Generic Model of a Multi-Agent System to Assist Ubiquitous Learning

Generic Model of a Multi-Agent System to Assist Ubiquitous Learning

Elena B. Durán (Departamento de Informática, Facultad de Ciencias Exactas y Tecnologías, Universidad Nacional de Santiago del Estero, Argentina), Margarita M. Álvarez (Departamento de Informática, Facultad de Ciencias Exactas y Tecnologías, Universidad Nacional de Santiago del Estero, Argentina) and Silvina I. Únzaga (Departamento de Informática, Facultad de Ciencias Exactas y Tecnologías, Universidad Nacional de Santiago del Estero, Argentina)
DOI: 10.4018/978-1-4666-4490-8.ch049
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Abstract

Ubiquitous learning (u-learning) is a new educational paradigm that takes place in a ubiquitous computing environment and allows proper content for learning at convenient place and time, thus matching the student features and needs. The development of u-learning applications requires considering the user characteristics and necessities and the complex set with multiple ways of mobility, diverse mobile technology, diversity of carriers, and also the diversity of learning situations that might happen. The agent technology and the Semantic Web with ontologies offer efficient tools to manage this problem. On the other hand, the complexity inherent in this kind of application requires adequate strategies to manage the multiple components and interrelations. In this chapter, a model-based development approach is proposed to obtain a generic model of the system, and the architecture of it as a set of software agents.
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Introduction

Nowadays the huge development in wireless communication technology has made an impressive progress, introducing the creation of a new field in computer science, namely, ubiquitous or pervasive computing. This new area in computer science tries to add to the everyday objects such things as the capacity of computing, wireless communication, and the interaction between both, creating a new model of the reality where these objects operate, in order to facilitate the tasks for people. The main purpose of ubiquitous computing is to identify the user, find out the location, deduce intentions and necessities and act according to them. Ubiquitous computing tries to dramatically change the present paradigm for human-computer interaction, offering an aid to anyone who is the focus of the attention.

Particularly, in the field of education, ubiquitous computing has fostered the rise of a new way of learning: the ubiquitous learning (u-learning), which encloses a set of educational activities, supported by technology, that is available anywhere and at anytime, from a great variety of devices. In a ubiquitous learning environment students learn with a PDA (Personal Digital Assistant), a WebP, a Tablet or a PC, indoors or outdoors, individually or in groups. The main characteristics of computer assisted ubiquitous learning are: persistence, accessibility, immediacy, interaction and situated learning activities (Chen, Kao, Sheu, & Chiang, 2004; Curtis, Luchini, Bobrowsky, Quintana, & Soloway, 2002). This set of characteristics explains why the generation of systems developed to assist the ubiquitous learning is a complicated task.

To tackle this problem, Semantic Web, software agent technology and personalization techniques show up as valid alternatives to enhance the development of the ubiquitous assisted learning systems.

The semantic Web or Web 3.0 is the new generation Web that makes it possible to express the information in an accurate way, understandable by the computer, to share and reuse information, and to understand which terms describe the meaning of data. One of the key components of the semantic Web is ontologies, which are an exhaustive and precise conceptual schema, within one or several given domains. They are built to enhance communication and for information exchange between different systems and entities, thus solving persistence and accessibility problems for the systems, which support ubiquitous learning

Agents use the needed technologies to extract information from the Web, to assist the search for information based on metadata, to interpret the retrieved information obtained by the ontology, and to process information (Antoniou & Harmelen, 2004).

Personalization, in particular, is considered to be a powerful methodology to improve the efficiency in the search for information and decision making. It enables us to design systems able to suggest relevant and personalized information for users, according to their characteristics and preferences, based on a User Model. Therefore, the application of personalization techniques offers the student situated learning activities, that is to say, adjusted to the context in which they operate.

The architecture of a Web system is introduced in this paper, consisting of a set of software agents responsible for the maintenance of the required ontologies to personalize the various services of the ubiquitous learning environment.

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