Intelligent Support for Authoring Semantic Learning Content
Content authoring for adaptive educational systems is a tedious and expensive procedure. It requires from the author to have a high level of expertise in the subject domain, knowledge engineering and metadata standards. Over the l...
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TIN2009-14317-C03-03
ARQUITECTURAS AVANZADAS, GESTION DEL CONOCIMIENTO Y CALIDAD:...
83K€
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Descripción del proyecto
Content authoring for adaptive educational systems is a tedious and expensive procedure. It requires from the author to have a high level of expertise in the subject domain, knowledge engineering and metadata standards. Over the last decade considerable efforts have been put into improving authoring practices through the development of authoring tools and proposal of metadata standards. Yet, to a large degree, the existing collections of learning objects suffer from a number of problems. Lack of metadata limits the use of learning content in adaptive systems and impedes its discovery, sharing and reuse. Another set of problems results from the design of existing authoring tools. While providing sophisticated functionality they have limited support of the author herself. Intelligent authoring support will allow a wider population of authors to participate in semantic learning content creation. Most of the existing authoring tool are developed to be used by a single author. This paradigm disregards the success of collaborative authoring patterns introduced by Social Web applications. This project will address the problem of semantic learning content authoring from several perspectives and will employ a set of technologies to provide comprehensive and intelligent support of the authoring process. Implementation of each technology will be performed as a separate work package: * collaborative authoring support; * intelligent support of metadata creation; * open-corpus content discovery. The target domain of the project will be the domain of mathematics, which is a core subject in every EU country’s education program. However, both the set of problems and the proposed solutions are domain-independent. The obtained results are expected to be transferable to other domains. The evaluation of the developed technologies will be performed with the partners of ActiveMath group and will be based on the analysis of social feedback and a set of experiments.