Appendix I

Case 6:20-cv-00507-ADA Document 71-11 Filed 04/14/23 Page 1 of 7
Boston, Massachusetts USA • April 24-28, 1994 Human Factors in Computing Systems 

T-Cube: A Fast, Self-Disclosing Pen-Based Alphabet 

Dan Venolia 

Apple Computer, Inc. 

1 Infinite Loop 

Cupertino CA 95014 USA 

(408) 974-4121 

E-mail: danv@apple. corn 

ABSTRACT 

An interface for entering text to a pen-based computer is 

described. The technique proposes a new alphabet, where 

each letter is a flick gesture. These flick gestures are selfdisclosing using pie menus. An experiment determined the 

speeds of executing the flick gestures and the transition 

speeds between gestures. An assignment of characters to 

gestures is developed and evaluated. Audio feedback is used 

to convey whether a gesture was well- or badly-formed. A 

longitudinal study showed clear progress on a learning curve. 

The method is compared to soft keyboards, handwriting 

recognition systems, and unistrokes. 

KEYWORDS: Stylus, text entry, pen-based computing, audio 

feedback. 

INTRODUCTION 

Computers are ever getting smaller, and the traditional keyboard is giving way to pen-based entry of text for portable 

applications. Existing techniques, like handwriting recognition and soft keyboards, have certain speed limitations. This 

paper presents T-Cube, a novel, faster method of entering text 

with a pen on small computers. 

Many substitutions for the full-sized keyboard have been 

tried. Some manufacturers have included miniaturized keyboards on their computers. These are often adequate for the 

entry of phrases of text, but are inappropriate for the entry of 

large amounts of data. Even at their smaller sizes, they often 

dominate the shape and size of the small computer. 

Others have attempted to use "chord" keyboards, where a 

small number of buttons (typically five) are pressed in combination to produce a single character. Despite the variety of 

chord keyboard designs, they have not succeeded in the 

marketplace, probably because they are difficult to learn. 

Instead of a keyboard, many manufacturers have turned to a 

stylus as the primary mode of input. Typically, a stylus is 

used in two ways to enter text: handwriting recognition or soft 

keyboards. With handwriting recognition, the user writes on 

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CHI94-4/94 Boston, Massachusetts USA 

1994 ACM 0-89791-650-6/94/0265...$3.50 

Forrest Neiberg 

2843 East Grand River #157 

East Lansing MI 48823 USA 

E-mail: fiteiberg@mcimail.com 

the screen using the stylus. Assuming fast and accurate 

recognition—not yet a reality—this technique is limited by 

the slow speed of printing or writing. 

A soft keyboard is a graphical representation of a keyboard on 

the screen, activated by tapping keys with a stylus [8J. They 

are often used as an alternative or fallback for handwriting 

recognition systems. They are easy to understand, but consume much screen space and are slow to use. 

A third technique for entering text with a pen, called unistrokes, 

was proposed by Goldberg and Richardson [5]. They tailored 

a new alphabet to the task of entering characters with a stylus. 

Unistrokes have several good properties: they are faster to 

write than Roman characters, they are easier to recognize 

algorithmically, and they take a small screen area to enter. 

T-CUBE 

This paper proposes a new alphabet and interaction style that 

has many of the advantages of unistrokes, and includes a 

faster, self-disclosing alphabet. Since a "flick" gesture is 

particularly fast with a pen, the alphabet constructed for TCube consists of flicks. A flick gesture has two easily 

controlled aspects: its starting point and its direction. Each 

flick starts in one of the nine cells arranged into a "target" 

shown in Figure I a. The target is typically 0.3 to 0.7 inches 

in diameter. The direction of the flick can be vertical, 

horizontal or diagonal, specifying one of eight directions. 

The combination of nine starting cells with eight directions 

yields 72 different gestures. Each gesture represents a character, e.g. "w" or "7", or an operation, e.g. Backspace, Return 

or Shift. d - 

k 

J 

I 

it 

— -c 

n 

❑ET- beE 

Figure 1: The T-Cube target (a) lies within a window. 

When the user presses the pen in one of the nine target 

cells, a pie menu (b) appears offset from the pen. 

Dragging the pen highlights one of the characters (c), 

and shows the result of the drag (d). When the pen is 

lifted, the character is "typed" to the system. 

