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A General Architecture to Support Mobility in Learning
Anna Trifonova, Marco Ronchetti
Department of Informatics and Telecommunications, University of Trento,
38050 Povo (Trento), ITALY.
E-mail: {Anna.Trifonova, Marco.Ronchetti}@dit.unitn.it
Abstract
A rather new tendency in distance learning is the
usage of mobile and wireless technologies to support
learners and educators. In this paper we present an
architecture, where the functionalities of e-learning
platform are presented as web services and on top of it a
mobile Learning Management System is taking the
responsibilities of adapting those services for the mobile
users and for providing additional mobile specific
services. Such a system should have three main
functionalities – “Context Discovery”, “Mobile Content
Management and Adaptation” and “Packaging and
Synchronization”.
1. Introduction
Online courses, web-based education, computer
supported training and even virtual university are already
wide used terms. All of them represent e-learning which
is growing very fast both in educational end corporate
environment. The rapid development of wireless
infrastructure and the advent of mobile devices in
everyday life of people push the research to combine
those two domains, which results in the emerging of
mobile learning [6]. Considering the functionalities of e-
learning system in this paper we analyze the possibilities
to extend it to provide services for mobile devices. This
includes distribution of didactic material, user
identification and authorization, gathering of data relative
to the user-system interaction, provisioning of mobile
services etc. We find suitable an architecture that provides
interoperability between eLMS and mLMS (LMS stands
for Learning Management System).
In Section 2 we give a description of what e-learning is
and the services generally offered by e-learning platforms;
then we discuss the problems in the transition from e- to
m-learning (3). Section 4 is dedicated to the proposed
architecture. Related work (5), conclusion (6) and
references follow.
2. E-learning
E-learning has two main facets: the first is relative to
using technology to support distance learning, the second
is concerned with enhancing the learning experience with
the help of information technology. In the first case the
learners and the instructors can be physically separated
(they never or rarely meet for face-to-face lectures,
discussions, etc.) and thus all the learning process is
technology-mediated. In the second scenario the
traditional learning approaches can be supported with
complementary services, like online delivery of the
learning materials, support for collaborative work, virtual
communities etc. In many cases both aspects are
simultaneously present. The goals of e-learning systems
and the functionalities they offer can differ: the needs and
goals of know-how transfer in an industrial company are
quite different from the educational needs of a university.
The functionalities can be broadly grouped in four
categories: access to resources (data), specific e-learning
services, common services and presentation. We intend to
first list the main services and then discuss how these
services must be modified with the introduction of small
ubiquitous devices.
a) Resources
- Support of learning objects (LO) – any digital
material, link to other resources, active element (like
simulations etc.). Breaking the educational content into
small pieces allows modularity and reusability of the
content. These chunks of digital resources can be
rearranged in modules, like lectures and courses. To
facilitate this process they are usually described by
additional metadata (as prescribed by the LOM standard).
- Support for Learning Metadata – Repositories
for metadata can help to catalog learning objects, and
facilitate search and reuse.
Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT’04)
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- Quizzes and questions: lecturers can create a
pool of questions and answers to be used both for
automatic formal examination (summative assessment) or
self-assessment of the students.
b) E-learning specific services
- Content management services – In general any e-
learning system has the notion of Course and Lecture. A
course can be composed by collection of resources:
syllabus, one or many lectures, a structure for describing
lecture sequence, forum, board, etc. A lecture is usually
composed by many resources: presentation, exercise,
additional material. All these components should be
organized and accessed through a proper engine. There
could be searchable directories of courses, programs, etc.
- Assessment - one of the main advantages of
computer-supported learning is the automation of some
important processes. The self-assessment is one example.
The pool of questions/answers and a suitable engine allow
automatic generation of different versions of tests and
quizzes and also automatic checking of the results,
evaluation of performance and comparison with others’
results.
- Knowledge management (KM) – today most e-
learning systems do not really support knowledge
management services. KM in general aims at extraction,
summarization and organization of explicit or tacit
knowledge from data sources (e.g. Web, e-mails, chats,
etc.). Application of KM to e-learning can be of vital
importance in companies, while in university context
(where most of the knowledge to be acquired by the
students is explicit and formalized) it can be a useful but
less relevant addition.
- Tools to support learners and tutors in managing
their learning resources - some systems allow different
users to have their own workspace and to upload personal
resources (links, documents, notes, etc.), or to markup
learning material.
c) Common services
- Support of different actors (students, teachers,
tutors, administrator and guests), and integration with the
company (university) information system. Different users
typically have different levels of permissions.
