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content=3D"Christian G=FCtl, Maja Pivec, Christian Trummer, Victor =
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<H1 align=3Dcenter>AdeLE (<U>Ad</U>aptive <U>e</U>-<U>L</U>earning with=20
<U>E</U>ye-Tracking): <BR>Theoretical Background, System Architecture =
and=20
Application Scenarios</H1>
<P align=3Dcenter>&nbsp;(Extended version of the paper published in the=20
proceedings of the I-KNOW '04, Graz, Austria, 2004)</P>
<P align=3Dcenter>Christian G=FCtl <SUP><A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#1=
">1</A>,<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#3=
">3</A></SUP>=20
[<A href=3D"mailto:cguetl@iicm.edu">cguetl@iicm.edu</A> and <A=20
href=3D"mailto:cguetl@acm.org">cguetl@acm.org</A>], Maja Pivec <SUP><A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#2=
">2</A>,<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#4=
">4</A></SUP>=20
[<A =
href=3D"mailto:maja.pivec@fh-joannuem.at">maja.pivec@fh-joannuem.at</A> =
and <A=20
href=3D"mailto:mpivec@izit.si">mpivec@izit.si</A>], Christian Trummer =
<SUP><A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#2=
">2</A>=20
</SUP>[<A=20
href=3D"mailto:christian.trummer@fh-joannuem.at">christian.trummer@fh-joa=
nnuem.at</A>],=20
Victor Manuel Garc=EDa-Barrios <SUP><A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#1=
">1</A>,<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#5=
">5</A></SUP>=20
[<A href=3D"mailto:vgarcia@iicm.edu">vgarcia@iicm.edu</A> and <A=20
href=3D"mailto:victor.barrios@campus02.at">victor.barrios@campus02.at</A>=
], Felix=20
M=F6dritscher <SUP><A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#1=
">1</A>,<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#5=
">5</A></SUP>=20
[<A href=3D"mailto:fmoedrit@iicm.edu">fmoedrit@iicm.edu</A> and <A=20
href=3D"mailto:felix.moedritscher@campus02.at">felix.moedritscher@campus0=
2.at</A>],=20
Juergen Pripfl<SUP> <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#2=
">2</A>=20
</SUP>[<A=20
href=3D"mailto:juergen.pripfl@fh-joanneum.at">juergen.pripfl@fh-joanneum.=
at</A>],=20
Martin Umgeher<SUP> <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#2=
">2</A></SUP>=20
[<A=20
href=3D"mailto:martin.umgeher@fh-joanneum.at">martin.umgeher@fh-joanneum.=
at</A>]</P>
<HR>

<H2>Abstract</H2>
<P>Due to the rapidly growing amount of knowledge, a stronger need =
emerges for=20
efficient and improved knowledge acquisition strategies. E-learning can =
be very=20
helpful for different learning activities in various learning =
environments.=20
However, in order to support different teaching and learning paradigms,=20
e-learning should deal with more than simply reading online lessons. =
Therefore,=20
content as well as communication and collaboration have to be supported =
in a=20
highly personalised manner by e-learning systems. Though, tracking and =
grasping=20
the user behaviour in real time remains the most challenging task to =
retrieve an=20
appropriate and fine-grained user profile as well as to provide =
personalised=20
learning content. In this paper we present AdeLE, a technology-based =
solution of=20
an enhanced adaptive e-learning framework, which comprises novel =
solution=20
approaches for fine-grained user profiles by exploiting real time =
eye-tracking=20
and content-tracking analysis as well as a dynamic background library. =
Based on=20
the global objectives of an enhanced e-learning environment, the system=20
architecture of AdeLE and the methods used in order to gain fine-grained =
user=20
information by real time eye-tracking are addressed. Furthermore, =
various=20
scenarios in different application domains are illustrated.</P>
<P>Der rasch ansteigende Umfang an Wissen bedingt einen zunehmenden =
Bedarf an=20
effizienten und verbesserten Strategien von Wissenserwerb. E-Learning =
kann f=FCr=20
unterschiedliche Lernaktivit=E4ten in verschiedenen Lernumgebungen sehr =
hilfreich=20
sein. Um jedoch verschiedene Lehr- und Lernmethoden zu unterst=FCtzen, =
muss=20
E-Learning mehr als nur simples Lesen von Online-Lektionen bieten. =
Deshalb=20
sollten E-Learning-Systeme Inhalte als auch Kommunikations- und=20
Kollaborationsaktivit=E4ten in stark personalisierter Weise =
unterst=FCtzten. Um ein=20
geeignetes und feingranulares Benutzerprofil zu erhalten und um =
personalisierte=20
Lerninhalte zur Verf=FCgung zu stellen ist jedoch das Verfolgen und =
Erfassen vom=20
Benutzerverhalten in Echtzeit eine gro=DFe Herausforderung. In dieser =
Arbeit=20
pr=E4sentieren wir AdeLE, eine Technologie-basierte L=F6sung eines =
verbesserten=20
adaptiven E-Learning Frameworks, welches einen neuartigen =
L=F6sungsansatz f=FCr ein=20
feingranulares Benutzerprofil durch Nutzung von Real-Time Eye-Tracking =
und=20
Inhalts-Tracking Analysen sowie die Anwendung der dynamischen=20
Hintergrundbibliothek umfasst. Aufbauend auf den allgemeinen Zielen der=20
verbesserten E-Learning Umgebung werden die AdeLE Systemarchitektur und =
die=20
Methoden zur Gewinnung von feingranularen Benutzerinformationen mittels=20
Real-Time Eye-Tracking adressiert. Weiters werden verschieden=20
Anwendungsszenarien in unterschiedlichen Bereichen erl=E4uternd =
dargestellt.</P>
<H2>Keywords</H2>
<P>e-learning, adaptive knowledge transfer, dynamic background library, =
user=20
profiling, eye tracking, AdeLE</P>
<H2>1. Introduction</H2>
<P>It is well documented in renowned research publications and studies =
that the=20
increasing amount of knowledge and therefore the serious demands on =
knowledge=20
acquisition for students and employees requires improved and efficient =
learning=20
activities. Furthermore, people have to be supported and assisted during =
their=20
life-long learning activities. Traditional learning methods and =
environments do=20
not meet the contemporary needs of our information society any more. =
Thus,=20
technology-based solutions have been increasingly established to =
overcome these=20
problems. As a result, e-learning can be identified as one of the =
emerging areas=20
in the last few years, as shown by means of concrete numbers in the (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#I=
DC (2003)">IDC=20
2003</A>) study. About 934 Mio US$ were invested in e-learning worldwide =
in the=20
year 2003 and the European market is meant to be the best one. Though, a =
lot of=20
failures and only a few - in most cases locally restricted - success =
stories can=20
be identified (see also <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
aumgartner, P. (2003)">Baumgartner=20
2003</A>).</P>
<P>In this paper, we introduce our new solution approach, named AdeLE, =
which is=20
the abbreviation for 'Adaptive e-Learning with Eye- Tracking' and =
comprises a=20
technology-based solution in the field of adaptive e-learning exploiting =
novel=20
methods of resolution for fine-grained user profiling based on real-time =