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Human Factors in Computing Systems

The use of starting cell and direction corresponds with the 

way pie menus work [2] [6] [7]. Pressing the stylus in a cell 

for a brief interval (one third of a second) causes a pie menu 

to appear (Figure lb). The eight symbols lie in eight directions from the center of the pie. When the stylus moves a few 

pixels away from its starting position, the character that 

corresponds to that direction is highlighted (Figure lc). The 

highlighted character is "typed" when the pen is released. 

The motion of selecting an item from a pie menu is the same 

as the flick gesture. 

If the user remembers exactly the starting cell and direction, 

she may make that gesture directly. If she knows the starting 

cell of the desired character, she may "pop up" the pie menu 

to see exactly which direction the letter is in. If she doesn't 

remember the starting cell, she may pop up a series of pie 

menus until the desired symbol is found. 

Until the user has learned the common characters, she needs 

to refer to the pop-up menus very frequently. To alleviate the 

tedium of popping up menus, the user may switch T-Cube 

into its "training mode." In this mode, the pie menu is visible 

whenever the pen is near the T-Cube target. When the pen is 

held above a cell in the target, the corresponding pie menu 

items are visible. She then selects a menu item by pressing the 

pen down, dragging in one of the eight directions, and 

releasing. 

A typical pie menu is displayed with its center exactly under 

the stylus tip. With a pen-based computer, the user's hand 

obscures nearly half of a typical pie menu. The T-Cube pie 

menu is offset from the center of the target, but it is still 

activated by a short radial movement of the pen. The motion 

of the pen from its location when the pie menu popped up to 

its present location is represented by a thick line radiating 

from the center of the pie menu, as shown in Figure ld. The 

pie menu is offset to the left for a right-handed user, and to the 

right for a left-hander. 

CHARACTER LAYOUTS 

An assignment of characters to gestures is called a layout. A 

layout is desirable if it is both predictable and fast. With a 

predictable layout, a moderately experienced user can guess 

at the gesture to make a desired character, and be right some 

(hopefully most) of the time. In a fast layout, frequent letters 

correspond to fast gestures. A predictable layout helps the 

novice user; a fast layout helps the expert user. To assess a 

layout's speed, an experiment was conducted to determine 

the speeds of individual gestures and transitions between 

gestures. 

Gesture Speeds Experiment 

Twenty-two subjects participated in the experiment—Apple 

Computer employees who were seletted for their exposure to 

graphic tablets from a volunteer subject pool. The experiment was run on a custom pen-based computer with an 

untethered pen and an 8.5" (diag.) backlit LCD screen. A TCube target was visible on the screen. For each trial, a 

stimulus target appeared 0.9" above it, marked with a gesture. 

The subject attempted to reproduce the indicated gesture. 

Another trial followed after 100ms. The time from the 

presentation of the stimulus to the pen-down and pen-up were 

CIT94 • "Celebrating Interdependence" 

te. A 

'4 

1.00 

1.10 

1.20 seconds 

Overall 

Figure 2: Mean speeds are shown for each direction 

and starting cell in this group of radial bar charts. The 

gray circle is the mean for the cell, independent of 

direction. 

recorded, along with several other parameters. Each subject 

performed 72 training trails, then three blocks of about 350 

trials each. In all, over 20,000 non-training trials were 

recorded. 

This experiment resulted in two kinds of information. First, 

the speed for each gesture was determined. This guided the 

placement of frequent characters to fast gestures in the layout. 

Second, a matrix of gesture-to-gesture transition times was 

found. These times were used to evaluate the speed of layout 

candidates. 

The results of the experiment are summarized in Figure 2. 

The speed value shown for each gesture is the mean of all 

times from stimulus to pen-up. The speeds indicated are 

slower than they would be in real use, in part since the subject 

had to look from the upper target to the lower. The fastest 

starting cells, in order, are Center, North, Northwest, South 

and East. The radial gestures (e. g. starting in the North cell 

and drawing to the North) are the fastest overall. Westerly 

gestures from any cell tend to be the slowest. There appears 

to be no categorical speed difference for orthogonal vs. 

diagonal gestures. There appears to be asymmetry in the 

response times, perhaps due to the handedness of the subjects. 

A Predictable Layout 

The construction of a predictable layout is considered next. 

Since the pie menu can be examined to find the direction for 

a character when given the correct starting cell, the assignment of characters to starting cells is more important than the 

arrangement within the cell's pie menu. Characters must be 

clustered into starting cells in a way that allows the user to 

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DET - CUbeEr: 

' Q .

