or utilize the kill button, and they could use one or two index fingers/thumbs to type. For chording, the researcher showed theparticipants how to strap the Twiddler onto their hand. He
also showed how to press each key with the tip of the finger
and how to press multiple keys simultaneously to generate
chords.
The software is self–administered (under researcher supervision), and participants have unique anonymous log in IDs.
The subjects are asked to copy a presented phrase by typing on the Twiddler keyboard. They are instructed to type as
quickly as possible while minimizing errors. The programprovides statistical data as feedback so the participants canmonitor their progress. In addition to the phrase to be typed
and the statistics, the program also displays the keyboard lay-out for the current method for reference.
Once started, the program initiates the warm–up phase forthe appropriate method. Once the four warm–up phrases are
typed, the program instructs the participants that the timed
trials will start next. After each block of ten phrases the
program pauses to show the participant’s statistics of rate
and accuracy for that block. After 20 minutes, the programshows the statistics for that half of the session and instructs
the participant to take a five-minute break. After the break,the program switches to the second input method. The participant changes grip on the Twiddler to be compatible withthe method and the second half of the session proceeds likethe first.
RESULTS
Data Summary

For each of our ten participants, we collected approximately
2100 transcribed phrases. In total for both conditions overall 20 sessions and 10 users we collected 600,000 transcribedcharacters.
Text Entry Speeds and Learning Curves

The mean entry rates for session one were 8.2 wpm for multi–
tap and 4.3 wpm for chording. As sessions continued, themeans improved and reached 19.8 wpm for multi–tap and26.2 wpm for chording by session 20. While both showed
improvement, the performance scores for the chording condition rapidly surpassed those of multi–tap (Figure 4).
An analysis of variance (ANOVA) of text entry speed showsa main effect for typing method (F1,9 = 45.2, p < 0.0001)
and for session (F19,171 = 36.8, p < 0.0001). There isalso a significant method–by–session interaction (F19,171 =3.62, p < 0.0001).
The main effect of session was expected as was the method–by–session interaction. The participants learned to type fasterover the course of the 20 sessions. Initially the participants
on average typed faster with multi–tap, but after a few sessions the difference eroded and by the eighth session chording was faster (T9 = 3.1, p < 0.05). The significance of thedifferences also increased as the sessions continued.
For each typing method, we derived exponential regression
curves to model the power law of practice (Figure 4) [2]. The
equations for the curves are below. The x values are the number of 20 minute sessions and the y values are the predicted
rate in words per minute for that session. The curves have R 2
values of greater than 98% indicating that the curves are wellfitted to the data, accounting for over 98% of the variance.
As can be seen, multi–tap rates begin to plateau while thechording method shows steadily increasing typing speeds.
Twiddler: y = 4.8987x0.5781, R2 = 0.9849
Multi–tap: y = 8.2235x0.2950, R2 = 0.9961

Learning rates of Chording and Multi-tap
30

25

WPM

20

15

10

5
Chording
Multi-tap

0

2

4

6

8

10
Session

12

14

16

18

20

Figure 4: Learning rates and exponential regression curves for multi–tap and chording.
The crossover point in the curves indicates where one condition’s typing rate surpasses the other. In our study, the chording method began with slower speeds but quickly overcame
multi–tap. The crossover occurred after the fifth session orafter 1 hour 40 minutes of practice.
Per Participant Text Entry Rates

Because learning rates are exponential, we graphed the text
entry rates per participant as a log-log plot. Both graphs in
Figure 5 show data for all ten subjects on a per session basis.
The left side of Figure 5 shows the chording data and theright is for multi–tap. The steep slope of chording indicates
rapid learning. The slopes of the multi–tap sessions are much
more shallow. The curves also show the large variances in themulti–tap entry rates.

phrase typing rates for the chording condition. In our 20 sessions, each participant typed approximately 1050 phrases foreach condition. We have extended the regression lines to predict what expert rates might be achieved. The chording regressions are particularly interesting because of the clusters
that appear. It suggests that the faster typists would reach
60 wpm, the rate of our expert, after 10,000 phrases (approximately 80 sessions or 27 hours) while the slower typists
could achieve 45 wpm.
Individual Regression Curves for Chording
80

