P
PEN-BASED COMPUTING The other way to combine the two is to mount the display
on top of the digitizer; although it does not have to be
INTRODUCTION transparent, the accuracy of the digitizer is reduced
because of the greater distance between its surface and
An Overview of Pen-Computing the tip of the pen when it is in contact with the writing
surface.
Pen-based computing first came under the mainstream
The two types of digitizers are active and passive. Active
spotlight in the late 1980s when GO Computers developed
digitizers are the most common type used in pen-based
the first computer operating system (OS) customized for
computers. These digitizers measure the position of the pen
pen/stylus input called PenPoint, which was used in the
using an electromagnetic/RF signal. This signal is either
early tablet PCs by companies such as Apple Computer
transmitted by a two-dimensional grid of conducting wires
(cuperline CA) and IBM (Among NY). A pen-based com-
or coils within the digitizer or transmitted by the pen.
puter replaces the keyboard and the mouse with a pen,
The digitizer transmits the signal in two ways: it is
with which the user writes, draws, and gestures on the
either induced through a coil in the pen and conducted
screen that effectively becomes digital paper. The value
through a tether to the computer, or as is more commonly
proposition of pen-based computing is that it allows a user
seen the pen, it reflects the signal back to the digitizer or
to leverage familiarity and skills already developed for
disturbs the magnetic-field generated by the set of coils in
using the pen and paper metaphor. Thus, pen-based
the exact location of the pen tip. This reflection or distur-
computing is open to a wider range of people (essentially
bance is detected subsequently by the digitizer. Figure 2
everybody that can read and write) than conventional
depicts the latter configuration where a magnetic-field is
keyboard and mouse-based systems, and is inline with the
transmitted and received by a set of coils, and this is
theme of Ubiquitous Computing, as such a computer is
disturbed by the inductance in the tip of a pen/stylus.
perceived as an electronic workbook, and thus provides a
In this type of configuration, the horizontal and vertical
work environment resembling that which exists without
position is represented in the original signal/magnetic-field
computers. pen-based computers exist primarily in two
transmitted by either signal strength, frequency, or timing,
forms, as mentioned above; tablet PCs, which often have a
where each wire or coil in the grid carries a higher value
clip board-like profile and personal digital assistants
than its neighboring counterpart. The position of the pen is
(PDAs) that have a portable/handheld profile. Both forms
evaluated using the values reflected back or disturbed.
(particularly the PDA) lend themselves very well to appli-
The configuration where the pen reflects or disturbs the
cations such as on site data entry/manipulation where the
signal is found more commonly in modern day pen-based
conventional approach is pen and paper-form based (1).
computers, as it allows for a lighter pen that is not attached
to the computer, which provides the user with an experi-
The Digitizing Tablet
ence closer to that of using conventional pen and paper.
The function of the digitizing tablet within a pen-based This method also allows more advanced information about
computer is to detect and to measure the position of the the user’s pen strokes to be measured, which can be used to
pen on the writing surface at its nominal sampling rate. provide more sophisticated and accurate handwriting
Typically, this sampling rate varies between 50–200 Hz recognition. The pressure being exerted on the screen/
depending on the application, in which a higher sampling tablet can be measured using a capacitative probe within
rate causes a finer resolution of cursor movement, and the the tip of the pen, where its capacitance changes as it closes
computer can measure fast strokes accurately. The digitiz- (as a result of being pressed against the screen/tablet),
ing tablet is combined with the display to give the user the which changes the strength of the signal being reflected
same high level of interactivity and short cognitive feedback back. The angle of the pen can be measured using electronic
time between their pen stroke/gesture and the correspond- switches that change the frequency of the signal reflected
ing digital ink mark. The user perceives the digitizing tablet back, and these switches operate in a similar manner to tilt-
and screen as one, which makes it a direct-manipulation switches. However, these advanced features require the
input device and gives the user a similar experience to that pen to be powered by a battery or by the computer via a cord.
