A service-orientated architecture for adaptive and collaborative e-learning systems

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Meccawy, Maram (2009) A service-orientated architecture for adaptive and collaborative e-learning systems. PhD thesis, University of Nottingham.

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Abstract

This research proposes a new architecture for Adaptive Educational Hypermedia Systems (AEHS). Architectures in the context of this thesis refer to the components of the system and their communications and interactions. The architecture addresses the limitations of AEHS regarding interoperability, reusability, openness, flexibility, and limited tools for collaborative and social learning. It presents an integrated adaptive and collaborative Web-based learning environment.

The new e-learning environment is implemented as a set of independent Web services within a service-oriented architecture (SOA). Moreover, it uses a modern Learning Management System (LMS) as the delivery service and the user interface for this environment. This is a two-way solution, whereby adaptive learning is introduced via a widely adopted LMS, and the LMS itself is enriched with an external - yet integrated - adaptation layer.

To test the relevance of the new architecture, practical experiments were undertaken. The interoperability, reusability and openness test revealed that the user could easily switch between various LMS to access the personalised lessons. In addition, the system was tested by students at the University of Nottingham as a revision guide to a Software Engineering module. This test showed that the system was robust; it automatically handled a large number of students and produced the desired adaptive content. However, regarding the use of the collaborative learning tools, the test showed low levels of such usage.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Blanchfield, P.
Brailsford, T.J.
Keywords: E-Learning, Adaptive Educational Hypermedia, Adaptive Web-based Learning Systems, SOA, Web Services, Software Architectures, Collaborative Learning, Learning Management Systems, Personalised Learning
Subjects: Q Science > QA Mathematics > QA 75 Electronic computers. Computer science
Faculties/Schools: UK Campuses > Faculty of Science > School of Computer Science
Item ID: 10684
Depositing User: EP, Services
Date Deposited: 04 Dec 2009 11:30
Last Modified: 15 Dec 2017 23:43
URI: https://eprints.nottingham.ac.uk/id/eprint/10684

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