eye-tracking and content tracking information. By applying fine-grained =
user=20
profiles and real-time behavioural data about users, a highly =
personalised=20
information provision and a wide range of new applications are =
facilitated.=20
Given that the objectives of technology-based educational environments =
and their=20
impact on individuals are linked with complex and context-dependent =
constraints=20
and conditions, we are conscious that the solution framework presented =
in this=20
paper may only be valid for specific sub-fields of e-learning. </P>
<P>In concrete, this paper represents an extended version of 'AdeLE: A =
Framework=20
for Adaptive E-Learning through Eye Tracking', presented at the IKNOW 04 =
(see <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
arc=EDa-Barrios, V. M.; G=FCtl, C.; Preis, A.; Andrews, K.; Pivec, M.; =
M=F6dritscher, F.; Trummer, C. (2004)">Garc=EDa-Barrios=20
et al. 2004</A>), whereupon the scope of this version is extended by and =
focused=20
onto a practical discussion of real-time eye-tracking and a description =
of=20
practical application domains. Thus, the reminder of the paper is =
organised as=20
follows: Section <I>2. Motivation</I>, describes key issues and =
requirements for=20
the proposed system, in Section <I>3. Related Work</I>, a selection of =
related=20
research topics is depicted, Section <I>4. Real-time Eye-tracking</I>, =
discusses=20
specific features of eye-tracking technology and the application of its=20
real-time application for the AdeLE framework, Section <I>5. =
Architectural=20
Overview of the AdeLE Framework</I>, provides a technical insight into =
the=20
modules of the AdeLE architecture, and in Section <I>6. Application=20
Scenarios</I>, examples of application areas for our solution approach =
are=20
discussed.</P>
<H2>2. Motivation</H2>
<P>Our previous experiences in the subject of e-learning (e.g. <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#D=
ietinger, T. (2003)">Dietinger=20
2003</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
arc=EDa-Barrios, V. M. (2001)">Garc=EDa-Barrios=20
et al. 2001</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#P=
ivec, M. (2000)">Pivec=20
2000</A>) have shown that learners tend to stick to distinct learning =
methods=20
and teachers favour various teaching methods. Consequently, e-learning =
involves=20
more than simply reading online lessons. </P>
<H3><B>Adaptive E-learning</B></H3>
<P>E-learning is a large and complex field of research encompassing a =
<I>variety=20
of learning and teaching paradigms</I>, such as constructivistic, =
serial,=20
symmetric (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#J=
ain, L. C., Howlett, R. J., Ischalkaranje, N. S., Tonfoni, G. =
(2002)">Jain=20
et al. 2002</A>), cognitive, face-to-face, discovery, and managed =
learning (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#L=
ennon, J.&nbsp;; Maurer, H. (2003)">Lennon=20
and Maurer 2003</A>). In addition, various levels of pre-knowledge as =
well as=20
progress and difficulties on lessons for individual learners have to be=20
considered. As stated in (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#J=
ain, L. C., Howlett, R. J., Ischalkaranje, N. S., Tonfoni, G. =
(2002)">Jain=20
et al. 2002</A>), e-learning, even if standardised, tends to produce=20
asymmetrical learning, as its tools reach out to a dispersed audience =
where=20
individuals may arrive at different stages at different times, even if =
along a=20
common learning trajectory. Furthermore, the personalisation of =
instructions and=20
interactivity improves the knowledge acquisition process. For example, a =
learner=20
in a classroom setting asks significantly less questions, whereas in an=20
individual tutoring setting, a learner may ask or is required to answer =
a lot of=20
questions in any learning session. Thus, the achievement of individually =
tutored=20
learners' performance, as measured by test scores, may significantly =
exceed that=20
of classroom colleagues; for details see (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#A=
DL (2001)">ADL=20
2001</A>) and (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
loom, B. S. (1984)">Bloom=20
1984</A>). These are some of the reasons for considering =
<I>personalisation</I>=20
and <I>adaptivity</I> to be one of the key issues in modern e-learning=20
environments.</P>
<H3><B>Key Issues and Objectives</B></H3>
<P>Following the observations and findings stated so far, it is worth =
mentioning=20
that in order to offer the appropriate learning method and to compile =
the=20
relevant learning assets and learning sequences for any individual =
learner, the=20
gathering and analysis of <I>fine-grained user profiling information =
</I>is a=20
serious technological challenge. Furthermore, just providing the =
technical=20
solution of delivering learning content from static learning =
repositories will=20
not meet all requirements for supplying teachers and learners with =
personalised=20
and timely information. In particular, the <I>knowledge transfer process =

