Abstract:

With the use of mobile technologies and Web 2.0 services, tutoring system must cope with new needs and respond to new challenges. So the tutor is required to monitor educative spaces for discussion, analyze the interaction between learners in order to evaluate the degree of understanding and the types of problems encountered. Subsequently, he was invited to share its findings with the author. Initially, the tutor must take into account the dynamic context of the learner who can continually change its learning context and device access and production content. Secondly, the tutor must be able to evaluate the learners' navigation path and content that are rich and varied existing on various spaces for discussion.

USAGE OF WEB CONTENT MINING TO IMPROVE D-LEARNING QUALITY
Content exchanged between groups of learners and between them and their tutor are increasingly voluminous, especially with the integration of Web 2.0 technologies which allowed learners to become, more than ever before, content producers.
This rich and varied content are no longer mastered by the classical tutoring tools. We need tools able to take charge the content volume, their disparities and their richness. Also, they should take into account the learners' navigation tracks to exploit these data and allow authors and tutors to improve the learning process.
Can we use Web mining in order to analyze, handle the increasingly volumes of pedagogical content?
Content Mining: Mining for information focuses on the development of techniques for assisting a user in finding documents that meet a certain criterion. Web content mining refers to the discovery of useful information from web contents, including text, image, audio, video, etc. Mining the link structure aims at developing techniques to take advantage of the collective judgment of web page quality which is available in the form of hyperlinks that is web structure mining.
This is an extremely important component in the era of the explosion of web content. The tutor must guide learners during the completion of learning activities through the integration of this component he will be able to facilitate the task of the learners in the choice of educational resources available on the web.
Web usage mining refers discovery of user access patterns from Web servers. Web usages data include data from web server access logs, proxy server logs, browser logs, user profiles, registration data, user session or transactions, cookies, user queries, bookmark data, mouse clicks and scrolls or any other data as result of interaction.
This component will be of great utility to ensure traceability of learners learning pathway. It also helps to identify the contribution of each learner in the group. In addition, it can be used to improve the learning process through the proposal to learners more appropriate navigation paths. New specifications and criteria can be added to improve the learner profile.
The purpose of tutoring 2.0 system using web mining tools is to make tutors functions easier in terms of learners profiles management, creation of homogeneous groups and assessment of learners' contributions.
Such system of tutoring can actively contribute in the d-learning process. It will improve the learning content and eventually the content structure and sequencing of the graph of educational content.

Keywords:

d-learning, tutoring 2.0, web content mining, ciollaboration 2.0.