70

60

WPM

50

Chording WPM by Session (log-log)

40

Multi-tap WPM by Session (log-log)

30
32

1
2
3
4
5
6
7
8
9
10

32

20

10
16

0

WPM (log)

WPM (log)

16

8

4

1

2

4
Session (log)

8

2000

3000

4000

5000

6000

7000

8000

9000

10000

Figure 6: Per participant regressions for chording
1
2
3
4
5
6
7
8
9
10

4

16

1000

Sentence

8
1
2
3
4
5
6
7
8
9
10

0

1

2

4
Session (log)8Error Rates
16

Figure 5: Log-log plots of learning rates for chording(left) and multi–tap (right) for each participant.
Figure 6 illustrates per user regression lines that model per

We used Soukoreff’s and Mackenzie’s total error rate metric[16] which combines corrected and uncorrected errors. Ourparticipants tended not to correct their mistakes, so most of
the errors in this study were left uncorrected.
Figure 7 shows the average total error rates per session forboth conditions. Our error rates are comparable to other studies [9], and all of the error rates are less than 5% after thesecond session. The chording method error rates started at
10.4% but quickly decreased. We believe the high initial rateis due to the fact that the participants had no experience withchording on the Twiddler.
Total Error Rates
11

Chording
Multi-tap

109Total Error (%)

8
7
6
5
4

participants than previous studies. The James and Reischelstudy found multi–tap typing rates of 8 wpm; our participants
started close to this rate (8.2 wpm) but quickly surpassed
it. One possible explanation for this increase is that while
James and Reischel’s subjects may have been experienced
with sending text messages, they may not have had as muchpractice as ours. Another possible explanation is the keypad
itself. They used a phone keypad while we used a Twiddler
which has larger buttons spaced farther apart. MacKenzie
et. al also did not use a mobile phone keypad. Their starting rates were comparable to ours, but our participants’ final rates were higher. Perhaps an explanation for this is that
we allowed 2 finger/thumb entry. Another factor could bethat our participants had a rapid base typing rate on standard
QWERTY keyboards (Table 3).

3
2

0

5

10
Session15

20

Figure 7: Total error rates for chording and multi–tap.
Expert Chording Rates and Errors

To compare our novice participants’ final entry rates with anexpert we tested the second author, an expert of 10 years
in chording text entry. He utilizes his non-dominant handin contrast to our study and normally uses multi-character
chording shortcuts for increased speed (i.e. 1 chord to type‘the’). We tested him without this feature forcing him to typeone character at a time. We conducted three practice sessions
to allow him to adjust to the letter–by–letter typing. By session four his average typing rate for chording stabilized andwas found to be 59.72 wpm. His total error rates were 4.44%.
We also tested the expert with MCCs enabled, resulting in a
rate of 65.25 wpm and a total error rate of 6.3%. Some errors
were intentional as it was often more efficient to type a chord
and correct the last character than to type each letter one–by–
one. For example, to type the word “their” the chord “the “
may be followed by backspace to remove the trailing spacecharacter, resulting in two chords to type three characters.
DISCUSSION
Multi–tap Typing Rates

It was also observed that all of our participants touch typed
for both methods, looking only at the screen not the keypad. Silfverberg examined the ability to type on keypad withdifferent haptics and found significant effects with varying
visual attention [13]. Perhaps the Twiddler has better tactile
feedback than the mobile phone used in the James and Reischel study.
Chording versus Multi–tap

As we have shown, novices initially have faster typing speeds
using multi–tap compared to chording. However, after practice, chording becomes the faster typing method and greatly
exceeds the multi–tap rates. Furthermore, our regression lines
suggest that the chording method has a greater potential typing rate. With only a little more practice, our participants
have the ability to achieve typing rates comparable to our expert.
Keystrokes per character (KSPC) is a metric of how many
keys need to be pressed for a particular typing method togenerate a character [8]. The KSPC for multi–tap is 2.0432[9]. For chording, only one or two simultaneous key presses
are needed to generate a character. Given Soukoreff’s digrams [15], this equates to a KSPC value of 1.4764. Fewer
key presses are required in chording to generate the same text
as compared to multi–tap, thus allowing for faster rates using
the chording typing method.