of writing/drawing using the conventional pen and paper Typically, passive digitizers consist of two resistive
method. To enable this high level of interactivity, the digi- sheets separated by a grid of dielectric spacers, with a
tizer must also operate with speed and precision. The dis- voltage applied across one of the sheets in both the hor-
play must be a flat panel display for the integrated unit to izontal and vertical directions. When the pen makes contact
provide the user with the optimum writing surface. The with the screen/tablet, it connects the two sheets together
display and digitizer can be combined in two ways. If the at the point of impact, which acts to change the resistance
digitizer is mounted on top of the display (as illustrated (which is proportional to length of the resistive material)
below in Fig.1), the digitizing tablet must be transparent, across the sheet in the two directions. In turn, it changes
although it can never be so infinitely, and thus the display’s the two voltages across the sheet. essentially, these vol-
contrast is reduced and the user sees a blurred image. tages represent a coordinate-pair of the pen’s position.
1

2 PEN-BASED COMPUTING
activity of handwriting, where the user writes on a digitiz-
ing tablet and the computer then converts this to text. Most
users, especially those without prior knowledge of comput-
ing and the mainstream/conventional interface that is the
keyboard and mouse, initially see this as a very intuitive
and attractive human-computer interface as it allows them
to leverage a skill that has already been acquired and
developed. Although a major disadvantage of pen-based
computers is that current HWX methods are not completely
accurate. Characters can be recognized incorrectly and
these recognition errors must be corrected subsequently
by the user. Another aspect of current HWX technology that
impacts the user’s productivity and experience in a nega-
tive way is the fact that characters have to be entered one at
a time, as the technology required to support the recogni-
tion of cursive handwriting is still a long way off and
possibly requires a new programming paradigm (4). Hand-
writing of individuals varies immensely, and an indivi-
dual’s handwriting tends to change over time in both the
short-term and the long-term. This change is apparent in
how people tend to shape and draw the same letter differ-
Figure 1. A digitizing tablet shown in the configuration where ently depending on where it is written within a word what
the digitizer is mounted on top of the screen (2) . the preceding and subsequent letters are, all of which
complicates the HWX process.
The two types of handwriting recognition are on line
Being sensitive to pressure, passive digitizers also can
(real-time) and Off line (performed on stored handwritten
receive input from the users fingers, and thus the computer
can provide the user with a more natural/familiar mechan- data). When using conventional pen and paper, the user
ism for pressing on-screen (virtual) buttons. A disadvan- sees the ink appear on the paper instantaneously; thus, on
tage of this pressure-based operation is an increase in line recognition is employed in pen-based computers for the
errors when using the pen, which are caused by the user user to be presented with the text form of their handwriting
resting against or holding the screen/tablet. However, pas- immediately. The most common method for implementing a
sive digitizers can also be configured to be sensitive only to HWX engine (and recognition engines in general) is a
pen input by placing the dielectric spacers between the two neural network, which excel in classifying input data
resistive sheets closer together, where the higher amount of into one of saveral categories. Neural networks are also
pressure needed to force the two sheets together can only be ideal for HWX as they cope very well with noisy input data.
exerted through the small area of the pen tip. This quality is required as each user writes each letter
slightly different each time, and of course altogether dif-
Handwriting Recognition ferently from other users as explained previously. Another
asset of neural networks useful in the HWX setting is their
Handwriting recognition (HWX) gives the user the ability
ability to learn over time through back-propagation, where
to interface to a computer through the already familiar
each time the user rejects a result (letter) by correcting it,
Figure 2. A digitizing tablet shown in the configuration
where a set of colls generated a magenetic-field which is
disturbed by the presence of the pen tip in that exact
location (3).

PEN-BASED COMPUTING 3
Figure 3. The Graffiti character set developed by
palm computing. The dot on each character shows
its starting point.
the neural network adjusts its weights such that the prob- based computer’s user interface must support something
called gesture recognition, where the functions and the
ability of the HWX engine making the same error again is
reduced. Although this methodology can be used to reduce operations associated with these keyboard keys are acti-
the probability of recognition errors for a particular use. vated by the user drawing a gesture corresponding to that
When met with another user, the probability of a recogni- function/operation. Typical examples common among most
tion error for each letter may have increased compared to pen-based computing user interfaces are crossing a word
what it would have been before the HWX engine was out to delete it, circling a word to select it for editing, and
trained for recognizing the handwriting of a specific user. drawing a horizontal line to insert a space within text.
