Oscar M. Salazar

Adaptive and Personalized Educational Ubiquitous Multi-Agent System Using Context-Awareness Services and Mobile Devices

In the last decade, some useful contributions have occurred to e-learning system development such as adaptation, ubiquity, personalization, as well as context-awareness services. The aim of this paper is to present the advantages brought by the integration of ubiquitous computing along with distributed artificial intelligence techniques in order to build an adaptive and personalized context-aware learning system by using mobile devices. Based on this model we propose a multi-agent context-aware u-learning system that offers several functionalities such as context-aware learning planning, personalized course evaluation, selection of learning objects according to student profile, search of learning objects in repository federations, search of thematic learning assistants, and access of current context-aware collaborative learning activities involved. In addition, several context-awareness services are incorporated within the adaptive e-learning system that can be used from mobile devices. In order to validate the model a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of using this kind of approaches in virtual learning environments which constitutes an attempt to improve learning processes.

Modelo de Recomendación Personalizada en Cursos Virtuales basado en Computación Ubicua y Agentes Inteligentes

El objetivo de este articulo es proponer un modelo de recomendacion personalizada de recursos educativos para cursos virtuales adaptativos que incorpora las bondades de la computacion ubicua y de los agentes inteligentes. Dicho modelo busca proveer de informacion relevante y personalizada a los estudiantes sobre la planificacion de sus cursos virtuales, evaluacion en linea, busqueda y recuperacion de objetos de aprendizaje. La metodologia utilizada para la construccion del sistema es MAS-CommonKADS la cual ofrece modelos utiles para las fases de conceptualizacion, analisis y diseno expresados a traves de los artefactos que proporciona la extension del Lenguaje Unificado de Modelado para Agentes (AUML). El prototipo construido exhibe agentes inteligentes proactivos y deliberativos que permiten la busqueda y recomendacion de informacion adaptada al perfil del estudiante. Para validar el sistema se realizo una fase de pruebas con un escenario de aprendizaje, el cual evidencia la eficacia de utilizar este tipo de tecnologias en entornos virtuales y ubicuos de aprendizaje.

A Fuzzy-Based Multi-agent Model for Group Formation in Collaborative Learning Environments

Group formation is one of the key stages in a Computer Supported Collaborative Learning (CSCL) process since each organized group should be composed of adequate individuals that perform good interaction and contribute to the group’s goals. Team members use their capabilities and strengths always in order to achieve satisfactory learning results from efficient collaborative work. The aim of this paper is to propose a fuzzy-based Multi-Agent Model for group formation based on nine roles defined by Belbin typology using the strengths and ideal responsibilities for each team member role. To better balance different working groups based on existing roles we use a fuzzy logic approach that allows classifying the role performance of each individual into the group. In order to validate the proposed model a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of this approach to group formation stage for CSCL environments, which constitutes an attempt to improve learning processes.

A Proposal to Integrate Context-Awareness Services to Enhance CSCL Environments Based on Intelligent Agents

Computer Supported Collaborative Learning (CSCL) is a computational approach allowing students−being organized into groups− to work together for a common goal and discuss from different points of view always seeking to improve learning processes. The context-awareness concept, which is inherent to humans when performing any learning activity, becomes the main component for monitoring activities in virtual learning environments. The aim of this paper is to integrate context-awareness services to enhance CSCL environments supported by Multi-Agent Systems. The awareness-group-agent that composes the system architecture provides the coordination of several agents responsible of handling each of the 11 context-awareness services proposed. This characteristic allows both students and teachers at a given time be aware of their teamwork progress status during execution of the CSCL-MAS environment. In order to validate the incorporation of context-aware services a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of using this kind of approaches in collaborative learning environments which constitutes an attempt to improve learning processes.

A Case-Based Multi-Agent and Recommendation Environment to Improve the E-Recruitment Process

The current growth of information and communication technologies has promoted the development of tools in order to facilitate the process of e-recruitment; benefiting both recruiters as jobseekers. This paper presents a case-based Multi-Agent System which aims at integrating an ontology in order to select and to recommend adapted jobseekers to the recruiter job postings or vice versa. For this reason, the ontology considers the HR-XML standard for map-ping CVs in order to standardize the knowledge representation. The MAS was designed following the Prometheus Methodology and then a prototype has been implemented. A case study was performed within a testing phase in order to validate our work. As a result of this phase, we can prove the effectiveness of using this kind of technologies in the e-recruitment process.

