Automated Course Composition based on Semantic Knowledge

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The document discusses improving current e-learning systems by automating course composition based on semantic knowledge. It proposes creating user profiles and selecting personalized learning objects (LOs) that account for dependencies between LOs to dynamically compose courses tailored for each individual user. This would improve upon pre-defined, generic courses by cross-referencing information between courses. The document also outlines basic workflow patterns like sequence, parallel split, and synchronization that could be used for composing courses, and identifies defining goals and improving composition algorithms as areas for future work.

Automated Course Composition based on Semantic Knowledge Filip Maciej Czaja Filip Maciej Czaja [email_address] SemInf, 14.03.2007

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Ontologies and semantic web services are the basics of next generation semantic web. This upcoming technologies are useful in many fields such as bioinformatics, business collaboration, Data integration and etc. E-learning is also the field in which semantic web technologies can be used to provide dynamism in learning methodologies. E-learning includes set of tasks which may be instructional design, content development, authoring, delivery, assessment, feedback and etc. that can be sequenced and composed as workflow. Web based Learning Management Systems should concentrate on how to satisfy the e-learners requirements. In this paper we have suggested the theoretical framework ALMS-Adaptive Learning management System which focuses on three aspects 1) Extracting the knowledge from the use's interaction, behaviour and actions and translate them into semantics which are represented as Ontologies 2) Find the Learner style from the knowledge base and 3)deriving and composing the workflow depending upon the learner style. The intelligent agents are used in each module of the framework to perform reasoning and finally the personalized workflow for the e-learner has been recommended.

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