These problems are overcome to a good extent by using a The user will enter textual, as well as gesture and
character set where all the letters consist of a single stroke graphic (drawing/sketching) input, and thus the user
and their form is designed for ease of recognition (i.e., a interface is required to distinguish between these forms
specific HWX engine has been pre trained for use with that of input. The user interface of some pen-based computing
particular character set). One such character set is shown OS, especially those that are extensions of conventional
in Fig 3. OS, separate the different types of input by forcing the
As can be seen in Fig. 3, the characters are chosen to user to set the appropriate mode, for example pressing an
resemble their alphabetic equivalents as much as possible. on-screen button to enter the drawing/sketching mode.
The use of such a character set forces different users to This technique is uncomfortable for the user as it detracts
write largely the same way and to not form their own from the conventional pen and paper experience, and so
writing style, which is the tendency when using more the preferred method is for the OS to use semantic context
than one stroke per letter. information to separate the input. For example, if the user
is in the middle of writing a word and they write the
The User Interface character ‘O’, the OS would consider the fact that they
were writing a word and so would not confuse the char-
The overall objective of a user interface that supports
acter ‘O’ with a circle or the number zero. This latter
handwriting recognition is to provide the user with vir-
method is typical of OS written specifically for pen-based
tually the same experience as using conventional pen as
computing (Pen-centric OS).
paper. Thus, most of its requirements can be derived from
The causes of recognition errors fall into two main
the pen and paper interface. This means that ideally, no
categories. One is where the errors are caused by indis-
constraints should as to where on the digitizing tablet/
tinguishable pairs of characters, (for example the inability
screen (paper) the user writes, the size of their writing,
of the recognizer to distinguish between ‘2’ and ‘Z’). The
or even when they write and when online recognition can
best solution in this case is for the OS to make use of
take place. Obviously, conventional pen and paper does not
semantic context information. The other main source of
impose any restrictions on special characters with accents,
errors is when some of the user’s character forms are
so ideally the user could write such characters and they
unrecognizable. As explained previously, this situation
should be recognized and converted to text form. Although
can be improved in two ways. One is for the user to adapt
even in pen-based computing, the standard character set
their handwriting style, so that their characters are a
used is ASCII as opposed to Unicode, which is the standar-
closer match to the recognizer’s pre-stored models; the
dized character set that contains all characters of every
other way is to adapt the recognizer’s pre-stored models; to
language throughout the world.
be a closer match with the user’s character forms (trained
As the pen is the sole input device, it is used for all the
recognition) (5).
user’s interfacing action. As well as text entry, it is also used
for operations that a conventional mouse would be used for,
An Experiment Investigating the Dependencies of User
such as selecting menu options, clicking on icons, and so.
Satisfaction with HWX Performance
The action of moving the mouse cursor over a specific icon/
menu-option and clicking on it is replaced entirely with A joint experiment carried out by Hewlett Packard (palo
simply tapping the pen on the item you would have clicked Alto, CA) and The University of Bristol Research. Labora-
on. A dragging operation is performed by tapping the pen on tories (Bnstd, UK) in 1995 investigated the influence of
the item to be dragged twice in quick succession (corre- HWX performance on user satisfaction (5). Twenty-four
sponding to the double clicking associated with the mouse), subjects with no prior knowledge of pen-based computing
keeping the pen in contact with the tablet after the second carried out predetermined tasks using three test applica-
tap and then dragging the selected item, and finally lifting tions as well as text copying tasks, after being given a brief
the pen off the tablet to drop the item. A pen-based com- tutorial on pen-based computing. The applications were
puter has no function keys or control keys (such as return, run on an IBM-compatible PC with Microsoft Windows for
space-bar, etc.) like a keyboard does, and as such a pen- Pen Software and using a Wacom digitizing tablet (which

4 PEN-BASED COMPUTING
10
each models a specific level within the user’s goal-hierarchy
9 from high-level goal and task analysis to low-level analysis
appropriateness ratin
of motor-level (physical) activity. cognitive models fall into
8
two broad categories: those that address how a user
7
fax acquires or formulates a plan of activity and those that
6
records address how a user executes that plan. Considering appli-
5
diary cations that support pen input, whether they are exten-
4
sions of conventional applications that support only
3 keyboard and mouse input or special pen-centric applica-
2 tions, the actual tasks and associated subtasks that need
to be performed are often the same as those in conventional
1
applications. Only the task execution differs because of the
80 - 83.9 84 - 87.9 88 - 91.9 92 - 95.9
different user interface. Thus, only cognitive models that
% recognition accuracy
address the user’s execution of a plan once they have
Figure 4. Plots of appropriateness rating against recognition acquired/formulated it shall be considered, as a means of
accuracy .
evaluating the pen interface.
