SAXEF: A System for Automatic eXtraction of E-learning object Features

نویسندگان

  • Marco Alfano
  • Biagio Lenzitti
  • Natalia Visalli
چکیده

New online courses are often created by using existing materials on the net. However, those materials are usually proposed without information on their aims and the typology of users which they are destined to. Moreover, the contents are not clearly synthesized so that a complete analysis of the whole materials is often necessary to understand their relevance to the new course. Using our experience on the creation of online courses with existing web materials, we have thought how to help teachers in finding the best materials for the creation of new online courses. To this end, we have developed a system, called SAXEF (System for Automatic eXtraction of lEearning object Features), that is capable to automatically extract the didactic indicators (a sort of DNA) of any web page (or group of pages) found on internet and allows a teacher to easily evaluate whether that page (with its contents) is of interest to him/her. This paper presents the main architecture of SAXEF, its implementation details and some experiences on its use. At present, SAXEF is capable to automatically extract various didactic indicators such as main and secondary topics, synthesis level and multimedia level from any group of web pages.

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تاریخ انتشار 2008