Digital games provide a recognised means of engagement and education when addressing challenges in educating and immersing individuals in their own heritages, and those of other cultures. Similarly, gamification techniques, commonly expressed as the addition of game elements to an existing process, have been successfully applied to augment existing resources and programmes. The many examples of gamification or serious games focusing on cultural heritage also highlight the potential benefits of using these principles for the purposes of supporting preservation and learning. In this chapter, we present I-Ulysses, a virtual-reality game designed to engage based around the notable work Ulysses by Irish author James Joyce. The rationale for the selection of Ulysses as a basis for the game's content and design was two-fold; firstly because of its cultural impact within Ireland, and secondly as its content appeared well-suited to exploration as a virtual reality experience. Facets of gamification are explored in I-Ulysses through key mechanics, including a focus towards virtual worlds and crowd intelligence based on real-world data, to highlight how these principles can be employed for cultural heritage preservation and knowledge transfer. Through feedback obtained from focus groups interacting with I-Ulysses, it can be seen that the gamified mechanics presented through the lens of virtual reality provide an informative and educational guide to Ulysses that would engage and appeal to a wide audience.
Developments in artificial intelligence can be leveraged to support the diagnosis of degenerative disorders, such as epilepsy and Parkinson's disease. This study aims to provide a software solution, focused initially towards Parkinson's disease, which can positively impact medical practice surrounding degenerative diagnoses. Through the use of a dataset containing numerical data representing acoustic features extracted from an audio recording of an individual, it is determined if a neural approach can provide an improvement over previous results in the area. This is achieved through the implementation of a feedforward neural network and a layer recurrent neural network. By comparison with the state-of-the-art, a Bayesian approach providing a classification accuracy benchmark of 87.1%, it is found that the implemented neural networks are capable of average accuracy of 96%, highlighting improved accuracy for the classification process. The solution is capable of supporting the diagnosis of Parkinson's disease in an advisory capacity and is envisioned to inform the process of referral through general practice.
The COVID-19 pandemic caused a shift in teaching practice towards blended learning for many higher education institutions. This led to the rapid adoption of certain digital technologies within existing teaching structures as a means to meet student access needs. This paper is an attempt to summarise and extend pre-COVID-19 pedagogical research to leverage digital immersive technologies for blended teaching in the post-pandemic era. This paper forms both a review of these methodologies and a case study of the I-Ulysses Virtual Learning Environment as an example of a platform that leverages such immersive digital technologies and employs instrumental use of VR. To further clarify, the purpose of the paper is to describe and propose a distance learning solution with immersive VR qualities; this is what the I-Ulysses environment represents, as the main obstacle to learners of site-specific information during the pandemic has been lack of on-site accessibility. Furthermore, this is of key importance, because Joyce’s novel takes place in historical Dublin, where access to the physical location of the story is indispensable to a reader.
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