LORNET

Portails et services de gestion des connaissances et d'apprentissage sur le Web sémantique

mardi 21 novembre 2017 ExtraLORNET  •   English
   
ITS’08 / LORNET actes de l’atelier du 23 juin 2008

 9H00 – 9H30

Registration / Accueil

 

 

9H30 – 10H30

Papers’ session #1

From a Conceptual Ontology to the TELOS Operational System
Gilbert Paquette and François Magnan (Télé-université)

In the last four years, within the LORNET research network, the LICEF team has been designing and developing TELOS, an innovative operation system for eLearning and knowledge management environments. This communication will present the main steps that have led to the actual system, as a contribution to the general software engineering methodology. We will first briefly present the background and initial requirements for TELOS. Then, we will summarize an ontology that captures the conceptual architecture of the system. Finally, we will present the transition of this conceptual ontology towards the technical ontology that actually drives the system. In conclusion, we will underline the main advantages of this method for building ontology-driven systems such as TELOS.

The LUISA framework for enabling semantic search of learning resources
Monique Grandbastien (UHP Nancy1), Benjamin Huynh Kim Bang (UHP Nancy1),
Tomas Pariente Lobo (AtosOrigin, Spain), Miguel-Angel Sicilia (universidad de Alcala, Spain)

The paper describes a global framework enabling semantic search of learning resources making a heavy use of semantic technologies. First it presents he generic components. Then it exemplifies how this framework can be adapted to a given environment, i.e. which knowledge representations, Web Services descriptions and other components have to be tailored or added to the framework. Then it shows step by step how a query is processed. Finally lessons learnt and future trends are provided as well as comparisons with other approaches already published about annotating and retrieving learning objects in Learning Objects Repositories.

 

 

10H30 – 10H45

Coffee break

   

10H45 – 11H45

Papers’ session # 2

MDTS: An organizational agent-based Tutoring
Davy Monticolo (University of Technology UTBM, France), Sebastien Chevriau (University of Technology UTBM), Samuel Gomes (University of Technology UTBM)

This paper presents MDTS an agent-based tutoring system using an organizational approach to guide students at the time of mechanical design projects. In these projects, students have to develop a new product, more effective than the product designed by their colleagues of the past year. To succeed this challenge they have to reuse knowledge created by the last project team. To help student we propose an intelligent tutoring system composed by three components: an organizational model which specifies knowledge created, shared and used by students, a knowledge model based on a domain ontology, and a multi agent system which assists students by monitoring their activities. The objective of our system is to capitalize knowledge through the professional activities and to assist student in reusing knowledge in their activities.

An Ontology-based Knowledge Modeling Tool for Automatically Composing Learning Knowledge Objects
Amal Zouaq (University of Montreal), Roger Nkambou, (UQAM)

This paper presents an ontology-based knowledge modeling tool for the dynamic generation of learning knowledge objects (LKO). The paper tackles the issue of using textual resources (documents, learning objects) to set up a whole knowledge base. This knowledge base is then used to produce LKOs, which have the particularity of implementing AIED techniques and which exhibit characteristics hitherto reserved for intelligent tutoring systems (ITS): they are knowledge-based, adapted to a learner model and they are composed dynamically according to a learning need and a particular instructional theory. Finally, the paper also demonstrates how LKOs are deployed.

 

11H45 – 12H15

Papers’ Discussion

   

12H15 – 13H15

Lunch (served on site)

   

13H15 – 14H15

Papers’ session #3

Ontological Support for Socially-enhanced Self Regulated Learning
Melody Siadaty (Simon Fraser University), Ty Mey Eap (Simon Fraser University), Carlo Torniai (Simon Fraser University), Dragan Gasevic (Athabasca University), Jelena Jovanovic (University of Belgrade)

The “anytime anywhere” nature of E-Learning environments requires their learners to be self regulated, i.e. to be able to plan, monitor and evaluate their own learning process. However, E-Learning systems lack some notable strength of face-to-face environments such as social communications between the learners. In this paper, we promote an extended ontology-based framework for context-aware learning environments, in which a socially enhanced self-regulated learning design, is the leading pedagogical approach governing different learning scenarios. Our proposed framework is built upon our previous ontological learning foundation, LOCO, where a learning context is comprised of different contextual factors, each modeled by the aims of related ontologies. The aim of our proposed framework is to help learners to be more productive through fostering both their individual and social competencies and expertise.

An Ontology-based Learning Design Assistant
Valery Psyche (TELUQ-UQAM), Jacqueline Bourdeau (TELUQ-UQAM), Roger Nkambou (UQAM)

Ontological Engineering (OE) can play a significant role in the authoring of Intelligent Tutoring Systems (ITS) by supporting instructional designers. This research attempts to illustrate how OE can overcome the lack of support experienced by designers. The following issue is addressed: “How can we assist designers in the complex task of designing semantically valid learning scenarios, when authoring systems fail to offer the required assistance and access to educational theories?” Our hypothesis is that the main cause for this limit in authoring systems stems from the lack of an explicit representation of the domains of learning and instructional theories and of learning design standards. To test this hypothesis, an ontology of such theories was created, and a Learning Design assistant was developed to offer complementary services to the designer, based on the ontology. Called CIAO (Construction Intelligently Assisted by Ontologies), this tool accesses ontologies to provide designers with a series of services. CIAO was used to assist the designer in an IMS-LD compliant authoring system. The results of a qualitative evaluation are presented and future work is outlined.

   

14H15 – 14H30

Coffee break

   

14H30 – 15H30

Papers’ session #4

Keywords and Concept Extraction for Metadata of Learning Objects
Suphakit Niwattanakul (University of LaRochelle, France), Michel Ebouyea (University of LaRochelle), Philippe Martin (Institut Eurécom, France)

In this paper, we present a method we implemented to help a user index documents (and, in particular, learning objects) according to a given set of concepts (terms referring to domains or topics). The user first associates keywords to the concepts. Our method uses such associations to suggest simple rules for indexing a document by concepts according to the keywords this document contain. Then, our system uses those rules to perform the indexation of documents.

Learning Object Metadata: from the locally prescribed to the socially derived
Scott Bateman (University of Saskatchewan), Christopher Brooks (University of Saskatchewan), Gordon McCalla (University of Saskatchewan), Jim Greer (University of Saskatchewan)

Since their inception, learning objects have been described using a number of different metaphors that attempt to best characterize their modular, reusable and reconfigurable nature. However, these metaphors all suffer from the same shortcomings, in that they overlook learning object content and the interactions of learners through the content. We argue that this social context information is the data that is needed to fulfill the original visions of learning objects as modular content that could be automatically discovered and aggregated. Using inspirations from the Web, we exemplify the missing aspects and concerns of social context for learning objects and repositories. We close by describing the latest work by our research group and by others with the goal of representing social context in learning object metadata, and enabling advanced functionalities in e-learning systems.

   

15H30 - 16H00

Papers’ discussion

   

16H00 – 17H00

LORNET meeting

 
   
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