Laura K. Yohe

Proceedings of the Information Systems Education Conference.
Cincinnati, OH. November 1-4, 2001.
Laboratory
equipment (both hardware and software) for conducting experiments, usability
studies, and field studies in the area of human-computer interaction (HCI) is
typically complex, bulky, expensive, and intrusive. Recent strides in the development of surveillance software offer
the prospect of a non-invasive, inexpensive, and largely automatic way of
capturing data from user activities that could be useful to HCI professionals,
researchers, and educators. This project
investigates this possibility.
Keywords: human-computer interaction,
usability study, surveillance
An
article that appeared in the Wall Street Journal in March 2000 described two
low-cost surveillance software packages that were finding success on the market
(McCarthy 2000). This article coincided
with a problem that is common to small human-computer interaction (HCI) labs:
finding non-intrusive, inexpensive ways to monitor computer users during
experiments, usability studies, or field tests. Equipment and software being marketed for usability labs
currently costs tens of thousands of dollars, a sum beyond the reach of small
labs or companies (UserWorks 2001).
Surveillance software, however, is relatively inexpensive (a few hundred
dollars). We wondered whether such software
might be used in place of much more extensive (and expensive) lab setups which
typically use several video cameras and observation-recording software.
One
of the classic problems with observing users can be referred to as the
panopticon effect, Hawthorne effect (Preece et al 1994) or the
Heisenberg effect. Panopticon was a
term used by Jeremy Bentham in 1787 to describe a type of prison constructed in
the round, with cells on the outside of a central core that is manned by a
guard (Johnson 2001). The cell wall
facing the guard is a one-way window, so that the guard can see into each cell,
but the prisoners could not see the guard.
Bentham conjectured that it would not be necessary to always have a
guard present in order to ensure good behavior on the part of the prisoners,
since the prisoners could not verify when the guard was indeed present – they
would adopt behavior on the assumption that they were being observed. The Hawthorne effect refers to a study done
in 1939 in a Hawthorne, Illinois manufacturing plant. The Heisenberg effect comes from physics and, simply put, states
that the act of observing a particle changes the behavior (velocity or
direction) of that particle. All terms
apply to the problem of trying to observe users without affecting how they
behave. Such problems are nothing
really new, and can be traced back to the use of “efficiency experts” more than
100 years ago (Edgar 1997).
HCI
researchers and practitioners typically use video cameras to observe both the
user and the computer’s monitor during use.
While it is possible to hide the cameras to a certain extent, and while
some experts believe that users forget about the cameras in a short amount of
time (Shneiderman 1998), there are times when setting up several cameras is
difficult (such as in the field) or at least expensive. Furthermore, while a camera can faithfully
record most of the actions visible on the monitor, it is not recording the
actual actions of the user, i.e. what keys the user pressed, when the mouse was
clicked, which mouse button was clicked, etc.
While some of this could certainly be deduced by watching a videotape,
to do so would also be extremely time consuming (and, therefore, expensive). Automated data collection software has
largely been custom built and is not widely available, so videotaping is still
the preferred way of recording user interactions for most HCI professionals
(Drury et al 1999).
This
paper, then, describes an experiment conducted to determine whether
surveillance software could be used as an inexpensive, non-intrusive,
automatically logging tool for HCI work.
Two
software products were selected to test as possible HCI tools. One of the products proved to be too buggy
to use (inquiries to the company were ignored), and was dropped from the
study. The product selected, Silent
Watch by Adavi (Adavi 2001), has received substantial amounts of press in the
past year, so appeared that it might be a reasonable place to start our
project. Since this current project is more
of a feasibility study, it was decided that the initial study could
successfully be completed with a single product, leaving a comparative study of
multiple products to a future project.
Silent
Watch clearly fit the first two criteria we were concerned about, cost and
invisibility to the user. The product
costs about $225 per package, which includes a license for monitoring up to
four machines. Although software must
be installed on the machine to be monitored, an option in Silent Watch allows
it to be placed into “stealth” mode, so that the user has no way of discovering
that the software even exists on their machine. This is perfect for overcoming the Heisenberg effect, a
considerable concern in HCI studies.
