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Adaptive Content Delivery in E-Learning Systems using Mobile Agents

Adaptive Content Delivery in E-Learning Systems using Mobile Agents

S. R. Mangalwede, D. H. Rao
ISBN13: 9781613501078|ISBN10: 1613501072|EISBN13: 9781613501085
DOI: 10.4018/978-1-61350-107-8.ch007
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MLA

Mangalwede, S. R., and D. H. Rao. "Adaptive Content Delivery in E-Learning Systems using Mobile Agents." Ubiquitous Multimedia and Mobile Agents: Models and Implementations, edited by Susmit Bagchi, IGI Global, 2012, pp. 148-166. https://doi.org/10.4018/978-1-61350-107-8.ch007

APA

Mangalwede, S. R. & Rao, D. H. (2012). Adaptive Content Delivery in E-Learning Systems using Mobile Agents. In S. Bagchi (Ed.), Ubiquitous Multimedia and Mobile Agents: Models and Implementations (pp. 148-166). IGI Global. https://doi.org/10.4018/978-1-61350-107-8.ch007

Chicago

Mangalwede, S. R., and D. H. Rao. "Adaptive Content Delivery in E-Learning Systems using Mobile Agents." In Ubiquitous Multimedia and Mobile Agents: Models and Implementations, edited by Susmit Bagchi, 148-166. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-107-8.ch007

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Abstract

The e-Learning refers to the use of networking technologies to create, foster, deliver and facilitate learning anytime, anywhere. This chapter discusses our research on personalization of e-Learning content based on the learner’s profile. After justifying the feasibility of using mobile agents in distributed computing systems for information retrieval, processing and mining, the authors deal with the relevance of mobile agents in e-Learning domain. The chapter discusses the proposed Case-Based Reasoning (CBR) as an approach to context-aware adaptive content delivery. Different parameters like technological, cultural and educational background of a learner are taken as the basis for forming the case-base that determines the type of content to be delivered. Along with the CBR, a diagnostic assessment to gauge an insight into the student’s current skills is done to determine the type of content to deliver. The implementation observations of such implementation vis-à-vis traditional e-Learning are also documented.

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