Adaptation of the Keystroke-Level Model for Pen-based
did not present a direct-manipulation input device as it was
Computers
not integrated with the screen). The three applications
were Fax/Memo, Records, and Diary, and they were
The keystroke-level model (KLM) (6) is detailed in Table 1.
devised to contrast with each other in the amount of
This model was developed and validated by Card, Newell,
HWX required for task completion, tolerance to erroneous
and Moran, and is used to make detailed predictions about
HWX text, and the balance between use of the pen for text
user performance with a keyboard and mouse interface in
entry and other functions performed normally using a
terms of execution times. It is aimed at simple command
mouse. The mean recognition rate for lowercase letters
sequences and low-level unit tasks within the interaction
was found to be 90.9%, and 76.1% for upper case letters,
hierarchy and is regarded widely as a standard in the field
with the lower recognition rate for uppercase letters caused
of human-computer interaction.
mainly by identical upper and lower case forms with letters
KLM assumes a user first builds up a mental represen-
such as ‘C’, ‘O’, ‘S’, ‘V’. Pen-based computing OS’ attempt to
tation of a task in working out deciding exactly how they
deal with this problem by comparing the size of drawn
will accomplish the task using the facilities and function-
letters relative to each other or relative to comb-guides
ality offered by the system. This assumption means that no
when the user input is confined to certain fields/boxes.
high-level mental activity is considered during the second
As can be observed Fig. 4, the application that required
phase of completing a task, which is the actual execution of
the least amount of text recognition (Records) was rated as
the plan acquired and is this execution phase that KLM
most appropriate for use with pen input, and the applica-
focuses on. KLM consists of seven operators, five physical
tion with the most amount of text recognition (Diary) was
motor operators, a mental operator, and a system response
rated as the least appropriate in this respect. Figure 4 also
operator. The KLM model of the task execution by a user
shows that higher recognition accuracy is met with a higher
consists of interleaved instances of the operators. Table 2
appropriateness rating by the user, and the more depen-
details the penstroke-level model (PLM), which represents
dent an application is on text recognition the stronger this
a corresponding set of operators for pen-based systems.
relationship is.
As stated previously, the actual tasks that need to be
An indication of this last point can be observed from the
performed to achieve specific goals are largely the same
plots shown in Fig. 4, as the average gradient of an applica-
with pen-based and keyboard and mouse-based systems,
tion’s plot increases as it becomes more dependent on text
recognition. The results shown in fig. 4 also suggest that
the pen interface is most effective in performing the non Table 1. A description of the KLM model’s seven operators
textual functions associated normally with the mouse.
Operator Description
Thus, improving recognition accuracy would increase the
K Key stroking, actually striking keys,
diversity of applications in pen-based computing, as those
including shifts and other modifier
more dependent on text entry would be made more effective
keys
and viable.
B Pressing a mouse button
P Pointing, moving the mouse
COGNITIVE MODELLING (or similar device) as a target
H Homing, switching the hand
between mouse and keyboard
D Drawing lines using the mouse
Introduction to Cognitive Models
M Mentally preparing for physical
Cognitive models as applied to human–computer interac- action
R System response which may be
tion represent the mental processes that occur in the mind
ignored if the user does not have
of the user as they perform tasks by way of interacting
to wait for it, as in copy typing
with a user interface. A range of cognitive models exits, and

PEN-BASED COMPUTING 5
Table 2. The PLM model, a set of operators for a pen-based user interface corresponding to those of the KLM model
Operator Description
K’ Striking a key or any combination of keys is replaced in pen-based systems with writing a single character or drawing
a single gesture. It is widely accepted in the field of HCI that a reasonably good typist can type faster than they can write.
