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Impact of learner control on learning in adaptable and personalised e-learning environments

Abstract

The purpose of this thesis is to investigate the impact of learners‟ measure of control over their learning, while working in different online learning environments, and how this, in combination with a structured learning material selection according to their learning preferences, can affect their learning performance. A qualitative study was carried out on the understanding of different learning philosophies, different learning environments and different learning preferences, in correlation with learners‟ measure of control over their learning environments, in terms of their influence on their learning performance. The research commenced with a survey of UK Higher Educational institutions, to determine the usage of adaptive e-learning systems in UK HE and the type and nature of the systems in use, which in combination with the literature review enabled the clarification of the research hypothesis and objectives. Since a measurement of learners‟ learning performance was needed, an adaptable personalised e-learning system (ALPELS) was developed to create an environment where a qualitative measurement could be done. Experimental data was then gathered from two cohorts of MSc students over two semesters, who used the newly designed and developed online learning environment. The successful implementation of the project has produced a large amount of data, which demonstrates a correlation between i) adaptable and personalised e-learning systems, and ii) learners‟ learning styles (which in itself supports the behaviouristic approach towards this type of online learning environment – ALPELS). The study indicates a dependency between an online controlled learning environment and learners‟ learning performances, showing that a personalised e-learning system (PELS) would be supportive of recall (R) and understanding (U) types of content materials (with an indication of 4.89%), but also demonstrating an increase in student learning performance in an adaptable e-learning system (ALELS) while using competency (C) types of content materials (with an indication of 5.43%). These outcomes provide a basis for future design of e-learning systems, utilising different models of learner control based on underpinning educational philosophies, in combination with learning preferences, to structure and present learning content according to type

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