Unregistered users (guests) can have some (typically very
limited) level of access to the platform.
- Collaboration tools: synchronous (chat rooms,
shared applications, whiteboards, web-cast, audio- or
video-conference, role games, simulations) and
asynchronous (FAQ, forums, wikis, blogs, message/news
boards, e-mail, mailing lists). Usually few different
services are offered for communication between users of
the system (learners, lecturers, tutors, mentors). Some of
these tools are mainly meant to support cooperative work,
while others aim at sharing and accessing important or
topical information.
3. M-learning
In the general case mobile learning can be viewed as
any form of teaching or studying that happens when the
user is interacting through a mobile device. Nevertheless
here we try to transfer the services provided by an e-
learning platform (enumerated previously) into the mobile
context. We can easily see that there are services that need
to be adapted to fulfill the limitations of certain devices,
there are other services that are infeasible to transfer, but
also new services appear, provoked by the mobility.
The connectivity is one of the main differences if we
compare a mobile device with the PC (the usual medium
for delivering e-learning). Nowadays mobile devices
might be connected to ‘The Net’ via many technologies –
WAP, GPRS, UMTS, Bluetooth, WiFi, etc. Although it is
predictable that in the future the ‘always on’ will be wide
spread still it is not the case. Mobile devices often have
periods of disconnection, either intentionally (when the
connection is too expensive) or not (when no
infrastructure is provided).
Devices’ hardware and software characteristics have a
big impact on what content is possible and meaningful to
be delivered. Usually the web content is designed for
desktop PCs, thus unpleasant and even rarely useful from
a small-screened device. Nowadays mobile phones
became more powerful with amazing speed (both from
hardware and software point of view) however their
screens will remain comparatively small. Often also the
navigation is hard. Equipped with a small phone-style
keyboard or a touch-screen (for the PDAs) the users
might loose more time in searching where on the page the
information they need is than in reading it. We can
imagine alternative ways of navigation, for example voice
commands. The memory available on a mobile device is
also relatively small. It is possible to use extension packs
on some devices like PDAs, which reduces some of the
restrictions.
Location is a new thing to be considered. Although up
to now we are talking only about limitations, confronting
m-learning and e-learning there are also advantages. The
small size of the device and the wireless connections
make them available anytime and anywhere. The mobility
opens variety of new scenarios. Services involving
location-discovery are for example receiving directions
how to get to a certain room or alerts for seminars/lectures
that can be triggered while taking into consideration the
current place and the time to get to the needed destination,
location-aware printing of the learning content, etc.
4. The Architecture
Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT’04)
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In Section 2 we presented the functionalities offered
generally by Learning Information Systems (LIS). The
services approach (exposing web service interface to
access these functionalities) allows flexibility,
interoperability and possibility for extension. In this
section we are presenting an architecture that will provide
access to learning materials and other services to users
equipped with mobile devices. Our goal is to have an
architecture which is:
a) General – to be able to provide all possible services
offered to the e-learning users from the corresponding
eLMS, but also to support services that are new in the
mobile context.
b) Generic – to support different mobile devices
(digital pones, smart phones, PDAs, tablet PCs and etc.)
with different characteristics and be easily extensible for
the new generation devices.
To achieve this goal we believe that a “mobile adapter”
should sit on top of the traditional e-learning system and
provide adaptation of the existing e-services, like user
identification, authorization, distribution of didactic
material, gathering of data related to user-system
interaction etc. In addition it should take care of mobile
specific service.
eLMS
Web Services Interface
mLM S
M obile D evic e
Packaging and Sy nchronization
- Web browser
-Wap browser
- Application
Presentation Layer
Business Logic Lay er
Content Managem ent
User Tracking
Stora ge
(DB)
Lay er
User Profiles
(preferences)
Sem antic
Indexing
Context Discovery
Mobile Content Managem ent
and P resentation Adaptation
...
Tracking
Data
Mata-
Data
LO
Figure 1: General M-Learning Architecture
The mobile adapter (in the following m-LMS) is a
broker: on one side it has the mobile device, request
access to it from a web browser, WAP browser or specific
application.
On the other side we have the eLMS which exposes an
interface to the services it provides. Only some possible
services are shown on Figure 1. In the business logic layer
these services might not be so clearly separated.