Although holding down a combination of keys is effectively one individual key press for each key, as the position of
each key is stored as a one chunk in human memory. Some keys are not as familiar to a user as the character keys,
as they are used less frequently. Thus if the user has to look for a key (e.g. the shift key) then it is reasonable to assume
that the action of drawing a single gesture would be of a comparable speed.
B’ This operation is replaced in pen-based systems with tapping the pen once on the screen, which is essentially the same action
as marking a full-stop/period or doting an ‘i’ or ‘j’, and it is a better developed motor skill. No reason exists to believe or
evidence either way to suggest that B or B’ is faster than the other for a specific user.
P’ This operation is replaced in pen-based systems with the action of moving the pen over the screen, but the pen does not have
to be in continuous contact with the digitizing tablet. Thus, the cursor can be moved from one side of the screen to the other
simply by lifting it from one side and placing it on the other side. This action makes the pen interface more ergonomic than the
mouse in this type of situation as the user’s hand need no longer be in a state of tension while performing this action.
This action is a prime example of the benefits of a direct-manipulation interface.
H’ The homing operator is one for which no corresponding operator exists for pen-based systems, as the pen is the sole
input device. This decreases the overall execution time when using a pen interface compared with a keyboard and mouse.
D’ This operation is replaced in pen-based systems with the action of drawing with the pen, where again the benefits of
direct manipulation are observed, as it is just like drawing using pen and paper, which is a much better developed set
of motor-skills, especially when drawing curved lines/strokes that compose a sketch/drawing.
M’ Because the KLM model assumes the user has formulated a plan and worked out how to execute it, the mental preparation
modelled by the M and M’-operator is simply the time taken by the user to recall what to do next. Thus it is reasonable to
assume that the time taken up by an occurrence of an M or M’-operator is the same for pen-based systems as it is for
keyboard and mouse-based systems for each user. Although it is reasonable to assume that if one was the slower of the two
it would be M, because with keyboard and mouse-based systems, the user has to recall which input device (keyboard or
mouse) they need to use.
R’ Assuming the two systems were of a similar overall capability, it is reasonable to assume that the system response time for
a pen-based system and a keyboard and mouse-based system would be the same. However, the process of HWX is more
intensive computationally than reading keyboard input, so a pen-based system’s processor would need to be faster than
that of a keyboard and mouse-based system to be perceived by the user as being of comparable speed.
and I have thus adapted the KLM model into the PLM task, two targets were on either side of the screen as
model for application to pen-based systems. shown in Fig. 5.
From Table 2, it can be reserved that at worst, pen- In the experiment, an elemental pointing action was
based systems have one less physical motor operator than considered to be moving the cursor over a target and then
keyboard and mouse-based systems, and at best two of its clicking the mouse/trackball button or pressing the pen
four physical motor operators have quicker execution down onto the tablet to close its tip-switch, (as opposed to
times compared with the corresponding operators of key- the tapping action with the modern stylus and digitizer
board and mouse-based systems for each user. This abser- combinations which terminated an action and initiated the
vation suggests that pen-based systems are faster to use next action. An elemental dragging action was considered
than keyboard and mouse-based systems, and the pre- to be selecting an object within one target and holding down
vious discussion would suggest that this is especially true the mouse/trackball button or maintaining the pressure
for applications that contain many pointing and dragging of the stylus on the tablet, dragging it to within the other
tasks. target and then releasing the mouse/trackball button or
pressure on the tablet to drop the object in that target,
Experiment to Compare the Performance of the Mouse, Stylus which terminated an action and initiated the next action
and Tablet and Trackball in Pointing and Dragging Tasks where each time the new object would appear halfway
between the two targets. Fitts’ law provides a formula
An experiment by Buxton, et al. in 1991 (7) compared the
[shown below in its most common form in Equation (1) to
performance of the mouse, stylus (and digitizing tablet),
and the trackball (which is essentially an upside-down
mouse, with a button by the ball) in elemental pointing
and dragging tasks. Performance was measured in terms
of mean execution times of identical elemental tasks.