The
major portion of the project, of course, is evaluating the software’s
performance for logging user activity.
Silent
Watch software consists of two parts: the viewer and the client. The viewer software is loaded onto the test
conductor’s computer to observe the test subject’s machine. The client software is loaded onto the test
subject’s computer to allow the viewer machine to pick up the image of the
subject’s machine as well as any use of the keyboard and mouse. Transactional information is transmitted
from the client to the viewer system over an existing local area network.

Figure 1: Main Window of
Viewer
Figure
1 shows a typical display of the viewer system. The viewer can be configured to monitor up to 49 users
simultaneously. The figure shows the
viewer configured for four users, with only one currently active (called
Nell). The client software records
keystrokes and other data (such as URLs) and forwards these records on to the
viewer system, which then updates the viewer display as well as its own
activity files. The amount of time
between snapshots of a client system is settable, with the minimum time of 3
second intervals.
The
question we hoped to answer was whether Silent Watch’s log files provided
enough detail that could be analyzed to provide meaningful information for a
usability study. Initial testing showed
that the two likeliest useful files were the keystroke log and the URL
log.
The
keystroke log displays all characters entered from the keyboard, including
erasures made with the <backspace> key and special keys such as
<enter>, <shift>, and function keys (see Figure 2). In addition to displaying what has been
typed, it provides a time/date stamp down to the second and states when a user:
1.
logged
onto a machine, which is indicated by “Start Session” and the user login name,
2.
opened
an application, which is indicated by “Created” and the name of the
application,
3.
activated
an already open application, which is indicated by “Activated” and the name of
the application, and
4.
closed
an application, which is indicated by “Closed” and the name of the application
(Adavi, 2000).
The URL log specifically displays the Uniform Resource Locator (URL), i.e. website addresses, for every Internet site the machine has accessed or attempted to access. It continues to log this information even when the viewer machine is off. A sample of the URL log viewer can be seen in Figure 3. It can be saved and printed by using the options in its file menu. For every address, there is a time/date stamp down to the minute that shows when the site was accessed.


In
order to test the Silent Watch software, we created a dummy usability
experiment, ostensibly to study the differences between using a mouse,
trackball, and touch pad as a pointing device.
The intent was to pretend we were conducting a comparative experiment on
these devices while using the Silent Watch software to monitor the users’
interactions. The keystroke and URL
logs would then be analyzed to determine whether they provide any useful
information regarding the interactions.
Specifically, we were interested in whether the logs would show each
user’s actions accurately and with sufficient detail required of a real
usability study.
Twenty-two
computer science juniors and seniors in an HCI course were divided into three
groups, one for each pointing device.
Each student was given a set of written protocols to follow in order to
accomplish specific tasks. Protocols
were composed for four different activities: word processing, spreadsheet use,
Internet browsing, and using a graphing calculator. Figure 4 shows the protocol for the Internet Browsing task, along
with a typical resulting keystroke log.
In this example, note that although the keystroke log records most of
the activity of the protocol steps, it doesn’t do so discretely – most of the
actions have been recorded as part of the first time-stamped event in the
keystroke log.
The
test trials were conducted in the typical fashion for a usability study. The test conductor randomly assigned each of
the students to one of the three test groups.
One at a time the subjects were given one of the four protocols to
complete, as quickly as they could. The
tests were conducted in an HCI lab that was more or less isolated from other
activities. The test conductor observed
each test trial while monitoring the progress of each on a nearby system (which
contained the Silent Watch Viewer software).
Although the tests were not conducted in as rigorous a way as would be
normal for an actual usability study, the conditions were close enough to an
actual test as needed for our purposes.
The results of the protocols themselves are unimportant to this project
- it doesn’t matter how quickly or accurately the test subjects were actually
able to accomplish their given tasks.
Although we did some simple analysis of the test results, the purpose of
doing so was to see how well the log files that are automatically recorded by
Silent Watch captured the actions of the test subjects.