</I>defines the key issue within the context of technology-based =
instructional=20
environments and it can be interpreted as a holistic phenomenon composed =
of two=20
related streams: the <I>teaching process</I> (knowledge generation and =
delivery=20
as well as assessment of knowledge acquisition) and the <I>learning =
process=20
</I>(knowledge acquisition). Both of them have to be supported by a=20
future-oriented approach. </P>
<P>Thus, the main objectives of an innovative solution for an e-learning =
system=20
are: </P>
<OL>
  <LI>personalised retrieval, management and presentation of relevant =
and timely=20
  information for learning activities,=20
  <LI>support of various learning and teaching paradigms, and=20
  <LI>improved knowledge of the users' behaviour in the field of =
human-computer=20
  interaction in general as well as related to the displayed learning =
contents=20
  in order to gain new insights and input for (1) and (2) as well. =
</LI></OL>
<P>Considering the above depicted aspects, we believe that a more =
extensive=20
solution framework is needed, which allows the binding together of =
effective=20
modern technologies and solution approaches in order to enhance the =
adaptation=20
of knowledge provisioning and to increase the effectiveness of =
personalisation.=20
This notion builds the basis of our solution approach, the AdeLE =
framework.=20
Unlike common methodologies of tracking page views and mouse clicks, we =
advocate=20
a combination of <I>fine-grained real time eye-tracking </I>and<I>=20
content-tracking </I>operations for the user profiling as well as =
complementing=20
the data stream by interactive system-user dialogs and online progress =
testing.=20
Furthermore, in the field of information acquisition for the teaching =
and=20
learning activities, we propose besides static learning assets also a =
highly=20
dynamic, task-specific and personalised information retrieval component, =
which=20
we call <I>dynamic background library</I>.</P>
<H3><B>Going the right way?</B></H3>
<P>To conclude this chapter, let us state that we are conscious and =
aware of the=20
fact that personalisation and adaptation should not be considered as=20
<I>universal goals or solutions for effective e-learning</I>. E-learning =

environments, adaptive systems and personalisation techniques have a lot =
of=20
proven weaknesses and have been (often justly) criticised by experts of=20
different fields.</P>
<P>Although we think that it is not necessary to repeat all drawbacks =
and=20
problems of personalisation extensively in this paper, consider the =
following=20
few examples of critical aspects regarding the application of =
personalised=20
e-learning. From the knowledge delivery viewpoint, there are some cases =
where=20
teachers want students to use exactly the same learning material in =
order to=20
provide a common experience and thus, to foster community-based =
learning. From=20
the viewpoint of knowledge acquisition and the support of different =
learning=20
styles as well as considering some findings coming from other research =
fields,=20
developers of adaptive systems should (a) exercise care in not allowing =
an=20
<I>information overload </I>on screen in order to improve the =
effectiveness of=20
working memory (for details about cognitive load theory see e.g. (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#C=
ooper, G. (1998)">Cooper=20
1998</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#F=
einberg, S., Murphy, M. (2000)">Feinberg=20
and Murphy 2000</A>), (b) enable the <I>scrutability of the user profile =
</I>in=20
order to give learners the overview and control of adaptational =
parameters, and=20
(c) consider <I>privacy and security issues </I>e.g. due to the =
intrusive=20
character of devices such as an eye-tracker system (see also <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#C=
zarkowski, M., Kay, J. (2003)">Czarkowski=20
and Kay 2003</A>).</P>
<H2>3. Related Research Fields</H2>
<P>The purpose of this chapter is, on the one hand, to show that the =
ideas=20
behind personalised e-learning are not as new as supposed. On the other =
hand,=20
this fact underscores that the field is broad and has a high potential =
of=20
interest and for research. Thus, in accordance to the basic issues =
behind the=20
idea of the AdeLE solution framework, a selection of some interesting =
subjects=20
related to the proposed system is discussed as follows.</P>
<H3><B>Adaptive E-learning, Standardisation and Learning =
Repositories</B></H3>
<P>The utilisation of adaptive multimedia systems as improved learning=20
environments are well documented in research work (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
rusilovsky, P. (1998)">Brusilovsky=20
1998a</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
rusilovsky, P. (1998)b">Brusilovsky=20
1998b</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#H=
othi, J., Hall, W. (1998)">Hothi=20
et al. 1998</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#S=
eeberg, C. (2003)">Seeberg=20
2003</A>), implementation concepts and systems can be found, for example =
in (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
eaumont, I., Brusilovsky, P. (1995)">Beaumont=20
et al. 1995</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#H=
ockemeyer, C. (1997)">Hockemeyer=20
1997;</A> <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
oyle, C.F., Encarnacion, A.O. (1998)">Boyle=20
et al. 1998</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#A=
RIADNE (2003)">ARIADNE=20
2003</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
arc=EDa-Barrios, V. M. (2001)">Garc=EDa-Barrios=20
2001b</A>). Tracking the behaviour of users and analysing their learning =