However, the digitizing tablet was used in a form where
it was not integrated with the display and sat on the users
desktop, and thus it could not be considered a direct-
manipulation interface as is the case when it is integrated
with the screen. The participants of the experiment were
12 paid volunteers who were computer-literate college
students. During both the pointing and the dragging Figure 5. The on-screen user-interface used for dragging tasks.

6 PEN-BASED COMPUTING
1400 Table 3. Tabulated form of the plots shown in Figure 6
Average MT: Average MT:
elemental elemental
1200
Mean MT (ms)
Input device pointing dragging
Stylus & Tablet 665 ms 802 ms
Mouse 674 ms 916 ms
1000 Dragging
Trackball 1101 ms 1284 ms
800 nated erroneously (which the user was notified of via a
Pointing
beep) were also eliminated, as many people who had inves-
tigated repetitive, self paced, and serial tasks concluded
that erroneous executions were disruptive to the user
600
and could cause an abnormally long response time
Trackball
Mouse Tablet
for the following trial, which would have skewed the aver-
Device age execution time. Analysis also showed a significant
reduction in execution times after the first session,
Figure 6. Graph showing execution times of three devices for
and thus the entire first session for each subject, for each
elemental pointing and dragging tasks.
device task type combination was also eliminated. Figure 6
and Table 3 show the mean movement times (execution
calculate the time taken for a specific user to move the times) over all blocks for each device and for the two task
cursor to an on-screen target. types, after the adjustments mentioned above were made.
As can be seen in Fig. 6 and in Table 3, the pen and
Movement Time ¼ a þ blog2ðDistance=ðSize þ 1ÞÞ (1) digitizing tablet was fastest in both task types, although the
performance of the mouse was comparable in the pointing
As can be observed from Equation (1), according to Fitts’ task. The results show that the performance of each device
law the time taken to move to the target depends on the was better in the pointing task than in the dragging task.
distance the cursor needs to be moved and the size of the This seems reasonable as when dragging the hand (and the
target. Constants a and b are determinable empirically for forearm in the case of the pen and digitizing tablet) is in a
each user. As Equation (1) shows, a greater distance is state of greater tension compared with when pointing. The
moved in a greater time, and a smaller target is more big difference in performance between the mouse and
difficult to acquire and thus also increases movement the pen and digitizing tablet was in the dragging task,
time. The distance between the targets shown in Fig. 5 where the performance gap for the pointing task was the
was varied over the range of discrete values (A ¼ 8, 16, 32, greatest with the mouse. Error rates for each device-task
64 units) where a unit refers to eight pixels. The size type were also evaluated and are shown in Fig. 7.
parameter of Equation (1) was represented by the width As with mean movement time, error rates were worse for
of the targets, as the movement of the cursor would largely the dragging task than they were for pointing. The unad-
be side-to-side, and this too was varied over the discrete justed results were evaluated before making the modifica-
range (W ¼ 1, 2, 4, 8 units). All values of the distance tions described above. The adjustment of eliminating errors
between targets A were fully crossed with all values of the greater than three standard deviations from the mean
width of the targets W for both the pointing and the drag-
ging tasks, and each A-W combination was used for a block 20
of 10 elemental tasks (pointing or dragging), where the
user’s objective was to carry out the ten tasks in succession Unadjusted
as quickly and a accurately as possible. Sixteen blocks were
Mean Percentage Errors
ordered randomly into a session, and five sessions were Dragging
completed for each device for each of the two types of tasks.
Adjusted
The results showed that subjects occasionally would drop
the object a long way from the target. This was not because 10
of normal motor variability but occurred because of the
difficulty in sustaining the tension in the hand required to
perform dragging. It was particularly evident with the
Pointing
trackball, where the ball has to be rolled with the fingers Unadjusted
while holding the button down with the thumb. The results
Adjusted
were adjusted to remove these errors by eliminating ele-
mental task executions within each block that were termi- 0
nated (by a click or release) a horizontal distance from the Mouse Tablet Trackball
mean termination distance greater than three standard Device
deviations. This adjustment was made separately for each
subject, A-W combination, device, and task type. Elemental Figure 7. Graphs to show the mean error rates for three devices
task executions immediately after those that were termi- during pointing and dragging tasks.

