Intelligent Learning Objects: An Agent Approach to Create Reusable Intelligent Learning Environments with Learning Objects

2006 ◽  
pp. 17-26 ◽  
Author(s):  
Ricardo Azambuja Silveira ◽  
Eduardo Rodrigues Gomes ◽  
Rosa Maria Viccari
Keyword(s):  
Learning Environments ◽  
Learning Objects ◽  
Intelligent Learning Environments

Building Intelligent Learning Environments Using Intelligent Learning Objects

2008 ◽  
pp. 19-42 ◽  
Author(s):  
Ricardo Azambuja Silveira ◽  
Júlia Marques Carvalho da Silva
Keyword(s):  
Learning Environments ◽  
Systems Approach ◽  
Real Life ◽  
Learning Objects ◽  
Learning Material ◽  
Agent Architectures ◽  
Agent Based ◽  
Design Learning ◽  
Object Learning ◽  
Intelligent Learning Environments

The reusability of learning material is a very important feature to design learning environments for real-life learning. The reusability of learning material is based on three main features: modularity, discoverability, and interoperability. The object learning approach aims to provide these features. At the same time, several researchers on intelligent learning environments have proposed the use of artificial intelligence through architectures based on agent societies. Teaching systems based on multiagent architectures make it possible to support the development of more interactive and adaptable systems. We proposed an approach where learning objects are built based on agent architectures: the intelligent learning object (ILO). This chapter addresses the improvement of interoperability among learning objects in agent-based learning environments by integrating learning objects technology and the multiagent systems approach. It presents the ILO agent’s basic architecture and a case study.

A New Semantic Description for Multimedia and Learning Objects

2020 ◽  
pp. 195-205
Author(s):  
Jihad Chaker ◽  
Mohamed Khaldi
Keyword(s):  
Learning Environments ◽  
Learning Objects ◽  
The Other ◽  
Multimedia Content ◽  
Semantic Description ◽  
Other Hand ◽  
E Learning ◽  
Application Profile ◽  
The One ◽  
Intelligent Learning Environments

This chapter explains a new description of multimedia and intelligent learning objects. The authors mention the benefits of integrating multimedia content into e-learning. Then they develop the intelligent learning environments on the one hand and the pedagogical objects on the other hand. Then, they fix the new elements of their application profile; the latter is crowned with a semantic description in the form of an ontology. Finally, they detail the generation components of multimedia and intelligent learning objects.

scholarly journals A New Metadata Scheme for Multimedia and Intelligent Learning Objects

2019 ◽  
Vol 9 (2) ◽  
pp. 3340-3345
Keyword(s):  
Learning Environments ◽  
Semantic Representation ◽  
Learning Objects ◽  
Semantic Description ◽  
Multimedia Documents ◽  
Multimedia Metadata ◽  
Metadata Analysis ◽  
Application Profile ◽  
The One ◽  
Intelligent Learning Environments

The purpose of this contribution is to improve the interoperability of educational and multimedia metadata in the context of a new application profile based on the LOM standard, without affecting their educational purpose. our metadata analysis led to the creation of new elements and new categories by strengthening the semantic representation of pedagogical objects and the different structures of multimedia documents, namely: spatial, temporal and hypermedia structures, this proposal also includes the characteristics of description visual. This contribution was essential given the absence of a metadata schema capturing multimedia and educational characteristics at the same time. the choice to gather descriptive elements based on the LOM standard, has proven to be wise since this standard is the most recognized and known in the field of eLearning. Throughout this article, we cite the advantages of pedagogical use of Multimedia, more specifically in eLearning. We then present intelligent learning environments on the one hand and educational objects on the other. Finally, we fix the new elements of our application profile, the latter is crowned with a semantic description in the form of an ontology.

scholarly journals The Model for Learning Objects Design Based on Semantic Technologies

2017 ◽  
Vol 12 (2) ◽  
pp. 227
Author(s):  
Daina Gudoniene ◽  
Rytis Maskeliunas ◽  
Danguole Rutkauskiene
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Learning Environments ◽  
Information And Communication Technologies ◽  
Learning Objects ◽  
Semantic Web Services ◽  
Innovative Learning ◽  
Modern Learning ◽  
E Learning ◽  
Integration Of Learning

The paper presents a comparison of state of the art methods and techniques on implementation of learning objects (LO) in the field of information and communication technologies (ICT) using semantic web services for e-learning. The web can serve as a perfect technological environment for individualized learning which is often based on interactive learning objects. This allows learners to be uniquely identified, content to be specifically personalized, and, as a result, a learner’s progress can be monitored, supported, and assessed. While a range of technological solutions for the development of integrated e-learning environments already exists, the most appropriate solutions require further improvement on implementation of novel learning objects, unification of standardization and integration of learning environments based on semantic web services (SWS) that are still in the early stages of development. This paper introduces a proprietary architectural model for distributed e-learning environments based on semantic web services (SWS), enabling the implementation of a successive learning process by developing innovative learning objects based on modern learning methods. A successful technical implementation of our approach in the environment of Kaunas University of Technology is further detailed and evaluated.

Content Adaptation in Mobile Learning Environments

2012 ◽  
pp. 240-255
Author(s):  
Sergio Castillo ◽  
Gerardo Ayala
Keyword(s):  
Learning Environments ◽  
Mobile Learning ◽  
Mobile Device ◽  
Belief System ◽  
Learning Objects ◽  
Content Adaptation ◽  
Programming System ◽  
Knowledge Use ◽  
User Adaptation ◽  
Content Model

In this paper, the authors present their proposal for adaptation of educational contents of learning objects to a particular mobile device and a specific learner. Content adaptation in mobile learning objects implies user adaptation and device adaptation, and requires additional metadata categories in comparison with SCORM 2004. This learning object content model, ALMA (A Learning content Model Adaptation), inherits from the SCORM standard a subset of metadata categories, and extends it with three top level metadata categories for content adaptation, i.e., Knowledge, Use, and Mobile Device Requirements (Castillo & Ayala, 2008). For user adaptation, the authors developed NORIKO (NOn-monotonic Reasoning for Intelligent Knowledge awareness and recommendations On the move), a belief system based on DLV, a programming system based on Answer Set Programming paradigm. For device adaptation the authors designed CARIME (Content Adapter of Resources In Mobile learning Environments), which uses transcoding and transrating to adapt media content to suit the device characteristics.

Sign in / Sign up

Export Citation Format

Share Document