progress are not new research issues, but were demonstrated in classic =
systems=20
already in the 1950's. Well known early systems are CLASS and PLATO (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#C=
rowell, F. A., Traegde, S. C. (1967)">Crowell=20
1967</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#M=
odesitt, K. L. (1974)">Modesitt=20
1974</A>). In the present, novel user modelling techniques are important =
as they=20
allow systems to personalise the human-system interaction processes (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#C=
onlan, O., Dagger, D., Wade, V. (2002)">Conlan=20
et al. 2002</A>). </P>
<P>Well-defined learner model standards and specifications, like PAPI =
(Public=20
and Private Information for Learner - IEEE), IMS LIP (IMS Learner =
Information=20
Package) or GESTALT (Getting Educational Systems Talking Across =
Leading-edge=20
Technologies) already exist (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#P=
API (2000)">PAPI=20
2000</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#I=
MS LIP (2001)">IMS=20
LIP 2001</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
estalt (1999)">Gestalt=20
1999</A>). Furthermore, e-learning capabilities that enable =
interoperability,=20
accessibility, structuring, packaging and reusability of Web-based =
learning=20
content are also finding standardisation through advanced specification=20
initiatives, such as SCORM (Sharable Content Object Reference Model). =
Also=20
regarding courseware objects other well-known standards find broad =
application,=20
as for example LOM (Learning Object Metadata) in order to support =
semantic=20
enrichment, or IMS Simple Sequencing in order to define conditional=20
interrelationships of different successive nodes along an adaptable =
learning=20
path (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#L=
OM (2003)">LOM=20
2003</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#I=
MS (2003)">IMS=20
2003</A>). </P>
<P>The examples shown in the previous paragraphs point out that =
adaptivity and=20
personalisation constitute broad research fields with a relatively long =
history=20
and a large number of significant results (see also <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
rusilovsky, P. (1998)b">Brusilovsky=20
1998b</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#H=
othi, J., Hall, W. (1998)">Hothi=20
et al. 1998</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#B=
eaumont, I., Brusilovsky, P. (1995)">Beaumont=20
et al. 1995</A>). However, much work is still to be done towards =
existing or=20
emerging issues and challenges, especially more generic solutions are=20
needed.</P>
<P>Further, a lot of work is already done regarding the topic of =
learning=20
repositories. In the field of static learning assets there exist various =

initiatives as listed in (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#N=
LII (2004)">NLII=20
2004</A>), web information retrieval for assisting learning activities =
are=20
discussed for example in (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#L=
iaw, S.S.; Ting, I.H.; Tsai, Y.C. (2003)">Liaw=20
et al. 2003</A>), and the novel idea of the dynamic background libraries =
is well=20
documented in (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#D=
ietinger, T., Guetl, C., Kn=F6gler, B., Neussl, D., Schmaranz, K. =
(1999)">Dietinger=20
et al. 1999</A>) and (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
uetl, C. (2002)">Guetl=20
2002</A>). Though, to our knowledge no integrative solution combining =
static and=20
dynamic learning content in e-learning systems is available so far.</P>
<H3><B>Eye-Tracking Research Field</B></H3>
<P>The field of eye-tracking research is indeed an old but at present a =
very=20
active discipline. Nowadays, eye- and gaze-tracking systems are found in =
several=20
research fields, like scan-path testing on the WWW (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#J=
osephson, S., Holmes, M. E. (2002)">Josephson=20
et al. 2002</A>), research in the area of aviation (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#M=
erchant, S. (2001)">Merchant=20
2001</A>) or of driving environments (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#H=
ayhoe, M. M., Ballard, D. H., Triesch, J., Shinoda, H., Aivar, P., =
Sullivan, B. (2002)">Hayhoe=20
et al. 2002</A>), computational studies about visual cognition (see <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#R=
ao, R. P. N., Zelinsky, G. J., Hayhoe, M. M., Ballard, D. H. (1997)">Rao =

et al. 1997</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#Z=
hai, S. (2003)">Zhai=20
2003</A>), design implications in web search tasks (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
oldberg, J. H., Stimson, M. J., Lewenstein, M., Scott. N., Wichansky, A. =
M. (2002)">Goldberg=20
et al. 2002</A>), human computer interaction (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#I=
vory, M. Y., Hearst, M. A. (2001)">Ivory=20
et al. 2001</A>), and many others. Quite recently eye-tracking vendors =
began to=20
implement real time eye-tracking analysis, but there is still a lack of=20
integration in profiling systems and exploiting the data flow for =
personalised=20
content compilation.</P>
<P>To sum it up, let us state that according to our extensive literature =
survey=20
in the context of adaptive e-learning, (a) great research work has been =
done,=20
and (b) several prototype solutions, tools and systems already exist. =
However,=20
these are just isolated solutions, which cannot entirely satisfy the =
teachers'=20
and learners' needs in order to improve a personalised semantic =
knowledge=20
transfer. Thus, the <I>AdeLE framework</I>, which will be introduced in=20
following sections, covers new ideas by means of providing a <I>modular =
and=20
flexible architecture </I>for adaptive multimedia learning systems in =
order to=20
enhance the <I>adaptive semantic knowledge transfer process </I>as well =
as by=20
combining real time eye-tracking and content-tracking in order to =
enhance=20
<I>fine-grained user profiling</I>.</P>
<H2>4. Real-time Eye-tracking Information</H2>
<P>One of the main aims within the scope of the AdeLE project is to =
observe=20
users' learning activities in real-time by monitoring the major possible =
number=20
of behavioural aspects and personal traits. Learner profile information =
of=20
special interest for AdeLE are (a) <I>personal characteristics</I>, such =
as=20
cognitive or learning styles, (b) <I>momentary states</I>, like =
tiredness or=20
mental effort (see <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
arc=EDa-Barrios, V. M., G=FCtl, C., Pivec, M. (2004)">Garc=EDa-Barrios=20
et al. 2004</A>), as well as (c) <I>other indicators</I> during the =
learning=20
process, such as objects and areas of focus, time spent on objects, =
frequency of=20
visits, and sequences in which learning content is consumed (see <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#P=
reis, A. M., Mueller, H. (2003)">Preis=20
and Mueller 2003</A>). The advantage of interpreting these data in real =
time=20
lies in gaining prompt information about the user's state. By exploiting =