The
results were basically as expected, a mixture of success and failure, and a
promise of potential improvements that would produce a very useful tool.
First,
the additional overhead of the Silent Watch software does not appear to be
noticeable to the user, such as by adding in unexpected delays as a result of
logging activity. This was true even
though the systems the tests were conducted on were very slow by today’s standards
(200 MHz Pentium II’s). So the software
lived up to its promise of stealth.
This is important for two reasons: (1) users are not reminded (although
they are initially told) that they are being monitored by occasional delays of
the system during their activities, and (2) the use of the software does not
appear to add noticeable overhead time for completing tasks, so that timed
tests would be reasonably accurate.
Next,
the keystroke log does a pretty good job of recording what the user has entered
at the keyboard, including any special keys and function keys. Although all entered text is displayed in
all upper case, the actual characters entered can be deduced by following the
use of special keys such as <shift> and <caps lock> (it even differentiates
between the left and right shift keys). Time stamps for launching and closing applications are recorded to
the second, adequate perhaps for many kinds of usability studies. It was not difficult to calculate the time
between certain events using these time stamps. In addition, certain types of errors, especially typos, are
easily determined. It is easy to
imagine a program to assist in such mundane analysis, e.g. by counting the
number of times the <backspace> character appears in a log file or calculating
the time between two events. It is also
not very difficult to match up elements of the keystroke log with the protocol
steps, where that’s possible. For
instance, Figure 4 shows how some of the logged data matches the given
protocol.
The URL file is less useful. Although it contains the time a particular site is entered, and records even the launch of auxiliary components of a website (note the launching of go.msn.com in Figure 3, for instance), this information is only marginally useful, except, perhaps, in analyzing how a particular website launches, and how long it takes to complete the overall launch.
1.
Double
click on the Internet Explorer/Netscape Browser icon on the desktop
2.
Type www.yahoomail.com in the address slot of
the browser and hit enter
3.
Type
in user name and password
4.
Click
on check e-mail
5.
Click
on compose
6.
Send
the message to self
7.
Type
“This is a test” in the text box
8.
Click
on the “Send” button
9.
Type
www.wunderground.com in the address slot
of the browser and hit enter
10.
Type
“17601” in the text box for fast forecast and hit the <enter> key
11.
Type www.adavi.com
in the address slot of the browser and hit enter
12.
Click
on the Download tab
13.
Fill
in the text boxes but do not click on the “Download” button
14.
Type www.yahoo.com
in the address slot of the browser and hit enter
15.
Search
for some topic by typing the topic in the text box
16.
Type www.millersville.edu in the address slot
of the browser and hit enter
17.
Click
on the Max icon
18.
Click
on the “Personal Information” button
19.
Type
in user identification and password and hit enter.
20.
Type
in password again and hit enter
21.
Type
www.citibank.com in the address slot of
the browser and hit enter
22.
Select
United States from the country list
23.
Select
Credit Card Account Online from Products/Services List (automatically takes you
to the desired site)
24.
Type
in user name and password and hit enter
25.
Click
on the link for unbilled activity
26.