Incorporating Context-Awareness Services in Adaptive U-MAS Learning Environments

The context-awareness concept, which is inherent to humans when performing any learning activity, becomes the main component for monitoring activities in virtual learning environments. The aim of this paper is to incorporate context-awareness services within an adaptive ubiquitous Multi-Agent System (U-MAS) learning environment intended for instructional planning and educational resource recommendation. The awareness agent developed that composes the system architecture provides the functionality that involves several context-awareness services. This characteristic allows both students and teachers at a given time be aware of their learning progress status during U-MAS execution. In order to validate the incorporation of context-aware services a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of using this kind of approaches in virtual learning environments which constitutes an attempt to improve learning processes.

Improving the Entrepreneur's Market Research Strategies Learning Process Using the MaREMAS Environment

The development of e-learning systems serving as instructors in the marketing research field for new entrepreneurs is an alternative that allows a better use of resources, a broader knowledge of the market, and a creative activity support in the discovery of new potential niche markets. Thus, the purpose of this paper is to improve the entrepreneur’s learning process of market research strategies by using the MAS learning environment so-called MaREMAS. The methodologies MAS-CommonKADS and GAIA are integrated with AUML diagrams for system designing. The paper further describes the tasks, architecture and communication model of MaREMAS. In addition, main steps that support entrepreneur’s market research learning process are detailed. To validate these aspects a case study in the motorcycle industry is shown. The paper finally concludes with a comparison performed between the learning processes achieved through MaREMAS environment and the traditional learning approach.

User-Centered Ubiquitous Multi-Agent Model for e-Health Web-Based Recommender Applications Development

Despite recent progress in e-health system development, there are still significant problems in health service recommendation processes such as searching for healthcare specialists or medical appointments in hospitals and healthcare centers. Also, there are not so many e-health user-centered systems that provide assistance and good recommendations to users at any time in the location they are situated. The aim of this paper is to propose a model based on the integration of several approaches such as: ubiquitous computing, adaptive and recommender systems, web-based and user-centered multi-agent systems, and ontologies. In addition, an e-health web-based system prototype was built based on this model adopting mechanisms to search for information from anywhere and anytime, thus providing ubiquity characteristics. Finally, we present the validation of the U-MAS-HEALTH system by means of a case study.

A Fuzzy-Based Multi-agent Model to Control the Micro-grid Operation Based on Energy Market Dynamics

The concept of distributed generation and renewable energy has increased the need for using Smartgrids which are electric micro-grids having intelligent characteristics that provide autonomy to the system not only to improve their operation but also to make it easier for users their management. The aim of this paper is to propose a fuzzy-based Multi-Agent Model to control a micro-grid by determining optimal operation states based on real-time process conditions and energy market dynamics. The Prometheus methodology is used for the MAS architecture design and development. The implementation of the system is carried out using Java, the JADE framework and the JFuzzyLogic library. Based on the proposed fuzzy MAS model, a prototype was implemented and validated through a case study. Results obtained demonstrate the effectiveness of this approach to automatically manage the states of a micro-grid when connected to external grid in a dynamic energy market environment. It is also possible to extend this application for different micro-grid applications involving other power generation, storage, and consumption capabilities.

EOLo: A Serious Mobile Game to Support Learning Processes

A great deal of interest is now being given to the use of serious games to improve specific issues of learning processes at different levels of education both in primary and secondary schools as well as in universities worldwide. The aim of this paper is to propose a serious game model supported by mobile computing for improving learning of specific topics regarding AVC (Adaptive Virtual Courses). The model incorporates three main modules: the web-based backend, the mobile application (game) and finally, the instructional design module in charge of the game content management. The implementation of the model was achieved through the development of EOLo, a functional prototype which was validated using a case study applied to a secondary school English course. The results show that students are motivated with the use of EOLo thanks to the healthy competition offered by the game during the development of learning activities. In addition, the system allows the detection of learning failures and from these generates a proactive feedback based on the recommendation of educational resources.