1 = , 

• • 

• 

• • 

Figure 3: Symbo s are displayed next to the target when 

modes-Shift, Option and Command—are active. 

predict which cell contains the desired character. Where 

possible, frequently used characters were associated with fast 

gestures. 

The most frequently used characters are Space, Backspace 

and Shift. They are clustered with the other "non-printing" 

characters—Tab, Return and the so-called "meta-keys"—

and placed into the fastest starting cell. For the Macintosh, 

meta-keys are and Option; other systems have different 

ones, e. g. Alt, Ctl or 0. Meta-keys act as toggles—the same 

gesture turns them on and off—and are shown next to the TCube target when they are active (Figure 3). Shift and CapsLock are meta-keys that also have an effect on the layout. As 

on a normal computer keyboard, when either is active, letter 

gestures make capital rather than lower case characters. 

When Shift is active, a gesture may result in a different 

character altogether, just as "shift-3" on a keyboard produces 

a "#" symbol. All the meta-keys except Caps-Lock deactivate after a character is produced. This cluster of characters 

and meta-keys is placed in the center starting cell (Figure 4). 

Since the main goal is for the entry of text, the clustering of 

the letters is crucial for a predictable layout. One predictable 

clustering of the letters was designed by separating the 

vowels from the consonants: 

ABCDEFGHIJKLMNOPQRSTUVWXYZ 

Moving the vowels into one cluster reveals a natural clustering of the consonants: 

AEIOU BCD FGH JKLMN PQRST VWXYZ 

The two small clusters can be combined, leaving five clusters. 

The clusters are placed clockwise from the North cell, as 

shown in Figure 4. 

The ten digits must be placed in two or more cells. Choosing 

to mimic a numeric keypad in organization, the numbers are 

placed in cells along the West side of the target. 

Symbols are grouped with either the numbers or the letters, 

depending on which they are more commonly used with. The 

symbol shown on the left is produced when Shift is inactive, 

and the right when it active. 

Finally, the remaining five gestures are assigned to the 

Accent meta-keys (Northwest starting cell, shown in Figure 

4). Accent meta-keys act as toggles, and only one can be 

active at a time. The active accent is shown next to the T-Cube 

e 

a 0 

Accents 

7 9 8 

a 

! i ? 

. : 

b 

% 

g 

d 

s 

h 

Shift 

/\ 

_ 

Option Tab 

k a m 

- # + Backspace Space J 

4 6 5 Return 

41. • 

• • 

mmand 

I • 

Caps-Lock r 

<≤ >≥ q S 

• H 

w 9 

p t 

1 2 3 ) 

V z 11 

{} 

8 

Figure 4: The character that results from each gesture 

is shown here. For example, the gesture that starts in 

the East cell and goes Northeast results in an "m". The 

character produced depends on the state of the Shift 

modifier. 

target as below the other meta-key states. When an accent ( ) 

is active and the user makes a letter that can use that accent 

("a"), the accented character is produced ("a"), and the accent 

mode deactivates. 

There are a myriad of possible layouts. Dozens of possible 

layouts were considered for this design. Future work may 

discover a better layout. 

FEEDBACK 

Any interactive system needs to give feedback to help the user 

understand, learn and use it. T-Cube enlists both graphic and 

audio feedback to help convey information about the interface. When the user makes a gesture, a small tic appears for 

a brief time showing an idealized version of the gesture. 

Many users suggested that the character itself should also 

appear briefly. Both are shown in Figure 5. This feedback 

helps strengthen the association between the gesture and the 

character, assisting the novice user to become an expert. It 

also reinforces the ideal form of the gesture—starting at the 

center of the cell, and extending orthogonally or diagonally. 

Another way that T-Cube helps users draw well-formed 

gestures is with sound. A brief sound clip is heard when the 

user begins a flick, and another when it ends. The first sound 

is a subtle but crisp "tick" when the start of the flick is near the 

center of the cell. When it is near to the edge, a "clonk" sound 

is mixed in with the "click." The sound at the end of the flick 

is a crisp "tock" when the direction is orthogonal or diagonal. 

A more ambiguous angle produces the "tock" blended with a 

kind of "buzz" sound. The use of sound may alert users to 

sloppy gestures, and the potential errors that may result. 

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DEET-CubeE 

m 

al 

Figure 5: After a gesture is completed, the character is 

"typed" to the system, and graphics briefly show the 

character and an idealized version of the gesture. 

