A Framework for Adaptive e-Learning.
PhD thesis, National University of Ireland Maynooth.
Adaptive learning systems attempt to adapt learning content to suit the needs
of the learners using the system. Most adaptive techniques, however, are constrained
by the pedagogical preference of the author of the system and are always
constrained to the system they were developed for and the domain content. This
thesis presents a novel method for content adaptation. A personal profile is described
that can be used to automatically generate instructional content to suit
the pedagogical preference and cognitive ability of a learner in real time. This thesis
discusses the manifestation of measurable cognitive traits in an online learning
environment and identifies cognitive resources, within instructional content, that
can be used to stimulate these manifestations.
There exists two main components for the learning component: Content Analyser
and a Selection Model. The Content Analyser is used to automatically generate
metadata to encapsulate cognitive resources within instructional content.
The analyser is designed to bridge the perceived gap found within instructional
repositories between inconsistent metadata created for instructional content and
multiple metadata standards being used. All instructional content that is analysed
is repackaged as Sharable Content Object Reference Model (SCORM) conforming
content. The Selection Model uses an evolutionary algorithm to evolve instructional
content to a Minimum Expected Learning Experience (MELE) to suit the
cognitive ability and pedagogical preference of a learner. The MELE is an approximation
to the expected exam result of a learner after a learning experience has
taken place. Additionally the thesis investigates the correlation between the cognitive ability and pedagogic preference of an author of instructional content and
the cognitive resources used to generate instructional content. Furthermore the
effectiveness of the learning component is investigated by analysing the learners
increase in performance using the learning component against a typical classroom
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