EVALUATION OF ANTHROPOMORPHIC USER INTERFACE
FEEDBACK IN AN EMAIL CLIENT CONTEXT AND
AFFORDANCES
Pietro Murano
1
, Amir Malik
1
and Patrik O’Brian Holt
2
1
School of Computing Science and Engineering, University of Salford, Gt. Manchester, M5 4WT, U.K.
2
Interactive Systems Research Group, School of Computing, The Robert Gordon University
St. Andrew Street, Aberdeen, AB25 1HG, Scotland
Keywords: Anthropomorphism, User interface feedback, Evaluation, Affordances.
Abstract: This paper describes an experiment and its results concerning research that has been going on for a number
of years in the area of anthropomorphic user interface feedback. The main aims of the research have been to
examine the effectiveness and user satisfaction of anthropomorphic feedback. The results are of use to all
user interface designers. Currently the work in the area of anthropomorphic feedback does not have any
global conclusions concerning its effectiveness and user satisfaction capabilities. This research is
investigating finding a way for reaching some global conclusions concerning this type of feedback. This
experiment, concerned the context of downloading, installing and configuring an email client which is part
of the domain of software for systems usage. Anthropomorphic feedback was compared against an
equivalent non-anthropomorphic feedback. The results indicated the anthropomorphic feedback to be more
effective and preferred by users. It was also the aim to examine the types of feedback in relation to
Affordances. The results obtained can be explained in terms of the Theory of Affordances.
1 INTRODUCTION
The user interface is one of the most important
aspects of any software system used by humans.
Badly designed user interfaces can lead to decreased
productivity, less profits for a company (due to
reduced productivity and more errors) and
frustration for the end users.
The aim of this research is to improve user
interface feedback and discover which methods may
be best. The authors are particularly investigating
the effectiveness and user satisfaction of
anthropomorphic feedback. To achieve this direct
comparisons are being made with non-
anthropomorphic feedback in an experimental
setting. Furthermore, the authors of this paper are
also trying to explain the results of conducted
experiments in terms of appropriate theories. One
such theory that is being investigated in conjunction
with the experimental results is the Theory of
Affordances.
Anthropomorphism at the user interface usually
involves some part of the user interface, taking on
some human quality (De Angeli, Johnson, and
Coventry, 2001). Some examples include a synthetic
character acting as an assistant or a video clip of a
human (Bengtsson, Burgoon, Cederberg, Bonito and
Lundeberg, 1999).
The area of anthropomorphic feedback has been
investigated for several years by various different
researchers. One aspect that is clear is that the
results available do not reveal an overall consistent
pattern. In some cases anthropomorphic feedback is
shown to be more effective and preferred by users
and in some cases the converse has been shown.
This is also shown in the work of Murano and his
collaborators (see Murano, 2002a, 2002b, 2003,
2005, Murano, Gee and Holt, 2007 and Murano, Ede
and Holt, 2008).
An example can be seen in a study by Moreno
Mayer and Lester (2000). The main thrust of their
experiment involved comparing anthropomorphic
and non-anthropomorphic information presented in
the context of tutoring about plant designs. Their
results suggested that the anthropomorphic
information was better for ‘transfer’ issues (i.e.
using the knowledge to solve new similar problems)
15
Murano P., Malik A. and O’Brian Holt P. (2009).
EVALUATION OF ANTHROPOMORPHIC USER INTERFACE FEEDBACK IN AN EMAIL CLIENT CONTEXT AND AFFORDANCES.
In Proceedings of the 11th International Conference on Enterprise Information Systems - Human-Computer Interaction, pages 15-20
DOI: 10.5220/0001856000150020
Copyright
c
SciTePress
and better in terms of users’ having a more positive
attitude and inclination towards learning more about
plant designs.
However a contrasting example can be seen in a
study by Moundridou and Virvou (2002). They also
tested anthropomorphic information and equivalent
non-anthropomorphic information in the context of
algebra tutoring. They found no significant
differences to do with issues of effectiveness of the
feedback types. However they did find significant
differences in terms of user attitudes, where the
anthropomorphic feedback fostered better user
attitudes.