Our study data for multi–tap reveals a wide range of values
for typing rates across users (Figure 5). One explanation
for this is prior knowledge and experience with multi–tap.
All subjects reported owning mobile phones except for two.
Multi–tap is a common technology, and it is hypothesizedthat participants are familiar with how it works even if they
do not use it often. At the very least, the mapping of letters to numbers on a phone is familiar. This might also bea reason for multi–tap rates starting higher than chording.
Another factor in multi–tap’s initial advantage is the participants’ lack of experience with chording. All reported neverusing chording or the Twiddler before.

Chording on the Twiddler offers even faster potential typing
rates due to MCCs. One chord (1 or more simultaneous key
presses) can generate multiple characters. For example, theword ‘and’ can be typed letter-by letter with 4 key presses (1for ‘a’, 2 for ‘n’, 1 for ‘d’) or 1 chord of 2 simultaneous key
presses with the default multi-character chord (‘a’ and ‘h’keys). Key strokes per character changes from 4/3 to 2/3 forthis example. Extensive use of the default MCCs available
with the Twiddler could offer even faster typing rates thanthose observed in our study.

Another issue with our multi–tap study data are the values
themselves. Our study shows higher typing rates for our

As we have shown, the same 3X4 keypad can produce vastlydifferent typing rates. This might be due to a tradeoff in theuse of space versus time. In the standard QWERTY design,
all lowercase characters are devoted to a separate key (dedicated space). The opposite extreme would be to use one
key to cycle through all characters one at a time. The Twiddler chording method and multi–tap are two distinct points
in this design domain. Multi–tap spreads 3 or 4 letters acrossthe keys. The user selects a letter by pressing a particular key
several times. Chording does not utilize a temporal approach.
The user presses multiple keys at approximately the sametime to generate characters. So even if chording and multi–
tap had the same keystrokes per character values, chording
would be faster since it is not dependent on time.
QWERTY as a Baseline Predictor

We utilized the data collected from a full sized desktop QWERTY keyboard to normalize each participant’s entry rate.
Table 3 shows each participant’s QWERTY average wpm,
the ratio of his or her chording and multi–tap rates during thelast session to his or her QWERTY rate. This table shows
remarkable consistency across participants despite the large
range in QWERTY speeds. After twenty sessions, the average ratio for chording is 32.5% (s.d. 3.9), while the average
ratio for multi–tap is 24.7% (s.d. 4.5).
QWERTY wpm
113.9
111.1
94.8
86.8
83.5
82.3
74.5
61.5
58.5
54.1

Chording (%)
32.3
28.0
31.9
30.0
33.8
29.3
29.9
36.6
31.4
41.3

Multi–tap (%)
23.0
21.0
23.3
22.4
25.8
23.8
17.6
29.9
27.2
33.3

Table 3: Typing rates as a function of QWERTY speed.
The consistency between participants suggests that QWERTY
rates might predict chording and multi–tap rates. Using ourtable, if someone types 90 WPM on a standard QWERTY
keyboard, our data suggests that after 20 20-minute sessions
she would type approximately 29 wpm chording, while only
22 wpm with multi–tap. More data needs to be collected toconfirm this hypothesis.
Chording as Alternative for Text Entry on Mobile Phones