We identify three main modules in an m-LMS. They
are:
• Discovery of context
• Content management and specific adaptations
• Support for disconnected operation
Let’s see the interaction between different modules by
giving a simple example. We can imagine a scenario in
which a user requests an interaction with learning system
from her PDA. The system shows to the user the services
which it can provide and the user selects to requests more
data about a seminar. The system provides to the user the
information about the subject, speaker and location of the
seminar, and if the user is interested also creates a
reminder, which is triggered by the system depending on
what time the user needs to get to the seminar room. Later
the systems gives to the user direction how to get to the
room and during the seminar lets the user watch the
slideshow of the presentation also on the PDA display.
First the user request is captured and in order to
proceed the system need to know who is the user and
what is the device used. This is done automatically by the
“Context Discovery” module, which (based on the first
request or additional interaction) already hold the
information about the user and the capabilities and
limitations of the device (both software and hardware).
Based on this data the system checks the user role
(student, teacher, guest, etc.) and access rights in the
eLMS, decides what services can be offered at this time
and proposes a list to the user. After the next interaction
with the user the m-learning system requests information
about the seminar from the eLMS and triggers the
“Mobile Content Management and Presentation
Adaptation” module. Knowing the capabilities of the
device (from the “Context Discovery” module) the data is
redesigned and returned to the user. Afterwards the user
requests the reminder to be set up for her. The system
needs additional context information, namely the user
location, in order to calculate the needed time to get to the
seminar room. Once again the “Context Discovery”
module is triggered to track the user current position.
Meanwhile, as the system ‘knows’ that the network is not
accessible in the seminar room, it triggers the “Packaging
and Synchronization” module. The eLMS might contain
big amount of materials concerning the seminar – the
presentation itself, including explanations from the
lecturer; related links; additional papers and examples;
etc. As the system already knows the limitations of the
device the “Packaging” module selects (with certain
confidence) what part will be more useful and important
during the seminar (for example only the presentation). In
order to fit the device memory the system also ‘asks’ the
“Presentation Adaptation” module to resize the images
used. In the end the presentation is seamlessly uploaded to
the user’s PDA and is accessible when needed.
4.1. “Context Discovery”
This module adds an abstraction that can hide the
details about the different physical methods of context
Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT’04)
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discovery. By context we mean identity, temporal
information, spatial information (i.e. physical location),
environmental information (i.e. noise level), availability
of resources (i.e. battery, display, network, and
bandwidth), and etc. For example for finding location
different positioning systems can be used – outdoors a
GPS system can be used while e inside a building the
strength of WiFi signal from more antennas will be used.
A possible solution is the introduction of a semantic
server, which translates data from the format used by the
device (GPS, WLAN, etc.) into a proper format for the
service that requests the context information. It is not
necessary that the system detects all possible context data
at the first user request for service. Some context data
might be detected and provided when needed (on
demand).
4.2. “Mobile Content Management and
Presentation Adaptations”
An important service provided by e-learning systems is
content delivery. The presentation of learning materials is
an important issue and should be carefully designed. If,
for example, the content will be accessed through a
standard web-browser on the PDA then it should not
contain incompatible elements, like scripts. Adapting e-
learning material for a mobile scenario might imply
something more than a simple reshaping of material or
translating from one presentation language into another. It
should be more precise and could involve different
presentation logic than in e-learning - “Mobile Content
Management”. The presentation adaptation can include
adaptation of the structure, of the media format, quality or
even type, etc. This module should be also used to adapt
the presentation for auxiliary services, not only
presentation of content.
4.3. “Packaging and Synchronization”
For allowing offline usage we require a mechanism for
selecting what the user needs and also for taking care of
content’s coherence and synchronization with the system.
During offline usage user activities should be tracked and
the gathered data should be fed back to the LMS when the
connection is re-established. This module should be able
to predict which ‘learning path’ the user is most likely to
follow and assign weights to the learning objects
depending on how important they are for the next user
session. The objects with higher weights should be
uploaded to the device first; afterwards the materials with
smaller weights should be uploaded until the device’s
available cache is filled. The module should be able to
analyze how successfully the previous uploads were done
and improve further prediction.
5. Related Work
A work closely related to ours is [2]. The authors
discuss the possible m-learning scenarios in respect of e-
learning platforms and the functionalities an m-learning
platform is best suitable for. Also the characteristics of the
mobile devices are discussed and their impact on
foreseeable learning scenarios. What differs drastically in
this work is that the mobile platform functionalities are
direct mapping of the functionalities of an e-learning
platform and only those that are impossible to deliver are
excluded. In our opinion is also important to foresee the
support of new services that are proper only in the mobile
case, like location-dependent services.