Also in the realm of the author’s work (Murano,
2002b, 2005), a study conducted in the context of
English as a foreign language pronunciation,
anthropomorphic and non-anthropomorphic
feedback types were compared. This experiment
indicated with significant results that the
anthropomorphic feedback was more effective and
preferred by users.
However in another experiment conducted by
the author (Murano et al, 2008) in the context of PC
building, comparing anthropomorphic and non-
anthropomorphic feedback, the results showed no
difference in terms of effectiveness. However there
was a marginal result showing the anthropomorphic
feedback to be preferred by users.
This brief review of some of the literature
indicates that the study of anthropomorphism as a
means of user interface feedback is incomplete.
While some of the differences in results could be
attributed to experimental design issues, some of the
differences could be attributed to issues of
affordances at the user interface.
The original Theory of Affordances (Gibson,
1979) has been extended by Hartson (2003) to cover
user interface aspects. Hartson identifies cognitive,
physical, functional and sensory affordances. He
argues that when a user is doing some computer
related task, they are using cognitive, physical and
sensory actions. Cognitive affordances involve ‘a
design feature that helps, supports, facilitates, or
enables thinking and/or knowing about something’
(Hartson, 2003). One example of this aspect
concerns giving feedback to a user that is clear and
precise. If one labels a button, the label should
convey to the user what will happen if the button is
clicked. Physical affordances are ‘a design feature
that helps, aids, supports, facilitates, or enables
physically doing something’ (Hartson, 2003).
According to Hartson a button that can be clicked by
a user is a physical object acted on by a human and
its size should be large enough to elicit easy
clicking. This would therefore be a physical
affordance characteristic. Functional affordances
concern having some purpose in relation to a
physical affordance. One example is that clicking on
a button should have some purpose with a goal in
mind. The converse is that indiscriminately clicking
somewhere on the screen is not purposeful and has
no goal in mind. Lastly, sensory affordances concern
‘a design feature that helps, aids, supports, facilitates
or enables the user in sensing (e.g. seeing, feeling,
hearing) something’ (Hartson, 2003). Sensory
affordances are linked to the earlier cognitive and
physical affordances as they complement one
another. This means that the users need to be able to
‘sense’ the cognitive and physical affordances so
that these affordances can help the user.
Therefore the remaining sections in this paper
will discuss the results of an unpublished experiment
and links will be made to the affordances as
identified by Hartson (2003).
2 EMAIL CLIENT EXPERIMENT
2.1 Aims
The aim of this experiment was to gather data
regarding effectiveness and user satisfaction in the
downloading, installing and configuring of an email
client context which is part of the domain of
software for systems usage. Specifically the aim was
to find out if anthropomorphic user interface
feedback fostered a better interaction experience
with fewer errors and therefore a better task
completion rate.
Two identical prototypes were developed with
only the feedback methods varying. The first had
textual feedback available and the second had
anthropomorphic feedback in the form of the MS
Agent Merlin character with voice and speech
bubbles. The system was built to identically emulate
the basic task of downloading, installing and
applying a basic configuration to the Kerio (2006)
email client.
Further, the authors were also interested to find
out if the user interfaces designed were appropriately
facilitating the affordances.
2.2 Users
20 participants were used in the experiment.
These were selected by means of contacts at
local colleges and personal acquaintances.
All the participants taking part in the study were
in the 18-40 age groups.
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Although gender was not the main issue of this
research, the participants were all adult males
and females.
All the participants were novices in terms of
overall computing experience.
All participants had downloaded software
from the Internet in the past, but had not
downloaded email clients. However most
participants had experienced difficulty with the
downloading and installation process.
2.3 Design
A between users design was used. The 20
participants were randomly assigned to one of the
two conditions being tested. Random allocation to
one of the two experimental groups was achieved by
alternately assigning an individual to one of the
groups.
2.4 Variables
The independent variable was the type of feedback,
(Textual instructions - Non-anthropomorphic and
MS Agent synthetic character – Anthropomorphic).
The dependent variables were the participants’
performance in carrying out the tasks and their
subjective opinions.
