Integrating adaptivity into web-based learning

Abstract

Adaptive hypermedia is an emerging technology that changes the conventional way of presenting information online. Instead of displaying a static page, information can now be adapted dynamically to users, where different users with different needs, interests and domain background are directed to different pieces of information. This idea has attracted the educational community in recent years to develop adaptive systems and applications for learning purposes. Many techniques and methodologies have sprang from these developments for organising the content (domain modeling) and capturing information from the users (user modeling) in order to implement the adaptive mechanisms.

This thesis proposes two methodologies that build upon existing methods in both domain modeling and user modeling for adaptive hypermedia, particularly in the educational context. This work demonstrates the use of effective reading speed to present a novel way of modeling the user's browsing history in adaptive hypermedia. Also, in terms of domain modeling, the work proposes the use of a keyword representation technique to free the domain expert from their heavy involvement in the conventional way of organising the content for adaptive hypermedia. As a result, a web-based medical learning application, namely JointZone, is developed to embrace these new methodologies. Joint-Zone's content is made adaptive using two adaptive techniques: knowledge-based link hiding and browsing history-based link annotation. The thesis also presents a usability study and an evaluation that assess the impact and effectiveness of these adaptive techniques in web-based learning.

A secondary objective of this work is to explore how better linkage between information entities on the web can be achieved through the adoption of linkbases. The thesis hence also demonstrates methods for generating structural, associative and referential links to provide an additional dimension to the conventional methods of linking information in a web-based learning application.

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