This module aims to provide students with a comprehensive understanding of the core concepts and AI technologies used in the Extended Reality (XR), Gaming, and Entertainment industries. Students will explore the unique challenges and opportunities of applying AI to these sectors, learning to design, implement, and evaluate AI algorithms for game development, XR applications, and entertainment systems. Topics include game AI techniques such as pathfinding, decision making, and tactical AI, as well as procedural content generation and AI-driven interactions in XR environments. The module also covers the role of AI in creating personalized entertainment experiences and enhancing user interaction through real-time AI processing. By examining industry trends and the impact of AI in these fields, students will gain practical insights into the evolving applications of AI in gaming and entertainment, preparing them for future roles in these dynamic industries.
A Demonstrate the application of core concepts related to Extended Reality (XR), Gaming, and Entertainment in industry contexts. B Identify, explore and describe the key AI technologies of XR, Gaming, and Entertainment Industry. C Design, implement, and evaluate different AI algorithms in XR, Gaming, or Entertainment Industry focused projects. D Analyse the impact and industry trend of applied algorithms and models
The teaching philosophy of the module follows very much the philosophy of Syntegrative Education. This philosophy is carried through in terms of assessment, with reduction on the use of exams and increase in coursework, especially problem-based assessments that are project focused. This module will be delivered through a combination of lectures, group discussions, case studies, and hands-on practical exercises etc. Lectures and group discussions are conducted using the Problem Based Learning paradigm focusing on student-centered learning, where they develop critical thinking and problem-solving skills to address open-ended problems that lacks a straightforward solution This module is taught with an emphasis on student learning through practice and by projects, facilitated by a module leader, and where appropriate, industrial mentors. Students can identify particular areas of learning needs or interests according to the available project(s). They will conduct independent research to gather information and resources to better define the problem. Progress towards the learning outcomes will be facilitated and monitored, where students are guided to progressively address the given problem through tasks. Independent learning will form an important aspect of the educational activities in this module. Case studies will be used to provide students with real-world examples of how the concepts and techniques covered in this module can be applied. Lab/Practical sessions will allow students to apply the techniques and tools acquired to solve real-world industry focused problems. Assessed primarily by a project, students shall gain practical experience in undertaking independent study and research on industry focused real-world problems. This module will leverage generative AI to enhance course content and teaching methods in line with the learning outcomes. By integrating advanced AI technologies, we aim to improve the efficiency of teaching and interaction, while fostering greater student autonomy and flexibility in learning.