eye-tracking data combined with other user behavioural traits linked =
with the=20
content provided, a <I>fine-grained learner profile</I> can be tracked =
by the=20
system and applied e.g. for personalisation of learning content and =
navigation.=20
Furthermore, based on this fine-grained learner information, the target =
of AdeLE=20
is to gain an insight into the <I>learning strategies </I>that users =
apply when=20
using an e-learning platform and to be able to detect patterns =
indicative of=20
disorientation or other suboptimal learning strategies. At this point, =
it should=20
be also mentioned that in order to interpret efficiently behavioural =
indicators,=20
it is important to not rely exclusively on eye-tracking data, but to =
supplement=20
it with information gained by direct and constant <I>user feedback,</I> =
i.e.=20
learners must 'on screen' not only be informed of why/how adaptation =
happens but=20
also get free control of the adaptation procedures.</P>
<H3><B>Eye-Tracking Technology and E-learning</B></H3>
<P>In terms of eye-tracking technology, eye movements, scanning patterns =
and=20
pupil diameter are indicators of thought and mental processing involved =
during=20
visual information extraction (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#R=
ayner, K. (1998)">Rayner=20
1998</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#K=
ahneman, D. &amp; Beatty, J. (1966)">Kahneman=20
1966</A>). Thus, real-time information of the precise position of gaze =
and of=20
pupil diameter can be used for supporting and guiding learners through =
their=20
learning journey. Very roughly, eye movements can be divided into two=20
components: <I>fixations</I>, i.e. periods of time with relatively =
stable eye=20
movements where visual information is processed, and <I>saccades</I>, =
which are=20
defined as rapid eye movements that bring a new part of the visual scene =
into=20
focus. However, more important indicators can be gained by analysing =
both=20
components together with other derived parameters. Finding out reliable=20
parameters is one of the emerging aims of the AdeLE project. To =
emphasise the=20
complex situation in this research field consider the following problems =
and=20
prospects in context.</P>
<P><I>Gaze duration</I> (i.e. time spent on an object) and fixations are =
not=20
indicative of attention per se, because one can also pay attention to =
objects=20
that do not lie in the centre of the focused region. Nevertheless, by=20
considering other indicators, such as saccadic velocity, blink velocity =
and rate=20
as well as eyelid's degree of openness, a better and more meaningful=20
approximation can be gained. Saccadic velocity, for example, is said to =
decrease=20
with increasing tiredness and to increase with increasing task =
difficulty (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#F=
ritz, A., Galley, N., Groetzner, Ch. (1992)">Fritz=20
et al. 1992</A>). Further, blink rate, decreasing blink velocity and =
decreasing=20
degree of openness may be indicators for increasing tiredness (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
alley, N. (2001)">Galley=20
2001</A>). Thus, if tiredness is identified, it should be possible =
through=20
adaptive e-learning mechanisms to suggest optimised strategies such as =
the best=20
time to take a break. At this point it is reasonable to also emphasise =
that the=20
user should always retain the final say over whether to accept or reject =
the=20
system's suggestions (we call that <I>controlled adaptation </I>or=20
<I>non-intrusive adaptivity</I>).</P>
<H3><B>AdeLE's Eye-Tracking System</B></H3>
<P>At the present there basically exist two types of eye-tracking =
systems on the=20
market: outside-in systems and inside-out systems. Outside-in systems =
are=20
characterised by the fact that one or more cameras record the eye of the =

participant and trace the gaze in a scene through imaging algorithms. =
The=20
cameras are positioned in front of the participant. One of the =
advantages of=20
these systems is given by the fact that the camera can be integrated =
into the=20
monitor, and therefore remains basically invisible (i.e. a relatively=20
non-intrusive monitoring is possible). Inside-out systems are =
characterised by a=20
special device that the participant has to wear on the head. The image =
of the=20
eye is led into a mini-camera by using mirrors. This mini-camera records =
the eye=20
and the actual line of vision is found out through imaging algorithms. =
More=20
characteristics of both systems along with advantages and disadvantages =
related=20
to the requirements of the AdeLE project are outlined in detail in (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#P=
ivec, M., Preis, M. A.">Pivec=20
et. al 2004</A>). For further detailed information about general =
eye-tracker=20
characteristics refer to (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#J=
acob, R. J. K. (1995)">Jacob=20
1995</A>) and (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
alley, N. (2001)">Galley=20
2001</A>).</P>
<P>For the purposes of the AdeLE project outside-in systems seem to be =
more=20
suitable, hence they are less intrusive for the learner and support =
tracking of=20
the user by regular e-learning lessons. Based on the project objectives =
and the=20
requirements for the eye-tracking system, the AdeLE team decided to =
utilise=20
<I>Tobii 1750</I>. Figure 1 on the next page shows the utilisation of =
the=20
eye-tracker system within the AdeLE project, on the left side a user is =
being=20
monitored on real-time by the eye-tracker during a learning session and =
on the=20
right side the monitored results are examined. The Tobii 1750 is =
integrated into=20
a 17" TFT monitor and can therefore be used for many forms of =
eye-tracking=20
studies with stimuli like Web sites, slide shows, videos and text =
documents.=20
Further, the Tobii 1750 does not show any problems with its functional=20
re-acquisition from extreme head-motions. Another advantage is given by =
its high=20
tracking quality, i.e. it can be used by young or old people, by persons =
with=20
dark or bright eyes, by users with different ethnical-dependent anatomic =
eye=20
types, by people with glasses or contact lenses as well as under varying =