The dependent measures were that the
performance was measured by counting the number
of input errors made, the number of incorrect
selections, the number of requests for help, the
number of manifested participant hesitations – minor
or major in nature (A minor hesitation was of the
kind that involved a participant taking longer than
ten seconds to choose an option after having
obtained some feedback. A major hesitation was
when a participant was given some feedback and
then proceeded to not take any action at all) and
whether the participant completed a task. These
factors were then used in a scoring formula in order
to achieve a single score per participant (see note
below). The formula was devised because it was felt
that the factors of errors, hesitations and actually
completing the tasks, were related to overall success.
These factors were recorded by means of an
observation protocol.
The subjective opinions were measured by
means of a post-experiment questionnaire, which
included questions regarding the user interface and
the users’ experience etc.
(NOTE – The formula used was as follows:
Each participant (unknown to them) was started
on ten points for each task.
For every incorrect selection made, one point
was deducted. An example of this ‘error’ was
the participant not selecting the ‘next’ option to
begin the installation process.
For every input error made, one point was
deducted. An example of this ‘error’ was the
participant not entering a password for the email
account.
For every obvious minor (>ten seconds)
hesitation, e.g. taking longer than ten seconds to
make choose an option after having received
feedback, half a point was deducted.
For every obvious major hesitation, e.g. the
participant being given some feedback and then
not acting on the feedback at all, one point was
deducted.
For every help request made, one point was
deducted.
If the participant completed a task correctly the
score was left as described above.
If the participant did not complete a task a
further one and a half points were deducted to
give a final score.)
In the actual experiment no major hesitations
were observed and all participants completed the
task, therefore two elements of the formula
described above were not used in practice.
2.5 Apparatus and Materials
The equipment used for the experiment was: A
laptop running Windows XP and 448 Mb RAM, the
laptop’s own speakers and TFT display were used,
Microsoft Agent 2.0 ActiveX component and
Lernout and Hauspie TruVoice Text-To-Speech
engine. Lastly the prototype was engineered with
Visual Basic 6.
2.6 Procedure and Tasks
The first step was to recruit a suitable number of
participants particularly meeting the requirement of
being novices to computers, not having downloaded
and installed email clients in the past and if any
other software had been downloaded in the past that
some degree of difficulty had been experienced on
their part (see Users section above). The recruitment
process was achieved by the participants completing
a pre-experiment questionnaire. The questionnaire
had various questions which were mainly designed
to elicit prospective participants’ experience with
computers, the Internet and downloading and
installing software (including email clients).
Each participant was briefed with the same
information, i.e.: 1. A brief narrative regarding the
EVALUATION OF ANTHROPOMORPHIC USER INTERFACE FEEDBACK IN AN EMAIL CLIENT CONTEXT
AND AFFORDANCES
17
purpose of the experiment. 2. The purpose of the
experiment was not to test the participant. 3.
Participants should do their best to concentrate
whilst carrying out the tasks. 4. Each participant was
given an explanation regarding the type of feedback
they would be using. 5. Most of their interaction
would be mouse based. 6. Feedback would be given
by the system if the participant made any errors. 7.
Participants were asked if the instructions were clear
and if not, further (un-biasing) explanations were
given. The further instructions did not use leading
language which would have given clues on how to
complete the task. Also no specific examples were
used to further attempt better control on the matter.
8. A post-experiment questionnaire would need to be
completed at the end of the experiment. 9. It was
verbally made clear that if they wanted to leave at
any time, they could do so and if they did not want
their data to be used at the end of the experiment,
that this was their prerogative. Also data collected as
part of the experiment would be kept confidential.
10. Completing the whole experiment would mean
each participant would be entered into a prize draw
for a £20 Selfridges voucher.
Then the procedure described below was carried
out in the same way for all participants using the
same environment, equipment and
questionnaires/observation protocols. Each
participant was treated in the same manner. This was
all in an effort to control any confounding variables.
There was one basic global task with several
stages. This was to download, install and prepare an
email domain with the Kerio email client. The
following stages were required to complete the
overall global task:
1. Click the appropriate download link. 2.
Choose a folder for storing the downloaded file. 3.
Await the download process to complete. 4. Initiate
the installation process. 5. Choose the appropriate
language. 6. Await the file extraction process to
complete. 7. Read the welcome message and choose
proceed. 8. Read the licence information and choose
proceed. 9. Select a folder for the Kerio email client.