Both multi–tap and the Twiddler chording method utilize a
12 button 3X4 keypad in a size appropriate for mobile phones.
As we have demonstrated through the data collected in thisstudy, even novice chording users quickly outperform multi–
tap typing speeds. Furthermore, data suggests that the Twiddler has greater potential expert typing rates. Anecdotally,
these typing rates are sufficient for composing email.
One can imagine a mobile phone design based on the current
Twiddler keyboard. A speaker can be placed in the position of the “Twiddler” logo in Figure 1, and a microphone

at the base of the keyboard under the “h” key. Furthermore,a high resolution touch screen can be placed on the reverse
side of the Twiddler where the thumb buttons currently reside. The thumb buttons (Control, Shift, NUM, ALT, etc.)
can be emulated with the touch screen and could be reprogrammed as needed. For messaging or learning to type, thehigh resolution screen could be used to display a graphicalinterface similar to that in Figure 3, which would encourage good touch typing and good posture. This screen could
also serve for more advanced features. For example, a camera could be mounted in the flat base of the Twiddler (wherethe velcro strap attaches), and the screen could act as a camcorder viewfinder.
Besides increased text entry speed, this design may have otherbenefits. For example, the user could type notes without
needing to look at his phone. In our experience, this ability is key while engaged in conversation [7]. In a presentation at Mobile HCI 2003, Silfverberg [13] observed thatsuch “blind” typing might be a market differentiater for the
teenage population for exchanging notes in class. Finally,
the ability for the user to type with his hand at the side withthe wrist straight and relaxed may help alleviate the stress ofsome repetitive strain injuries.
FUTURE WORKOne potential area of future work is to continue the study
to find the session number in which participants’ chording
typing rates begin to level off. Given our regression curves,
we expect to reach the rate of our expert after approximately
10,000 phrases. More data would be needed to confirm this.
Another possible point to explore is to include more participants. This study, with only ten participants, showed large
variances between participants in the multi–tap typing rates.
Perhaps a larger subject pool might reduce the variance observed. It would also be interesting to look at left versus
right-handed issues with chording as the layout is not symmetrical. Furthermore, we could explore the effects of gender and different hand sizes. More participants would also
allow us to explore if the typing rates normalized by QWERTY speeds are a valid predictor of performance.
We would also like to explore more realistic usage settingsof mobile phones. These devices are utilized while people
are moving around in their environment; however, participants remained stationary during the trials. By the end of thisstudy, almost all of our participants were touch typing withboth methods and only monitored their progress by looking
at the screen. A study exploring blind typing, where subjects
have limited or no visual feedback, might more realisticallysimulate mobile use due to limited visual attention [13]. Another study might be to evaluate participants’ performance
while in motion. Examining performance of the Twiddler
chording condition while subjects are moving through theirenvironment would provide more practical typing rates.

The simple highlighting used during our warm–up phase could
be extended to create a tutorial for typing. For this study,
we allowed only letter–by–letter chords. The Twiddler also
provides several default multi–character chords. Examining
how to teach novices to use these MCCs and studying theireffect on typing performance would be interesting. Likewise,
creating a tutorial designed to improve an expert’s rates isanother interesting project. This would require examining
potential inefficiencies in the expert’s current typing and creating software to optimize the user’s performance.
Finally, we are interested in creating a predictive model oftyping rates for the Twiddler chording method and comparing the prediction to actual data. This could be useful for key
layout optimization and chord creation.
CONCLUSION

In this paper, we presented a longitudinal study comparing
multi–tap and chording methods on a HandyKey Twiddler,a mobile one–handed keyboard with a keypad layout similar
to a mobile phone. Chording out–performs multi–tap typing speeds, is learned quickly, and appears to have a higher
attainable maximum rate. In addition, the chording rates reported here are faster than those reported in studies on T9 andLetterWise for similar levels of expertise. With the numerous
wireless messages sent currently and the predicted increasein wireless email usage, the Twiddler’s one–handed chording
text entry method should be seriously considered for future
mobile phone designs.
ACKNOWLEDGEMENTS

Thanks to DARPA for partial support under the ”Augmenting
a Program Manager” seedling. Thanks also to Scott MacKenzie for his phrase set and Scott MacKenzie, William Soukoreff, Miika Silfverberg, and Shumin Zhai for their suggestions.
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