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.ududA 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.ududThe 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.ududThe 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).ududThe 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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机译：本文的目的是调查学习者在不同的在线学习环境中工作时对他们的学习进行控制的措施的影响，以及这与根据学习偏好进行的结构化学习材料选择一起如何影响他们的学习表现。定性研究是基于对不同学习理念，不同学习环境和不同学习偏好的理解，并根据学习者对学习环境的控制程度，对他们对学习绩效的影响进行的。 ud ud这项研究始于对英国高等教育机构的调查，以确定英国高等教育中自适应电子学习系统的使用情况以及所使用系统的类型和性质，再结合文献综述，可以对研究假设和目标。由于需要对学习者的学习绩效进行评估，因此开发了一种适应性强的个性化电子学习系统（ALPELS），以创建可以进行定性评估的环境。然后从两个学期的两个理科硕士生队列中收集了实验数据，他们使用了新设计和开发的在线学习环境。 ud ud项目的成功实施产生了大量数据，这表明i之间存在相关性适应性强和个性化的电子学习系统，以及ii）学习者的学习方式（其本身支持针对这种类型的在线学习环境的行为主义方法-ALPELS）。 ud ud研究表明，在线控制学习环境与学习者之间存在依赖性的学习表现，表明个性化的电子学习系统（PELS）将支持内容材料的回忆（R）和理解（U）类型（指示为4.89％），但同时也表明学生的学习表现有所提高在适应性电子学习系统（ALELS）中使用能力（C）类型的内容材料（指示为5.43％）。这些成果为未来的电子学习系统设计提供了基础，它利用基于基础教育理念的学习者控制的不同模型，结合学习偏好，根据类型来组织和展示学习内容。
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