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SEALMS: Semantically Enhanced Adaptive Learning Management System

Authors

M.Farida Begam1 and Gopinath Ganapathy2, 1Manipal University Dubai, U.A.E and 2Bharathidasan University, India

Abstract

Semantic web technologies have been attracting interest in many domains. E-learning is not an exception which also involves with many activities or tasks such as instructional design, content development, authoring, delivery, assessment, feedback and etc. which can be sequenced and composed as workflow. Web based E-learning services should be focused in this aspect to fulfill variant e-learners’ requirements. This paper focuses on the Adaptive instructional design framework in which three significant facets are considered 1) Knowledge extraction from user’s behavior, interactions and actions and convert them into semantics 2) Detection of learners style from the semantics defined in the knowledge base and 3) Composition of the workflow for the variant learners to satisfy their requirements dynamically. In this paper we have proposed SEALMS –Semantically Enhanced Adaptive Learning Management System a theoretical framework tracks the learners profile and composes the services for learners using OWL-S. Modules of SEALMS include intelligent agents which perform a kind of reasoning and deriving results from the input fed, finally personalized workflow has been recommended for the e-learner. SEALMS is also a cyclic model where the feedback can be taken and reviving process can be initiated from the start to obtain the better results.

Keywords

Learning Style, Learning Objects, workflow, web services, Semantics, Ontology, and OWL-S

Full Text  Volume 2, Number 5