Educational Data Analytics and Standards for Immersive Educational Systems

Technological developments in recent years have led to increased development of immersive learning and training applications for various domains. Within this thesis, a review of AR/VR-enhanced STEM and Language learning applications is presented, considering how such technologies can contribute to student learning and the shortcomings that may exist in the literature. Moreover, concerning the effects of AR technology on students with special needs, this thesis demonstrates and interprets the results of a digital AR-enhanced intervention to the literacy skills of students with a presence of ADHD. Pending the trend of digital education and the benefits of educational data analytics applications, this study further aims to explore and exploit the knowledge around EDM and LA applications. Particular attention is also being given to the standardization efforts on digital education and how these can apply to a digital learning repository, so its AR/VR and other types of LOs can be more easily found by others. The findings of this study support the idea that AR/VR technologies are worth implementing in STEM and Language learning activities, as they have been found to increase student performance, motivation and engagement, support inquiry learning, and students find them useful and easy to use. Additionally, in some cases, AR technology has been found to enhance students’ attitudes toward technology. Regarding digital AR-enhanced literacy interventions for pupils with ADHD presence, the case study revealed that digital and AR-enhanced applications can equivalently and significantly support participants in acquiring competent literacy skills beyond the conventional school programme. In terms of leveraging EDA methods and techniques from recently published studies, the review conducted revealed that recent efforts mainly use data from digital learning environments and often chose to apply relationship mining and prediction methods to achieve their goals. Moreover, the review showed that the most frequently targeted areas of study were: detection of student behaviour and learning strategy; predicting their performance and detecting at-risk students; assessing predictors of performance; and supporting students with feedback on their attendance and behaviour.
Given that EDM and LA are often used in the context of digital education, this thesis also demonstrated that a significant amount of standardization efforts have been published in the fields of describing learning resources, enhancing content packaging transition and reuse, monitoring and managing students’ data, and ensuring interoperability among heterogeneous learning systems.
Finally, aiming towards the dissemination and discoverability of immersive learning activities, this thesis demonstrates that the IEEE-LOM standard can be successfully integrated into a Moodle digital repository to allow creators of AR and other types of learning content to describe their resources in a standardized way that allows their reuse. Furthermore, under the same objectives, this thesis effort presents the OAI-PMH framework as a LOM metadata harvesting tool that supports interoperability between various repositories while at the same time arguing that other alternatives may be considered more successful due to the current lack of relevant search service providers.