environmental light conditions. More technical advantages of the system =
can be=20
summarised as follows: a) high accuracy (0.5 degrees accuracy, bias =
error), b)=20
compensation of unparalleled quality of head-motion and drift reduction, =
and c)=20
binocular tracking with a frequency of 50 Hz. Further, the system =
provides a=20
well-designed programming interface with which its automatic =
functionality can=20
be configured, enabling no additional manual adjustments of parameters =
on the=20
device. This interface is utilised to integrate the eye-tracking system =
into the=20
AdeLE framework, as described in the next section.</P>
<P align=3Dcenter><IMG height=3D192=20
alt=3D"Utilisation of the Tobii 1750 Eye-Tracking system."=20
src=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl_files/=
image001.jpg"=20
width=3D288>&nbsp;&nbsp; <IMG height=3D192=20
alt=3D"Utilisation of the Tobii 1750 Eye-Tracking system."=20
src=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl_files/=
image002.jpg"=20
width=3D288></P>
<P align=3Dcenter><B>Figure 1.</B> Utilisation of the Tobii 1750 =
Eye-Tracking=20
system.</P>
<H2>5. Architectural Overview of AdeLE Framework</H2>
<P>This section gives an overview over the functional and logical =
architecture=20
of the AdeLE framework, as is illustrated in Figure 2 below. The main =
functional=20
components are mainly divided into the following three logical parts: =
Core=20
Module, User-centred Modules and Lecturer-centred Modules.</P>
<P align=3Dcenter><IMG height=3D457 alt=3D"The architecture of the AdeLE =
framework."=20
src=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl_files/=
image003.gif"=20
width=3D442 align=3Dcenter> </P>
<P align=3Dcenter><B>Figure 2.</B> The architecture of the AdeLE =
framework.</P>
<H3><B>Core Module</B></H3>
<P>The <I>Adaptive Semantic Knowledge Transfer Module </I>(ASKTM) =
represents the=20
core module of the framework. From a global point of view the ASKTM =
coordinates=20
all the surrounding modules and sends and requests information to and =
from them.=20
It compiles pieces of content and meta-information for delivery to the =
learners.=20
Separate interfaces are provided for the other two groups of users: =
course=20
creators (authors) and lecturers (teachers, trainers or tutors). For =
media and=20
platform-independence, the information is provided in an XML schema and =
can be=20
transformed into various formats. The process of content delivery is =
depicted in=20
the upper left and lower left parts of Figure 2.</P>
<H3><B>User-centred Modules</B></H3>
<P>The upper right part of Figure 2 shows the user-centred modules for =
advanced=20
user profiling. The core functionality for gaining enhanced and more =
precise=20
user information is located in the combination of the <I>Eye Tracking =
Module</I>=20
(ETM)and the<I> Content Tracking Module </I>(CTM). ETM in combination =
with CTM=20
provides real-time fine-grained data regarding the user's reading and =
learning=20
behaviour. The ETM also gives the system hints about concentration, =
excitement=20
or tiredness of the learner, and consequently, inferring criteria to =
monitor=20
efficacy aspects to the knowledge assimilation process. </P>
<P>The entire set of information of user interaction and behaviour is =
supplied=20
to the <I>User Information Module </I>(UIM), which is in charge of =
managing the=20
user modelling and profiling issues. In order to support user-controlled =

adaptation, the <I>Interactive Dialog Module</I> (IDM) allows learners =
to set=20
and change user profile settings actively. Further, the system also can=20
proactively force user interaction. For example, the latter module can =
be used=20
to verify and if necessary adjust any automatically inferred user =
information.=20
If tiredness is suspected, the IDM may also be used to suggest a short =
break or=20
provide a relaxation exercise to the user. We have chosen the term =
'user' at the=20
upper-side of the framework, because lecturers may also interact with =
the system=20
in order to achieve a direct tutoring intervention in the adaptation =
processes=20
of the e-learning environment. The implementation of this feature is =
intended to=20
allow overriding of automatically generated system decisions, e.g. to =
support=20
hybrid learning techniques.</P>
<P>The UIM encompasses three user information databases of different=20
granularity: the <I>User Profiling Database </I>(UPD), <I>Collaborative=20
Filtering Database </I>(CFD) and <I>Statistics Database </I>(SD). The =
UPD holds=20
fine-grained information about a wide range of user interactions (e.g. =
sequences=20
of scanned and viewed pieces of information) and more abstracted values =
of user=20
behaviour types (e.g. level of gained expertise in certain subtopics). =
Similar=20
user profiles or user behaviour types are grouped and managed in the CFD =
(i.e.=20
supporting stereotyped user-modelling). Through collaborative filtering, =
the=20
system can proactively suggest particular pieces of information in =
proper media=20
by exploiting the collective knowledge of user groups and their =
behaviour.=20
Finally, the SD manages abstracted information in auser-independent =
level.=20
Course creators and administrators may use valuable information (e.g. =
identified=20
problematic areas of courseware sections) without violating the privacy =
of=20
individual learners. The learning process will be improved, because the =
system=20
will create or deliver adapted content by means of tracked statistical =
data=20
(e.g. by delivering more images/tables for learners that have problems =
with=20
large and complicated texts).</P>
<H3><B>Lecturer-centred Modules</B></H3>
<P>The lower-right section of Figure 2 shows the lecturer-centred =
modules of the=20
AdeLE framework that are responsible for the course creation process. =
The=20
<I>Course Creation and Maintenance Module </I>(CCMM) represents the core =
module=20
for the entire course management and controls the <I>Courseware Module =
</I>(CM),=20
the <I>Course Topics Module </I>(CTM) and the <I>Background Knowledge =
Module=20
</I>(BKM). Course creators and lecturers can set up and maintain courses =
as well=20
as request statistics about their courses. The CM manages pieces of =
information=20
in different media types and an extensive set of metadata. This module =
(CM) can=20
either store pieces of information locally or just manage metadata and =
include=20
remotely located sources by caching them. </P>
<P>On the one hand, the CTM manages course content by just defining =
subsections=20
using meta-descriptors, i.e. course creators only predefine subtopics =
and their=20
relations at the time of course generation. During the learning process, =
users=20
get dynamically proper and most recent pieces of information out fromthe =
pool of=20
the CM. On the other hand, the CTM permits to manage a course topics =
structure=20
and a thesaurus for providing automatically relations between =
subsections. The=20
BKM dynamically provides additional information within the learning =
process and=20
helps course creators to keep pace with most recent information.</P>
<H3><B>Different Viewpoints on the AdeLE Framework</B></H3>
<P>From the <I>point of view of learners</I>, the AdeLE framework =
provides an=20
adaptive e-learning system with personalised views of the learning =
material,=20
i.e. the content is adapted in accordance to pre-knowledge and learning=20
progress, preferred media types, etc. Furthermore, real time =
eye-tracking can=20
help to identify areas of understanding difficulty and enable the =
provision of=20
selective additional information or explanation. A smart progress =
profiling=20
keeps pace with learners' system interaction and may assist them at =
further=20
learning sessions. In addition, learners can get a wide range of dynamic =

background information.</P>
<P>From the<I> point of view of lecturers</I>, the framework offers a =
wide range=20
of helpful and smart features for courseware generation and maintenance. =

