ABITS

2

Overview

This is a VRML plug-in that works in conjunction with Pocket Internet Explorer. It proves quite effective for displaying small files (up to 20kb);

however, larger files are very slow both to download and render. Consequently, we intend to reduce the amount of the VRML world that will be displayed on the mobile devices. Many different techniques are currently being explored to achieve this – techniques include culling algorithms such as view frustum culling, backface culling and occlusion culling (Martens 2003) and Levels of Detail (LOD; see Ames, Nadeau and Moreland 1996). These methods limit the amount of the VRML world that is rendered and also the number of animations that occur, and so improve the overall efficiency of the system.

ABITS is being developed to include an intelligent user interface (UI) which can adapt, based on a number of criteria including available bandwidth, device type, user preferences, etc. This

adaptation is achieved by exploiting technologies such as Extensible Markup Language (XML), Extensible Stylesheet Language Transformations (XSLT) and JavaServer Pages (JSPs) to separate content and deal with layout concerns. On mobile devices such as PDAs, restrictions are enforced so that ABITS makes available only the content and options that can be displayed and performed given resolution and

processing restrictions.

4

Results and further development

An initial implementation of CLEV–R has been developed for desktop computers. A VR university setting is provided and has been networked so that multiple users can connect to the system. A GUI has been designed, and users, represented by avatars, can browse presentation and notice boards. Initial feedback from a set of test users has proved encouraging.

An initial prototype of ABITS has also been developed and testing is due to commence in the near future. At present, the VR component of CLEV–R has been successfully tested on PDAs and further work is now being carried out to improve its display and performance. An interface for the ABITS system has also been developed for mobile devices.

References

Ames AL, Nadeau DR and Moreland JL (1996).

Vrml 2.0 sourcebook. New York: John Wiley and Sons.

Martens R (2003). Occlusion culling for the real-time display of complex 3D models.

Master’s thesis: Transnational Universiteit Limburg, Germany.

McArdle G, Monahan T, Bertolotto M and Mangina E (forthcoming). A web-based multimedia virtual reality environment for e-learning. In Proceedings of Eurographics ’04.

Short presentations and interactive demos section, Grenoble, France, August 2004, 9–13.

ParallelGraphics (2004). The Pocket Cortona. At www.parallelgraphics.com/products/cortonace/, accessed April 2004.

Roche B and Mangina E (2003). Agent-based framework for intelligent tutoring systems within University College Dublin. In Proceedings of the International Conference on Information

Communication Technologies in Education, Samos, Greece, July 2003.

3Name3D (1997). Animation created by Cindy Ballreich (c) 1997. At www.ballreich.net/vrml/

h-anim/nancy_h-anim.wrl, accessed April 2004.

VRML (1997). VRML 97 specification. At http://tecfa.unige.ch/guides/vrml/vrml97/spec/, accessed April 2004.

Monahan McArdle Kilbride Mangina Bertolotto 137

Abstract

The m-learning emergency system (mLES) is a model developed by ENEA (the Italian National Agency for New Technologies, Energy and the Environment) to support management of emergencies through m-learning. The model provides system-comprehensible

representations and user-navigable access.

The content needs to be developed using representations that separate content from format for flexible delivery, independent of the device used.

At the next level, we need to add to that content model an architecture that provides knowledge of the user and their context, as well as knowledge of the content available, to provide the right match. This requires a user

categorisation scheme and a mapping process to create an intelligent delivery environment. The mLES provides also for the training of a new type of professional – emergency operators who function as intermediaries between the people personally experiencing the high-risk or emergency situation and the m-learning-based technological system. The mLES can become an important asset for the community, with positive implications in the security and social domains, representing a valid tool for those who already work in emergency management in the different operational centres in the field.

Keywords

m-learning, emergency, scientific knowledge

A new model for the m-learning emergency scenario in risk contexts: the emergency operator

Anna Moreno Sergio Grande

[email protected] [email protected]

ENEA (Italian National Agency for New Technologies, Energy and the Environment) Via Anguillarese 301

00060 Rome Italy

1

Introduction

The coming of TIC (Training for Industry and Commerce) in the modern economy and the diffusion of the internet at a global level have brought about a revolution also in methods of training, introducing a new educational

philosophy – e-learning. The rising importance of e-learning was acknowledged also by the European Commission (EC) when it adopted in May 2000 its eLearning Action Plan, which launched an initiative aiming to redraw the way to deliver education in Europe, supporting training processes that use new multimedia technologies and the internet to improve learning quality.

The use of information and communication technologies (ICT) in education and training has undergone several paradigm shifts over the last three decades. The concepts of e-learning (learning supported by digital ‘electronic’ tools and media) and m-learning (e-learning using mobile devices and wireless transmission) have only emerged very recently. Handheld devices are emerging as one of the most promising technologies for supporting learning and particularly collaborative learning scenarios, mainly because they offer new opportunities for individuals who require mobile computer solutions that other devices cannot provide.

During the last few years, mobile technology has become integrated into day-to-day activities.

Handheld computers appear to be part of a general movement towards mobile technology.

The convergence of computing and

communication is a process that is about to turn phones and mobile terminals into powerful multimedia units. For example, Synchronised Multimedia Integration Language (SMIL), which is based on Extensible Markup Language (XML), has been devised for the distribution of

sophisticated multimedia content. These forms of interactive multimedia offer new possibilities for how we learn, think and communicate.