10. Select the install type. 11. Await the installation
process to complete. 12. Use the Kerio configuration
wizard to create an email domain. 13. Enter an email
domain. 14. Enter a user name. 15. Enter a
password. 16. Complete the installation.
The session was started by the system presenting
a small tutorial using the feedback mode of the
relevant condition. The tutorial explained what the
task was and gave instructions regarding what had to
be done if help was required during the carrying out
of the task.
Once the tutorial material had been received by
the participants the actual task was undertaken with
the appropriate feedback condition. The simulation
that was built, emulated the actual stages required
for the task. Therefore each stage of the interaction
was accompanied by either anthropomorphic or non-
anthropomorphic instructions (depending on
experimental condition) regarding what had to be
done to complete the stage and go on to the next
stage. The instructions were basically of the kind
which instructed the user on what had to be done,
e.g. choosing a ‘typical’ installation and clicking
next etc. During the carrying out of the task, each
participant was observed and data was recoded on
the appropriate observation protocol.
Lastly the participants were asked to complete a
post-experiment questionnaire regarding their
subjective opinions about the software.
2.7 Results
The data was analysed using a multifactorial
analysis of variance (MANOVA) and when
significance was found, the particular issues were
then subjected to post-hoc testing using in all cases
either t-tests or Tukey HSD tests. The following
significant results were observed (NB: DF = Degrees
of Freedom, SS = Sum of Squares, MSq = Mean
Square):
For the variables ‘total score’ and ‘group’, there
is a significant (p < 0.05) difference. The
anthropomorphic group scored significantly higher
scores than the non-anthropomorphic group, with an
F-ratio of 4.87*. Table 1 shows the F Table:
Table 1: MANOVA, total score/group.
Source DF SS MSq F Ratio
Model 2 5.63 2.81 4.87
Error 17 9.81 0.58 Prob > F
C. Total 19 15.44 0.02
For the variables ‘Understandable UI feedback’
and ‘group’, there is a significant (p < 0.05)
difference. The anthropomorphic group felt that the
user interface feedback was significantly more
understandable when compared to the non-
anthropomorphic group, with an F-ratio of 3.83*.
Table 2 shows the F Table:
Table 2: MANOVA, understandable feedback/group.
Source DF SS MSq F Ratio
Model 2 1.80 0.90 3.83
Error 17 4.00 0.24 Prob > F
C. Total 19 5.80 0.04
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For the variables ‘Sufficient UI Feedback’ and
‘group’, there is a significant difference. The
anthropomorphic group felt that the user interface
feedback was significantly (p < 0.01) more sufficient
compared to the non-anthropomorphic group, with
an F-ratio of 10.37**. Table 3 shows the F Table:
Table 3: MANOVA, sufficient feedback/group.
Source DF SS MSq F Ratio
Model 2 2.50 1.25 10.37
Error 17 2.05 0.12 Prob > F
C. Total 19 4.55 0.001
For the variables ‘Friendly UI Feedback’ and
‘group’, there is a significant (p < 0.01) difference.
The anthropomorphic group felt that the user
interface feedback was significantly more friendly
compared to the non-anthropomorphic group, with
an F-ratio of 20.40***. Table 4 shows the F Table:
Table 4: MANOVA, friendly feedback/group.
Source DF SS MSq F Ratio
Model 2 7.20 3.60 20.40
Error 17 3.00 0.18 Prob > F
C. Total 19 10.20 <.0001
For the variables ‘UI Feedback not Intimidating’
and ‘group’, there is a significant (p < 0.01)
difference. The anthropomorphic group felt that the
user interface feedback was significantly less
intimidating compared to the non-anthropomorphic
group, with an F-ratio of 41.00***. Table 5 shows
the F Table:
Table 5: MANOVA, not intimidating feedback/group.
Source DF SS MSq F Ratio
Model 2 4.10 2.05 41.00
Error 17 0.85 0.05 Prob > F
C. Total 19 4.95 <.0001
For the help’ and ‘group’, there is a significant
(p < 0.01) difference. The anthropomorphic group
felt that the help given was significantly more
friendly compared to the non-anthropomorphic
group, with an F-ratio of 18.94***. Table 6 shows
the F Table:
Table 6: MANOVA, friendly help/group.
