Introduction to the special issue of ITSE on new learning support systems

Citation

Tazi, S. (2009), "Introduction to the special issue of ITSE on new learning support systems", Interactive Technology and Smart Education, Vol. 6 No. 1. https://doi.org/10.1108/itse.2009.36306aaa.001

Introduction to the special issue of ITSE on new learning support systems

Introduction to the special issue of ITSE on new learning support systems

Article Type: Guest editorial From: Interactive Technology and Smart Education, Volume 6, Issue 1.

The information society is burgeoning and new technology is shifting educational, learning and training paradigms. New platforms, software and concepts are blooming. What has learning become in this scientific and technological progression?

The International Conference on Human System Learning (ICHSL.6) held in Toulouse (May 2008), gathered researchers from different disciplines with regard to their approaches, methods and techniques for the application of advanced technologies to answer to this fundamental question.

This special issue, like the preceding one in the ITSE journal is a collection of selected extended papers from ICHSL.6. This final collection of papers focuses on new systems and models deployed in the learning process.

The first paper in the issue is by Francesco Colace et al. In this paper, the authors present a Bayesian model of ontology designed to be used in e-learning systems. The improvements related to the introduction of ontology formalism in the e-learning field are discussed and a novel algorithm for ontology building through the use of Bayesian networks is showed. Its application in the assessment process and some experimental results are illustrated.

Thanks to their characteristics, these networks can be used to model and evaluate the conditional dependencies among the nodes of the ontology on the basis of the data obtained from student tests. An experimental evaluation of the proposed method has been performed using real student data. The proposed method was integrated in a tool for the assessment of students during a learning process. This tool is based on the use of ontology and Bayesian network. In particular through the matching between ontology and Bayesian Network the developed tool allows an effective tutoring and a better adaptation of the learning process to the student's demands.

Pierre Loustau et al., in the second paper, aim at developing a toolset that end-users (particularly teachers) could use, first to retrieve travel stories from digital libraries, and then to study the itineraries reported in these travel stories. The challenging task that the authors address is to process these travel stories automatically in order to retrieve and to make explicit the geographical information that they contain. To this end, they propose two computational models from which is built a geographical information retrieval toolset in tune with travel stories characteristics. The paper demonstrates that these quite simple computational models are well fitted to process automatically (at discourse level) travel stories and to make explicit the geographical itineraries reported in such texts. Such geo-referenced itineraries can then be exploited by visual instructional design editors to encode interaction scenarios.

The third paper in this issue is by Bilel Elayeb et al. In this paper the authors propose a new qualitative approach for an intelligent possibilistic web information retrieval system. They define two models called Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). HSW consists in comparing the similarities between two independent queries that lead to the same class of two sets of pages, the authors. The goal of HSW model consists in considering a query as if it is multiple i.e. each query is considered based on its keywords with their synonyms. The PN generates the searched documents according to user's preferences.

The last paper by Véronique Baudin and Thierry Villemur relates two distant learning experiments using PLATINE in a student-centric pedagogical context. The first experiment was a mixed-reality experiment in fluid dynamics. It was conducted within the Lab@Future project. Students and teachers were remotely handling resources coming from the lab that was hosting the fluid experiment. The second experiment was realized during collaboration between LAAS-CNRS lab (France) and Tokushima University (Japan). The English course scenarios involved teachers and Japanese students. Feedbacks of teachers and students involved in the two experiments are described. These experiments have validated the technical choices of the platform and reinforced the underlying student-centric theoretical concepts.

Saïd TaziGuest Editor