Other sounds help convey modes. When a meta-key is 

invoked, a two-tone rising motif [1] is heard if it toggles on, 

and a two-tone descending motif plays if it toggles off. The 

Caps-Lock meta-key has more dramatic versions of the rising 

and falling motifs. The non-printing characters produce a 

sound since often the visual change associated with them is 

subtle. 

The user has the option of hearing a sound for each letter 

written. The sound consists of the spoken letter (e. g. "w" 

plays a recording of the words "double you") mixed with a 

chime sound whose pitch varies depending on the starting 

cell. The upper cells produce a high pitches, the low cells 

produce low pitches. This is intended to reinforce the association between the cell and the letter. 

Sounds in T-Cube encode much information. It is not 

necessary that the user perceive and use all the information all 

the time. Sounds may gain or lose value as the user progresses 

from novice to expert. What is more important is that the 

sounds provide a sonic texture to the user, so that changes in 

that texture will alert the user to changes in the interface and 

its use [4]. 

PILOT LONGITUDINAL STUDY 

The design proposed above is tantalizing, but it is not clear 

that the resulting interface can be learned and used by real 

people. To determine this, a pilot longitudinal study was 

performed. Eleven subjects, some of whom had participated 

in the earlier experiment, were exposed to T-Cube several 

times over the course of a month. Eight subjects performed 

eight or nine sessions; three subjects completed only four, 

five or six sessions. In each session, they were presented with 

a series of sentences to enter using T-Cube, as shown in 

Figure 6. One hundred sentences were selected from the text 

of "Alice in Wonderland," and were presented in random 

order. At the end of a sentence, the subject tapped the "Done" 

button, and could rest for an arbitrary time before starting the 

next sentence. The total time spent entering characters during 

the session was twenty to thirty minutes. 

Subjects were allowed to change at any time the target size, 

the kind of sounds presented, and whether they were in 

training mode or expert mode. The target was either 0.4, 0.55 

or 0.7 inches in diameter. The interface was silent, used only 

the basic sounds, or used both the basic and the alphabetic 

sounds. At the start of each session, the medium target was 

presented, with basic sounds, in expert mode. 

e file fail foam-meet Trials Medium] Wien* 

'forget Size: 

o Smell 

Medium 

0 Large 

Sounds: 

o None 

Basle 

o niphaliet 

Hover Tracking: 

Off 

000 

Ono of the Jurors had a pencil the) squeaked. 

One of the Juror 

Oone 

Figure 6: Subjects were studied over repeated exposure 

to T-Cube. In each session, they copied sentences. 

They had control of the target size, the sounds, and the 

training mode. (Screen shot shown at half actual size.) 

Each subject was assigned to one of two layouts. Eight of the 

subjects used the layout that was rated the fastest, the other 

three used a layout similar to the one described above. 

The basic sounds were preferred by most subjects. Seven 

users chose basic sounds more than the other settings. Two 

subjects only used the sounds for a few strokes, then turned 

them off. Another two tried sounds both basic and off, and 

tended toward turning them off. While this indicates good 

acceptance (64%) when users have a choice of sounds in the 

interface, it is hard to say whether sounds made T-Cube easier 

to use. The alphabetic sounds were universally disliked. 

The medium-sized target was preferred by most subjects. 

Seven subjects chose the medium target more often than the 

small or large targets. Two subjects preferred the large one, 

and two preferred the small one. Providing a variety of target 

sizes appears to be desirable. 

Two learning curves were examined: change in speed over 

time, and the use of the pie menu over time. Figure 7 shows 

the increase in median speed for letters, space and backspace 

that were entered without using training mode or the pop-up 

pie menu, for each subject by session. For the duration of the 

study, the entry speed increases linearly; there is no sign of 

leveling off. While this indicates that the study did not run for 

enough sessions, it also suggests that the maximum speed 

observed (60 to 106 characters per minute) is significantly 

less than the true maximum speed for T-Cube. There is no 

clear speed difference between the two layouts. 

Subjects' reliance on the pie menu is shown in Figure 8. In 

the first session, most used the training mode, while a few 

chose instead to use the pop-up menu. By the second session, 

8% of the gestures were drawn without the aid of the menu. 

By the final session, subjects referred to the menu only a few 

times. 