In [4] context awareness architecture for mobile
learning is presented. Similar to our “Context Discovery”
module their “Context Engine” is responsible for
gathering the context data. A very good description of
context is given in a hierarchical structure with the notion
of context states and substates, dynamics and historic
dependencies of processes. The main difference from our
“Context Discovery” is that authors suppose that all the
context information is collected on the mobile device
(including data obtained from sensors). In our vision
some context data can be extracted directly from the
infrastructure (i.e. location) and does not require adding
additional load on the device. Also in our opinion we
should support the presumption that the context data
might be needed in different formats by diverse
applications and services, thus there should be a way to
‘translate’ it properly. Still this work proves the viability
also of our ideas. The authors also see the web services as
a most appropriate way for integrating their context-aware
(sub)system with a mobile learning system.
In [5] architecture for m-learning based on web
services is discussed. The analyses here show that this
technology is proper for supporting mobile equipped
users in learning scenarios. The authors find one of the
biggest challenges in the ability of such system to convert
in satisfactory time the data (LO) from one format into
another. They find the solution in preliminary (before
request) creation of different versions. A major miss that
we find in this work is that the only way the system would
support the offline usage of material is on manual request
of the user (“students could easily access and download
the entire course content anytime anywhere on their
mobile device”).
A lot of work has been done in the area of content
adaptation for mobile devices and of device independent
representation of web content. In this context different
Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT’04)
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approaches are proposed for describing device
capabilities; different architectural approaches are
developed for using this information for adapting the
content accordingly. A comprehensive review of the
current device-independence technologies and activities
can be found in [1] and http://www.w3.org/2001/di/.
Transcoding servers or proxies are often used for
adaptation of content (see e.g. [3]), which is retrieved by
the server together with the client preferences and
constraints. A negotiation is then done between the client
and the server about the needed adaptations. Finally the
converted content is delivered. Different transcoding
techniques can be used for translating from one
presentation language to another (e.g. WAP-HTML-
WAP), for reducing the contents size, for satisfying
bandwidth or screen capabilities, for adapting the
structure of the content etc. What is missing here is that
generally only online access to the content is considered.
Only some of the transcoding proxies take care also for
caching web pages for offline usage (e.g. AvantGo).
Another point to consider is that in the learning scenario
the content that is to be delivered could be sometimes
quite large. We think that delivering content for offline
usage is an important issue as still mobile devices are
often disconnected because of the lack of access in certain
places but also because of the high prices, thus our
intention is to support both online and offline access to
data.
The off-line access to data is treated in the offline
browsing of web content. The typical pre-fetching
solutions offered by offline browser utilities cannot be
cast to the mobile domain without taking into account the
(severe) memory limitations of such devices.
6. Conclusion
This paper presents a general architecture to support
mobility in the learning scenario. We discussed the
services provided by eLMS, how they have to be changed
(adapted) for accessing them through mobile devices and
what additional services should be supported. We identify
three main functionalities for a mLMS, which sits on top
of the usual eLMS - “Context Discovery”, “Mobile
Content Management and Adaptation” and “Packaging
and Synchronization”. Interaction between these modules
will allow the automatic selection of services, properly
constructed for devices’ capabilities, user preferences and
needs and will permit the usage both online and offline.
7. Acknowledgement
We thank Prof. Fausto Giunchiglia for pushing us in
the e-learning field and especially for encouraging and
supporting our efforts for the current work.
8. References
[1] Butler M. H., “Current Technologies for Device
Independence”, HP Labs Tech. Report HPL-2001-83.
[2] Kurbel K., Hilker J., ” Requirements for a mobile e-
Learning Platform”, IASTED 2002 Int. Conference on
Communications Internet and Information Technology, US
Virgin Islands
[3] Lemlouma T., Layaida N., “Adapted content delivery for
different contexts”, Proceedings of Symposium on Applications
and the Internet 2003.
[4] Lonsdale P., Baber C., Sharples MArvanitis. T. N., “A
context awareness architecture for facilitating mobile learning”,
MLEARN 2003, London, UK, May 19-20, 2003.
[5] Sharma S. K., Kitchens F. L., “Web Services Architecture
for M-Learning”, Electronic Journal on e-Learning, Volume 2,
Issue 1, February 2004, pp. 203-216.
[6] Trifonova A., Ronchetti M., “Where is mobile learning
going?”, Proceedings of the E-Learn 2003 Conference, Phoenix,
USA
Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT’04)
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