Discussion
Moreira, M. I. G. and Costa, A. Carlos da Rocha and Aguiar, M. S. de (2017) A legislation-oriented VLE-MAS system applied to MOODLE. In: 2017 16th International Conference on Information Technology Based Higher Education and Training (ITHET).
Full text not available from this repository.Abstract
The Virtual Learning Environments (VLE) are considered virtual sites that have a vast amount of resources that allow it to host courses that occur as Distance Education (EaD in Portuguese) or blended mode, favoring communication between the actors involved in these arrangements. Assign Artificial Intelligence to VLEs using Multi-Agent Systems (MAS) is a way to facilitate the learning process. By analyzing the state of the art of existing VLEs today, it can be seen that they all work as tools to aid students, but none works the management aspects of distance education supporting legislation. Therefore, this article presents a model and VLE-MAS integration system that can make the VLE able to assist managers of distance education in their tasks incorporating legislation representation. In addition, this system will work in an evolutionary way where the machine-learning method called the nearest neighbors algorithm will be applied to help the dead-time warning mechanism.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Uncontrolled Keywords: | Artificial Intelligence, blended mode, computer aided instruction, dead-time warning mechanism, distance education, distance education supporting legislation, distance learning, Education, Law, learning (artificial intelligence), learning process, legal systems, legislation, Legislation, legislation representation, machine-learning method, MOODLE, multi-agent systems, Multi-agent systems, multiagent systems, nearest neighbors algorithm, organizational models, Standards, virtual learning environments, Virtual Learning Environments, virtual sites, VLE-MAS integration system, VLE-MAS system |
| Depositing User: | Elizabeth Dalton |
| Date Deposited: | 16 Dec 2019 23:40 |
| Last Modified: | 16 Dec 2019 23:40 |
| URI: | http://research.moodle.org/id/eprint/385 |
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