From observing the subjects, it was apparent that about half 

of the subjects were familiar with the layout after the first 

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100% 

Characters per Minute 

120 

100 • 

80 

60 

40 

20 

1 2 3 4 5 6 7 8 9 

Session 

Figure 7: The entry speed increased linearly with 

exposure. A line, representing a subject, starts at the 

first session where they entered more than a few 

strokes by gesture only, and ends at the last session. 

The "x" and "o" marks indicate different layouts. 

session, and that all subjects felt comfortable with it after the 

second session. 

These ways of looking at the learning curve indicate that users 

can get to know T-Cube in a few hours of exposure. Even in 

that short time, good speeds can be achieved. Given longer 

to learn, greater speeds could be achieved. 

Subjects consistently reported a few observations. Parallax 

caused by the distance between the front glass and the LCD 

image made users uncomfortable. Some mentioned that they 

write at an angle, so North should be customizable, rather 

than fixed to be "up" on the screen. Many suggested that 

separate buttons be added for the most common functions, 

like backspace, shift and repeat. 

COMPARISON 

How does T-Cube compare to the other ways of entering text 

with a stylus? Some of the many factors are considered here: 

Screen Size: T-Cube uses less than a square inch of screen 

space. Unistrokes take somewhat more. Soft keyboards take 

vastly more space. Handwriting can be done either in-place 

or in a separate entry window. When it is done in-place, it 

takes up virtually no space. When entry is done into a special 

area, that area can be very large. 

Speed: The speeds of T-Cube, unistrokes [5], finger-activated soft keyboards [8], writing with pen and paper, and 

typing [3] are compared in Figure 9. T-Cube rates competitively against the others. Note that the speed range for 

unistrokes is based on the "peak error-free writing speeds" for 

two users, so may not represent the population mean. 

Character Set: Handwriting systems and unistrokes have 

severely limited character sets. T-Cube produces all of the 

ASCII characters, along with many of the extensions that are 

common and useful in today's international systems. Soft 

keyboards can produce any character that a real keyboard can. 

80% co 

z 

Co

CD 

"5 40% 

E 

z 

60% - 

20% — 

0% 

Po -U 

Training Mode 

No 

nu 

ie Menu 

2 3 4 5 6 7 8 9 

Session 

Figure 8: Almost all subjects used the training mode for 

the early sessions. By the end, all of them had 

progressed to expert mode, and were using the popup pie menu very little. 

Visual Attention: Whether an input modality requires visual 

attention impacts how and when it can be used. One that 

doesn't require the eyes can be used for transcription, while 

driving a car, or while talking to a client. One of unistrokes' 

greatest strength is its ability to be used without visual 

attention. Handwriting and soft keyboards both require a 

great deal of visual attention. 

Using T-Cube, the entire target is accessible without moving 

the hand. It is conceivable that T-Cube could be used without 

looking at it, relying on the user's proprioception to guide the 

pen back to the center of the target. The difficult part for a user 

would be accurately getting to the desired starting cell. Audio 

feedback that acted as a homing device to find the cell centers 

might help to locate them. 

Further experiments are needed to determine whether TCube can be used with little or no visual attention. A redesign 

of T-Cube employing hierarchical marking menus [6] could 

much better serve the "eyes-free" need. 

Novice and Expert Use: While handwriting recognition systems appear to be novice-oriented, they are often difficult for 

the novice until he develops a sense of what the recognizer 

thinks is a well-formed character; once he learns this, the 

accuracy rate will climb. As he gains experience though, 

there is no way that he can enter text faster than his handwriting speed will allow. Handwriting systems have poor novice 

performance and no path for expert growth. 

Soft keyboards are very accessible to the novice. They use a 

layout that is likely to be known to the user. The expert is 

limited, though, by the speed of tapping buttons on the screen. 

The novice user of unistrokes must use a reference card 

initially, though it is unclear for how long. Once the user does 

successfully become an expert, great speed gains can be 

made. Writing speed after one week's experience compares 

favorably with soft keyboards. The reference card makes 

unistrokes cumbersome for novices, but the potential speed 

gains makes it good for experts. 

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Human Factors in Computing Systems CHI '94 • "Celebrating Interdependence" 

Characters per Minute 

1000 - 

= • 

100 

10 

an 

c 

ea 

c a) •.= I— c 

ch •c 

.c 0_ -0 

>. as asas x 

Soft Keyboard 

2 

*E 

a) 

Input Method 

Figure 9: Entry speeds for various methods are 

compared on a logarithmic scale. After eight or nine 

sessions, T-Cube subjects attained speeds in the 

indicated range. Since all of the subjects were 

continuing to get faster at the end of the observation, 

it is expected that in actual use, speeds would be 

higher than indicated. 