Assuming that courseware modules follow a separation of form and =
content, or at=20
least follow a consistent style guide, it allows lecturers to create =
course ware=20
by simply defining meta-descriptions of subtopics and their relations. =
Course=20
authors can also create their own multimedia knowledge units applicable =
for=20
course delivery and share them. In the processes of creating new =
knowledge units=20
or updating information as well as defining background information for =
the=20
learners, the dynamic background library assists the course creators and =

lecturers. The concept of dynamic background libraries is well =
documented in (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
uetl, C. (2002)">Guetl=20
2002</A>) and a prototype implementation has been developed by (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
arc=EDa-Barrios, V. M. (2001)">Garc=EDa-Barrios=20
2001b</A>). Statistical information (e.g. identified courseware pieces =
with=20
understanding difficulties, subjects of most/weak interest) supports the =

maintenance of the courseware. </P>
<P>Based on the architectural overview of the AdeLE framework, a wide =
variety of=20
applications scenarios are facilitated. However, in the first stage of =
the AdeLE=20
project, research work is focused on the utilisation of real time =
eye-tracking=20
and content tracking information. In order to get a view on the =
practical=20
application of the AdeLE framework in this field of research, some =
application=20
scenarios are shown in the following section.</P>
<H2>6. Application Scenarios</H2>
<P>By merging eye-tracking technology with proper content presentation =
the goal=20
is to identify, evaluate and develop methods of adaptive instruction for =

personalised e-learning. Currently, the research efforts of the AdeLE =
team=20
concentrate on three application areas, which are discussed in the =
following=20
paragraphs.</P>
<H3><B>Individual Learning Strategies</B></H3>
<P>The first application scenario deals with the development of methods =
to=20
extract individual learning strategies from the learner's gaze behaviour =
and=20
adapt against the identified learning style. Comprehensive reviews of =
cognitive=20
psychology research indicate that people exhibit significant individual=20
differences in how they learn (<A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#S=
chmeck, R.R. (1988)">Schmeck=20
1988</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#G=
laser, R. (1984)">Glaser=20
1984</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#R=
obertson, I. T. (1985)">Robertson=20
1985</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#H=
oney, P. (1986)">Honey=20
1986</A>; <A=20
href=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl.htm#L=
eutner, D.; Plass, J.L. (1998)">Leutner=20
1998</A>). A simple example being individuals who have a strong visual =
memory=20
but weaker verbal processing will find text based material harder to =
process=20
than individuals who have stronger verbal skills. In the traditional =
classroom=20
environment a teacher has the chance to adapt or explain material to =
suit=20
individuals' needs. In e-learning environments where a teacher is =
frequently not=20
present, pedagogical material is nowadays more uniformly presented. In =
this=20
environment information about the learner's gaze behaviour would be a =
great=20
opportunity to optimise material to an individual's needs. For example, =
if=20
somebody prefers text and ignores pictures the amount of pictures =
presented=20
could be reduced, and vice versa. </P>
<H3><B>Additional Context Specific Information</B></H3>
<P>The second application scenario is defined by the use of the =
information=20
gained from the specific content accessed by the user (specific words,=20
paragraphs, areas of pictures, tables, and the like) in order to provide =

additional context specific information. For example, an animated =
picture could=20
accompany textual information, whereas the integration of the picture =
proceeds=20
in relation to the words or paragraphs accessed by the user (see Figure =
3 below=20
and Figure 4 on the next page). </P>
<P align=3Dcenter><IMG height=3D338=20
alt=3D"In an e-learning course concerned with Alexander the Great's =
Conquest of Persia, a map of Alexander's advance in the region is shown. =
The map content is updated in correspondence to the text paragraph =
currently read by the learner. In the example, the second paragraph =
(&quot;Granikos&quot;) is being read and the map shows the journey of =
Alexander from Macedonia to Granikos (green, yellow and red areas =
indicate fixations and gaze duration)."=20
src=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl_files/=
image004.jpg"=20
width=3D449></P>
<P align=3Dcenter><B>Figure 3.</B> In an e-learning course concerned =
with=20
Alexander the Great's Conquest of Persia, a map of Alexander's advance =
in the=20
region is shown. The map content is updated in correspondence to the =
text=20
paragraph currently read by the learner. In the example, the second =
paragraph=20
("Granikos") is being read and the map shows the journey of Alexander =
from=20
Macedonia to Granikos (green, yellow and red areas indicate fixations =
and gaze=20
duration).</P>
<P align=3Dcenter><IMG height=3D339=20
alt=3D'The reader has advanced to the fourth and fifth paragraph =
("Gaugamela") and is automatically shown the corresponding map =
containing the passage from Issos to Gaugamela.'=20
src=3D"http://www.eurodl.org/materials/contrib/2005/Christian_Gutl_files/=
image005.jpg"=20
width=3D453></P>
<P align=3Dcenter><B>Figure 4.</B> The reader has advanced to the fourth =
and fifth=20
paragraph ("Gaugamela") and is automatically shown the corresponding map =