Source DF SS MSq F Ratio
Model 2 11.70 5.85 18.94
Error 17 5.25 0.31 Prob > F
C. Total 19 16.95 <.0001
For the variables ‘friendly error info’ and
‘group’, there is a significant (p < 0.01) difference.
The anthropomorphic group felt that the error
information given was significantly more friendly
compared to the non-anthropomorphic group, with
an F-ratio of 9.13**. Table 7 shows the F Table:
Table 7: MANOVA, friendly errors/group.
Source DF SS MSq F Ratio
Model 2 6.50 3.25 9.13
Error 17 6.05 0.36 Prob > F
C. Total 19 12.55 0.0020
2.8 Discussion of Results
The clearest result shows that the anthropomorphic
feedback was more effective for the global task of
downloading, installing and preparing an email
domain with the Kerio email client. The scores
achieved in the task were significantly higher in the
anthropomorphic condition.
As expected the perceptions of participants in the
anthropomorphic condition tended to be more
positive about the system. They clearly found the
task easier to complete and therefore had more
positive perceptions about the system. Specifically
they felt that the feedback was more understandable,
sufficient, friendly and less intimidating. Also the
anthropomorphic group felt that the help was more
friendly and that the error information was more
friendly in nature. The suggestion is that a higher
success rate in a task can elicit more positive
perceptions about a system.
Overall the results suggest that in the specific
context of downloading, installing and preparing an
email domain, the anthropomorphic feedback was
more effective and fostered more user satisfaction.
3 THE EXPERIMENT AND
AFFORDANCES
This experiment had results where the
anthropomorphic Merlin character condition was
significantly more effective and significantly more
satisfying for the participants. The anthropomorphic
condition had the Merlin character utter explanatory
speech, which was also displayed in speech bubbles
on the screen. The textual non-anthropomorphic
condition had the same text displayed in text boxes.
The difference in display design was that the text
boxes in the non-anthropomorphic condition were
not placed close to the area on the screen that they
were attempting to explain – compared to the
anthropomorphic condition. The result of this could
have been that the cognitive affordances would have
been negatively affected with respect to the
EVALUATION OF ANTHROPOMORPHIC USER INTERFACE FEEDBACK IN AN EMAIL CLIENT CONTEXT
AND AFFORDANCES
19
facilitation of the participant ‘knowing’ or ‘thinking’
appropriately about accomplishing the tasks. Further
the sensory affordances would have also been
affected and not provided the appropriate support for
the cognitive affordances. This could have happened
because part of the explanations for the download,
installation and configuring of the email client
involved completing form based aspects as part of
an on-screen dialogue. If the text boxes were not
close enough to the area requiring the interaction,
the sensory affordance concerning ‘seeing’ could
have been also negatively affected and therefore not
supported appropriately the cognitive affordance
aspect. The physical affordances in this experiment
tended to be the fields and buttons of the email client
dialogue, which were used by the participants with
the keyboard and mouse. These were the same under
both conditions and should therefore not have
affected matters either way. The functional
affordances should therefore not have been affected
either, as the experiment aimed to ‘explain’ or guide
the user through the various steps of the field filling
and dialogue stages. The actual results of the
statistical analysis give some support to this
argument because the participants in the non-
anthropomorphic condition significantly perceived
the feedback to be less understandable, insufficient,
less friendly and more intimidating. Lastly this
group achieved significantly lower performance
scores compared to the anthropomorphic group.
These aspects do suggest that due to the textual
instructions being laid out onto the screen in the
manner described, could have negatively affected
the various strands of affordances.
4 CONCLUSIONS
As has been considered in this paper, the study of
anthropomorphic feedback is still incomplete.
Various researchers have obtained disparate sets of
results with unclear reasons for these. However, the
authors of this paper, suggest that potentially the
issues of whether anthropomorphic feedback is more
effective and preferred by users, is strongly linked
with how the affordances are dealt with at the user
interface. This aspect could also provide a reason
regarding why there are so many disparate sets of
results in the wider research community, concerning
anthropomorphic feedback. Further, the principal
author of this paper is continuing to investigate these
issues and the affordances in light of other work by
the principal author of this paper and work of the
wider research community.
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