T-Cube supports both the novice and the expert user. The 

novice can use the predictable layout of letters and the pie 

menu to find characters. The act of using the interface in this 

way helps the user to gain expertise. For the expert user, entry 

of text becomes a fairly simple motor task, with potential for 

high speed. 

Best Use 

By examining the strengths of T-Cube relative to the other 

techniques, a picture of its use can be painted. It requires a 

small screen area, and is fast for experts. It helps the novice 

to become an expert—the training process is built into the 

interface. These characteristics paint a picture of a user of a 

portable, hand-held device who, motivated by the payoff of 

fast entry of text, is willing and able to invest the time to 

become an expert. This device might be a note-taking 

computer or a interactive TV remote control. On the other 

hand, T-Cube is not appropriate for many situations, as when 

use is infrequent (e. g. an information kiosk) or when a 

keyboard is available (e. g. a laptop or desktop computer). It 

is unclear whether any of the pen-based techniques are 

appropriate for entering large amounts of data. 

CONCLUSION 

T-Cube proposes a new alphabet for pen-based computing 

that is more appropriate for this medium than the traditional 

"paper" alphabet. In addition, it shows how a certain class of 

gestures can be self-disclosing, using pie menus. 

T-Cube supports the novice user in a variety of ways. Pie 

menus reveal how a gesture is formed, as well as the association between characters and gestures. A predictable layout of 

letters, numbers and punctuation helps the novice guess 

which starting cell to choose. The training mode, in which the 

pie menu is always visible, showing the contents of the 

starting cell that is under the pen tip, further helps the novice 

search for characters in the layout. When the user gains 

experience, she can leave the training mode, but still refer to 

the pie menu when the need arises, by pressing in the starting 

cell. The pie menu reveals the direction to draw the gesture 

to make the desired character. 

As the novice uses T-Cube, she is tacitly training herself to 

become an expert. The motion that she uses to invoke a pie 

menu is exactly the flick gesture that an expert uses to create 

a character. Frequent entry of a common character leads to a 

strong association with the specific gesture that stands for 

character. As she gains this knowledge, entry speed increases 

dramatically. When she becomes an expert, she is rewarded 

with a fast, predictable, reliable way to enter text. 

270 

Future research may examine the issues of using T-Cube for 

the young, the elderly, or the disabled. Also of great interest 

is the application of these techniques to other languages, 

particularly to Asian character sets with the use of a deeper 

hierarchy of pie menus. 

REFERENCES 

1. Blattner, M., Sumikawa, D., and Greenberg, R. Earcons 

and icons: Their structure and common design principles, 

in Human-Computer Interaction 4, 1 (1989), pp. 11-44. 

2. Callahan, J., Hopkins, D., Weiser, M., and Shneiderman, 

B. An empirical comparison of pie vs. linear menus, in 

Proc. CHI '88 (Washington, D. C., May 15-19, 1988), 

ACM Press, pp. 95-100. 

3. Card, S., Moran, T., and Newell, A. The psychology of 

human-computer interaction. Erlbaum, Hillsdale, New 

Jersey, 1983, p. 61. 

4. Gayer, W., Smith, R., and O' Shea, T. Effective Sounds in 

complex systems: The ARKola simulation, in Proc. CHI 

'91 (New Orleans, April 28—May 2, 1991), ACM Press, 

pp. 85-90. 

5. Goldberg, D., and Richardson, C. Touch-typing with a 

stylus, in Proc. INTERCHI '93 (Amsterdam, April 24-29, 

1993), ACM Press, pp. 80-87. 

6. Kurtenbach, G., and Buxton, W. The limits of expert 

performance using hierarchic marking menus, in Proc. 

INTERCHI '93 (Amsterdam, April 24-29, 1993), ACM 

Press, pp. 482-487. 

7. Ludolph, F., Chow, Y., Ingalls, D., Wallace, S., and 

Doyle, K. The Fabrik programming environment, in 1988 

IEEE Workshop on Visual Languages, pp. 222-230. 

8. Sears, A., Revis, D., Swatski, J., Crittenden, R., and 

Shneiderman, B. Investigating touchscreen typing: The 

effect of keyboard size on typing speed. Behaviour & 

Information Technology 12, 1 (1993), pp. 17-22. 

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