Moreno Grande 139

Mobile learning can be defined as ‘…any service or facility that supplies a learner with general electronic information and educational content that aids in acquisition of knowledge regardless of location and time…’ (Lehner and Nosekabel 2002). Technologically, we can now define mobile learning as e-learning’s new frontier, and

according to a study by Adkins (2003), by 2006, the m-learning market will be worth more than 5bn US dollars. The enormous potential of m-learning is ensured by the rising development of the wireless and mobile telephone market.

According to recent research on mobile

telephony by Intex Management Services (IMS), from sales of 288m mobile phones in 1999, we will reach sales of 1bn items in 2004. The growth of this market is predicted to reach 1.34bn mobile phones in 2006, when there will be 1.79bn users throughout the world.

2

The mlearning emergency system (mLES) project

ENEA, the Italian National Agency for New Technologies, Energy and the Environment (Ente per le Nuove Tecnologie, l’Energia e l’Ambiente), has been engaged for a long time in handling processes of knowledge transfer to enterprises and schools, as demonstrated by various

technological transfer initiatives realised at a local level, and by many collaborations with schools of all kinds. ENEA has always promoted the

diffusion and transfer of its own research results, supporting and favouring the technological innovation processes of small and medium enterprises (SMEs).

Precisely because of the importance, for a Learning Economy, of training in technological transfer processes, ENEA developed an

e-learning platform to make sure that knowledge and capabilities generated within the agency would be transferred through training to the highest possible number of individuals, and particularly to those working in SMEs.

ENEA’s e-learning platform was launched in 1996;

the project was devoted to the continuing education and retraining of workers. After this successful experience, the mission of the ENEA e-learning platform became the promotion of sustainable development through the diffusion of scientific culture and technological transfer to any person – not just workers, but also students and unemployed people. Now there are more than 12,000 users and 30 courses online, with the number of courses expected to double in 2004.

Some of the courses will be translated into other languages to allow other Mediterranean

countries to use the ENEA e-learning platform.

Many agreements with schools, universities and private and public training organisations are under way. The purpose of these agreements is to build up an open database of scientific learning objects that anyone can use.

The online training philosophy that ENEA adopted is dictated by the needs of the end users who, being strongly motivated to learn, are asking for an absolutely unrestricted training, in terms of time as well as methods. ENEA offers a system that can be considered as self-training for its own users, so that the learners will be free to learn what they want, when they want and where they want. From a pedagogic perspective, mobile learning supports a new dimension in the educational process. The ENEA educational process and philosophy are very close to the m-learning educational philosophy – that mobile learning systems should be capable of delivering education content at any time and anywhere the learners need it.

Emergency m-learning is one of the possible applications of m-learning, offering the possibility of exploiting the m-learning characteristics for learning processes in emergency cases.

An emergency is a situation that can produce risks, precisely because it is different from the events that are normally experienced by workers or the general public. The ENEA project’s idea is to create a technological system that ensures, through mobile learning, the management of emergency cases.

To execute this vision, we start with a content model that provides system-comprehensible representations and user-navigable access.

At the next level, we need to add to that content model an architecture that provides knowledge of the user and their context, as well as knowledge of the content available, to provide the right match. This requires a user

categorisation scheme and a mapping process to create an intelligent delivery environment.

Figure 1(opposite) depicts the architecture of ENEA’s mLES system.

140 Mobile learning anytime everywhere

Knowing how to manage emergencies means not only knowing the procedures and technical aspects needed to limit such risks, but also knowing how to be effective communicators and how to control the emotional situations that can surface. To be an effective communicator in emergency situations calls for attitudes and capabilities different from those needed in ordinary communication: authoritativeness, emotional strength, the capacity to adjust, etc.

The mLES, then, provides for the training of new professional figures – emergency operators who function as intermediaries between the people personally experiencing the emergency or high-risk situation and the m-learning-based technological system.

So, in the case of an emergency, the subject at risk contacts the emergency operator through a mobile device (mobile phone, palm computer, etc) and the emergency operator uses mLES to extrapolate the emergency learning object that represents the most appropriate solution, and then forwards it, via the mobile system, to the person at risk.

The emergency operator is a key figure, since as well as knowing how to interpret and to manage emergency calls, he or she must also be capable of managing the possible panic of the person at risk. To ensure that the system will be efficient, we must obviously have an articulate content repository containing all the examples of likely emergency events and the respective

emergency learning objects with which to respond to the various help and emergency calls.

Figure 1 Architecture of ENEA’s m-learning emergency system (mLES)

3

Conclusion

In Italy, the use of mobile phones to report an emergency has a yearly traffic of 33m calls. This data allows us to claim that an emergency m-learning system can become an important asset in Italian life, with positive effects in the security and social sectors. It represents a valid tool to support those who already work in emergency management in different local operation centres; for example, law enforcement agencies, public service agencies, local

emergency services, health centres, schools and civil protection organisations.

In 2004, ENEA designed and created an innovative platform called MATRIX 3, which includes videoconference functionality for online classes and seminars, using Active Server Pages (ASP), web-based and Real technologies.

Furthermore, the ENEA Usability Lab tested advanced visual interfaces to interrogate databases and to search on the Web in Java language. In this context, it was decided to proceed with Java-realised modules, and to pass later to a full Java platform for use on intranets as well as the internet. The outcome of this strategy was the implementation of mLES with its modules JNetseminar and JNetLesson, which aims to combine the functionality of web-based modules with other more innovative and complete functionalities.

Moreno Grande 141

Thanks to its experience in the e-learning sector and in research on advanced computer systems supporting training and video communication, ENEA is ready for this challenge in the mobile learning field, and is open to agreements and collaborations aimed at making an m-learning emergency system a well-established reality at the service of the local community.