PEN-BASED COMPUTING 7
termination distance from the target (as described above) using a pen than for using a mouse. The only exception to
was also applied to the pointing task, although dropping this is the B or B’-operator (pressing a mouse button/
errors could not have occurred during the pointing task. tapping the pen on the digitizing tablet), with which no
The results shown in Fig. 7 show that the mouse had a lower evidence suggests which is faster than the other, but
(but comparable) error rate compared with the pen and usually this operator is combined with the P or P’-operator
digitizing tablet in the pointing task, and had a much lower (pointing), and reasons exist to believe this method is faster
error rate than in the dragging task. The 12 participants using pen-based systems than keyboard and mouse-based
were computer literate, and because the mouse is the systems.
standard interface device for pointing and dragging, this The results of the experiment conducted by Buxton et al.
finding suggests that on average they would have been (7) discussed previously support these facts by showing the
more familiar with the mouse than they were with the pen pen to be faster than the mouse (and the trackball) for both
and digitizing tablet (in the non–direct-manipulation form pointing and dragging tasks. Although the results showed
that was employed in this experiment). Thus, they would higher error rates during both pointing and dragging for
have had better developed motor skills for pointing and the pen than for the mouse. It is reasonable to assume that
dragging using a mouse. It is reasonable to assume that the this was because the experiment used the indirect-manip-
pen and digitizing tablet interface in its direct-manipula- ulation form of the digitizing tablet (where it is not inte-
tion form would have yielded fewer errors all round, but grated with the screen). With this configuration of the
almost certainly in pointing as the user would no longer digitizing tablet the user is confined to using a low inter-
have to track the position of the cursor between the targets. activity-level input mechanism just as they are when using
The user could simply perform a dotting action on the a mouse, but with a less familiar input device as this
targets in an alternate fashion, which as well as eliminat- configuration of the digitizing tablet does not resemble
ing errors would have boosted the speed of elemental the conventional pen and paper metaphor like the direct-
pointing tasks. manipulation configuration does.
CONCLUSIONS BIBLIOGRAPHY
The results of the experiment conducted by Hewlett Pack- 1. PDA vs. Laptop: a comparison of two versions of a nursing
documentation application. Center for Computer Research
ard and The University of Bristol research labs (5) dis-
Development, Puerto Rico University, Mayaguez, Puerto Rico.
cussed previously suggest that the pen interface is very
2. N-trig http://www.n-trig.com.
effective for pointing and dragging tasks. Although subject
feedback gave applications a lower appropriateness rating 3. http://msdn2.microsoft.com/en-us/library/ms811395.aspx.
(for use with pen input), its handwriting recognition func- 4. Multimodal Integration for Advanced Multimedia Interfaces
tionality was more significant and vital in task execution. ESPRIT III Basic Research Project 8579. Avalable: http://
hwr.nici.kun.nl/~miami/taxonomy/node1.html.
Overall, the results of the experiment conveyed the impres-
sion that the pen was comparable with the mouse for 5. Recognition accuracy and user acceptance of pen interfaces.
University of Bristol Research Laboratories; Hewlett Packard
pointing and dragging tasks, but not as good as the key-
CHI ’95 Proceedings and Papers. Avalable: http://www.ac-
board for text entry because of relatively high recognition
m.org/sigs/sigchi/chi95/Electronic/documnts/.
error rates.
6. A. Dix, J. Finlay, G. Abowd, R. Beale‘‘Humancomputer Inter-
In my attempt at a direct comparison of pen-based and
action 2nd ed.’’ Englewood.Cliffs, NJ: 1998.
keyboard and mouse-based systems it was shown that pen-
7. A Comparison of Input Devices in Elemental Pointing and
based systems are the simpler of the two in a cognitive
Dragging Tasks. Avalable: http://www.billbuxton.com/fitts91.
sense, because the overhead associated with switching the
html.
hand between the mouse and the keyboard is removed with
pen-based systems as the pen is the sole input device. The
other operators in the model most likely have quicker DR. SANDIP JASSAR
execution times than their KLM equivalents for a specific Leicester, United Kingdom
user as a result of the direct-manipulation input device that
is the integrated digitizer and screen and because of the
more advanced motor skills that most users will have for