containing the passage from Issos to Gaugamela.</P>
<P>The AdeLE research team also aims at the possible application of the =
system=20
in the field of high sensible knowledge transfer, such as training =
sessions in=20
nuclear power plants, in the field of aviation techniques or in =
military, where=20
it is essential that each section of a content unit has to be read by =
the=20
learner. By means of the real-time user behaviour, unseen sections of =
content=20
units provided to the learner are identified by the system and again =
will be=20
supplied to the user at the following content units. Of course, this =
method can=20
not reflect information about the knowledge acquisition and about =
pre-knowledge.=20
However, information about content sections skipped by the learner are =
utilised=20
to compile specific assessment tests to check the learner's knowledge =
about=20
these particular concepts.</P>
<H3><B>Appropriate Intervention Strategies</B></H3>
<P>The third interesting application area of the AdeLE research work is =
based on=20
developing and testing appropriate intervention strategies when the =
learner is=20
found to be stuck. The e-learning environment might intervene when a =
learner is=20
not focused on a relevant part of the computer screen, or is focused =
completely=20
outside the task area for a certain period of time, or the eye gaze is=20
sufficiently quick/jerky for a given period of time. Just to give one =
example,=20
in case of knowledge acquisition problems for a particular content =
section more=20
detailed content or background information can be provided to the =
learner.</P>
<H3><B>Other Application Areas</B></H3>
<P>Besides the above-depicted issues, innovative solutions as well as an =

improved and more profound understanding are expected in the following=20
areas:</P>
<UL>
  <LI>Improved knowledge of the users' behaviour in the field of=20
  <I>human-computer interaction</I> in general as well as related to the =

  displayed learning contents=20
  <LI>Improved and detailed course <I>progress tracking</I>=20
  <LI>Novel possibilities for identifying the most suitable <I>media and =
content=20
  presentation</I> within knowledge transfer environments=20
  <LI>Identification of <I>problematic areas</I> in the content flow =
and/or=20
  content structuring </LI></UL>
<H2>7. Conclusions and Future Work</H2>
<P>Evidently, the price of an advanced eye-tracking system plays a =
decisive role=20
in the application possibilities of the AdeLE solution approach. =
Nevertheless,=20
existing systems show that an eye-tracking device can be integrated into =
a=20
standard monitor. Due to the continuing trend of rapid technical =
progress, it=20
may be expected that in the next few years it would be possible to build =
a=20
low-cost but high-quality eye-tracking system based on standard hardware =

components, which would be suitable for real-time analysis of =
eye-tracking=20
information as described in this paper. Some results of the AdeLE =
project may=20
contribute to find new ways of making advanced adaptive environments for =

teaching and learning feasible and affordable for institutions in a =
relative=20
near future.</P>
<P>Potential target groups that could benefit from the presented ongoing =

research and proposed innovations based on eye-tracking supported =
real-time data=20
capturing and adaptation-based systems are identified as follows:</P>
<UL type=3Ddisc>
  <LI><I>Various end-users </I><BR>Support of 100% knowledge acquisition =
in=20
  application fields such as aviation, traffic, different complex =
procedures,=20
  risk management, decision support, research on learning, and others.=20
  <LI><I>E-learning platform and knowledge management platform =
developers=20
  </I><BR>Inclusion of these innovative approaches and provision of =
better=20
  adaptive/adaptable platforms=20
  <LI><I>Content publishers</I> <BR>Improvement of content structuring,=20
  development of user-centred contents and of contents supporting =
various=20
  learning stiles.=20
  <LI><I>Eye-tracking system producers</I> <BR>Development of low cost=20
  eye-tracking systems, which are possible to apply in a standard =
computer=20
  working place. </LI></UL>
<H2>Acknowledgements</H2>
<P>The AdeLE project is partially funded by the Austrian ministries =
BMVIT and=20
BMBWK, by the FHplus impulse programme. The support of the following=20
institutions and individuals is gratefully acknowledged: Department of=20
Information Design, Graz University of Applied Sciences (FH JOANNEUM); =
Institute=20
for Information Systems and Computer Media (IICM), Faculty of Computer =
Science=20
at Graz University of Technology; especially Hermann Maurer and Karl =
Stocker.=20
Further information about the AdeLE project can be found at <A=20
href=3D"http://adele.fh-joanneum.at/"=20
target=3D_blank>http://adele.fh-joanneum.at/</A>.</P>
<P><SUP><A name=3D1>1</A></SUP> Institute for Information Systems and =
Computer=20
Media (IICM), Faculty of Computer Science, Graz University of =
Technology,=20
Austria [<A href=3D"http://www.iicm.edu/"=20
target=3D_blank>http://www.iicm.edu/</A>]</P>
<P><SUP><A name=3D2>2</A></SUP> Department of Information Design, =
University of=20
Applied Sciences (FH JOANNEUM), Graz, Austria <BR>[<A=20
href=3D"http://www.fh-joanneum.at/"=20
target=3D_blank>http://www.fh-joanneum.at/</A>]</P>
<P><SUP><A name=3D3>3</A></SUP> Infodelio Information Systems [<A=20
href=3D"http://www.infodelio.com/" =
target=3D_blank>http://www.infodelio.com/</A>],=20
Guetl IT R&amp;C [<A href=3D"http://www.guetl.com/"=20
target=3D_blank>http://www.guetl.com/</A>] <BR>and Internet Studio-Isser =
[<A=20
href=3D"http://www.studio-isser.com/"=20
target=3D_blank>http://www.studio-isser.com/</A>]</P>
<P><SUP><A name=3D4>4</A></SUP> Institute for Information Technology =
(IZIT),=20
Maribor, Slovenia [<A href=3D"http://www.izit.si/"=20
target=3D_blank>http://www.izit.si/</A>]</P>
<P><SUP><A name=3D5>5</A></SUP> Degree Program in IT and IT-Marketing at =
Graz=20
University of Applied Sciences CAMPUS 02, Graz, Austria [<A=20
href=3D"http://www.campus02.at/" =
target=3D_blank>http://www.campus02.at/</A>]</P>
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