An architecutre for the effective use of mobile devices in supporting contact learning

The features and capacities of mobile devices offer a wide range of significant opportunities for providing learning content in workplaces and educational institutions. This new approach of teaching, called mobile learning, allows for the delivery of learning content on the move at any time. Mobile learning supports learning by producing learning content to learners in a modern and acceptable way. The number of mobile learning applications has increased rapidly in educational environments. There are, however, limited mobile learning applications that take advantage of mobile devices to support contact learning in the classroom environment. The aim of this research was to design a mobile learning architecture to effectively support contact learning in the classroom. The researcher investigated the historical and theoretical background of mobile learning and reported these findings. This included an overview of existing mobile learning architectures. After identifying their limitations, the researcher designed the Contact Instruction Mobile Learning Architecture (CIMLA) to facilitate the use of mobile devices in the classroom. The researcher developed the LiveLearning prototype based on the proposed architecture as a proof of concept. He conducted a usability evaluation in order to determine the usability of LiveLearning. The results indicated that the LiveLearning prototype is effective in supporting contact learning in the classroom

An agent-based model for domain knowledge representation

International audienceThis paper focuses on the implementation of domain models for problem solving. We assume that the implementation shall preserve the form of domain models, especially the division between the knowledge structure and its role toward the solving process. We therefore propose to implement domain models with both knowledge bases and domain agents. We have defined a domain agent model which is linked to a knowledge base. We describe the abilities of this agent and how it has been implemented in a multi-agent system with the Yafool language. We give an example of the activity of the domain agent in a solving process

An agent-based model for domain knowledge representation

International audienceThis paper focuses on the implementation of domain models for problem solving. We assume that the implementation shall preserve the form of domain models, especially the division between the knowledge structure and its role toward the solving process. We therefore propose to implement domain models with both knowledge bases and domain agents. We have defined a domain agent model which is linked to a knowledge base. We describe the abilities of this agent and how it has been implemented in a multi-agent system with the Yafool language. We give an example of the activity of the domain agent in a solving process