Click
on the “x” in the upper right corner of the window to close it
1. 10/30/00 10:09:28 AM - Activated http://www.msn.com/ - Microsoft
Internet Explorer
WWW.YAHOOMAIL.COM<Enter><Shift>LEORAH3779<Tab>******<Enter>
<Shift>LEORAH3779<Right Shift>@YAHOO.COM<Shift>THIS IS
A
TEST.WWWIW<Backspace><Backspace>.WUNDERGROUND.COM<Enter><Num
1>
<Num 7><Num 6><Num 0><Num 1><Num
Enter>WWW.ADAVI.COM<Enter>
<Shift>DR. <Right Shift>ROY
<Shift>ROGERS<Tab><Right Shift>ASSOCIATE
<Shift>PROFESSOR<Tab><Shift>TRIGGI<Backspace>ER
<Shift>UNIVERSITY<Tab><Shift>PO <Right Shift>
BOX 1002<Tab><Shift>DEPARTMENT OF <Right Shift>COMP
<Right
Shift>SCI<Tab><Shift>TEMPE<Tab><Shift>A<Right
Shift>Z<Tab><Num 1>
<Num 7><Num 5><Num 5><Num
1><Tab><Shift>UNITED <Right Shift>STATES OF <Right
Shift>AMERICA<Tab>717-123-4567<Tab><Shift>
ROGERS<Right
Shift>@CS.TRIGGER.EDU<Tab>WWW.YAHOO.COM<Enter>LOGGING
SOFTWARE<Enter>WWW.TRIGGER.EDU<Enter><Num 1>
<Num 7><Num 3><Num 6><Num 0><Num 2><Num
9><Num 9>
<Num 4><Tab><Num 0><Num 3><Num 0>
<Num 7><Num 7><Num 9><Num Enter><Num
0><Num 3><Num 0><Num 7>
<Num 7><Num 9><Num Enter>WWW.CITIBANK.COM<Enter>
23. 10/30/00 10:16:49 AM - Activated
https://www.accountonline.com/CB/Login.dcl -
Microsoft
Internet Explorer
<Shift>LEORAH3779<Tab>********<Enter>
26. 10/30/00 10:17:45 AM - Closed Unbilled Activity - Microsoft Internet
Explorer
Figure 4b: The Keystroke Log for the Internet Browsing Test. The numbers to the left of the time stamp indicate which operation in the protocol the logged event corresponds to. Note: Passwords in the log were replaced with “*,” but the log does record them in plain text.
On
the negative side are a number of shortcomings that would need to be addressed
before this particular product would be particularly useful for HCI work:
1.
The
time stamps are not fine enough. In the
keystroke log they are only down to the second. Down to the tenth of a second would make this feature much more
useful for usability research, as many actions can happen much faster than in
one second. In the URL log, time stamps
are only to the minute. Again, an order
of magnitude improvement in the accuracy of the time would be a great
improvement.
2.
Mouse
clicks are not recorded. Where and when
mouse buttons are activated is often important to HCI work. They need to be recorded, again probably
down to the tenth of a second.
3.
The
keystroke log is perhaps not complete enough for work on web applications. For instance, the field into which
particular data is being entered is not recorded.
4.
The
URL log does not record all web pages visited, only when each website is
entered. It would also be helpful to
record whenever a link (in whatever form: menu, button, embedded link, etc.) is
activated (including the time), although if all web page addresses were
recorded with a fine enough time stamp, this might be deduced.
5.
The
mouse icon is not visible on the Viewer screen, which makes it difficult for an
observer to follow the user’s actions.
Actions such as mouse clicks must be deduced by, for instance, observing
that a particular application has just been launched or a menu been displayed.
6.
There
is no ability to save the screen snapshots from the Viewer. This means that the screen would need to be
recorded to a video tape for later analysis, an additional step and expense of
equipment.
7.
The
minimum three second refresh cycle for data transmitted between the client
(subject) system and the viewer (test conductor) system is probably a bit too
long. One second would be preferable,
and with today’s fast machines should be possible without degrading the
performance of the client system. A
one-tenth cycle would be preferred.
This
study succeeded in identifying weaknesses of one surveillance software package
when attempting to use it as an HCI tool.
It further showed, however, that surveillance software has the potential
for such use. The weaknesses described
above are felt to be within the technical limits of software development and
the capabilities of current hardware.
An
extensive comparative study of other surveillance software packages might prove
instructive by perhaps identifying other products that already address some of
the concerns indicated above.
Ultimately it is hoped that we could assist companies such as Adavi to
further develop their surveillance products so that they would provide an
inexpensive tool for HCI professionals and educators.
5. Acknowledgements
Special thanks to Adavi, Inc. for their donation of the Silent Watch software for this project. Also, the laboratory equipment used in this study was made possible by National Science Foundation grant #DUE-9551245.
Adavi, Inc. www.adavi.com. June
2001.
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Johnson, Deborah. Computer
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