AR, VR AND THE METAVERSE - 2023/4
Module code: EEEM067
This module will introduce and explore the underlying concepts and technologies of virtual/augmented reality (VR/AR) and the emerging idea of the Metaverse. The module will also investigate the current and future challenges of the technologies and consider the impact it will have on industry and wider society.
Computer Science and Electronic Eng
VOLINO Marco (CS & EE)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 93
Lecture Hours: 22
Tutorial Hours: 5
Laboratory Hours: 10
Guided Learning: 10
Captured Content: 10
Prerequisites / Co-requisites
Indicative material for 10 weeks of teaching will cover:
1. Introduction into AR/VR
2. Human Physiology and Perception.
4. Graphical rendering.
5. Motion in Real and Virtual Worlds & Tracking
7. VR for CAD
9. Virtual Avatars
10. Metaverse and VR/AR outlook
|Assessment type||Unit of assessment||Weighting|
|Examination Online||Examination ONLINE (OPEN BOOK) EXAM WITHIN 4HR WINDOW||80|
The assessment strategy for this module is designed to provide students with the opportunity to demonstrate the learning outcomes. The computer simulation assignment will assess the students’ technical skills and expertise in modelling VR/AR in the industry of their choice. The written examination will assess students’ knowledge and understanding of the main concepts delivered in the lectures.
Thus, the summative assessment for this module consists of the following.
1. Coursework: 10 page report and presentation on the role of VR/AR in the industry of choice (20% weighting).
2. Online (open book) exam in a 4-hour window (80% weighting).
Formative assessment and feedback
For the module, students will receive formative assessment/feedback in the following ways.
- During lectures, by question and answer sessions
- During lectures, by group discussions
- During worked example/revision classes
- By means of unassessed tutorial problems (with answers/model solutions)
- Via the marking of the assignment, both electronic file submissions and written report
- Students will receive formative assessment/feedback during lectures, by question and answer sessions, and during supervised computer laboratory sessions.
- This module aims to provide an understanding of Virtual and Augmented Reality (VR/AR) technologies including hardware systems, software systems, game engines, graphical rendering, human vision, vestibular systems, tracking systems, interaction, and current challenges.
- The module also aims to provide opportunities for students to learn about the Surrey Pillars listed below.
|001||Demonstrate an understanding of the knowledge of the theory behind Virtual and Augmented Reality hardware and software||K||M1|
|002||Demonstrate an understanding of the state-of-the-art, the role of VR and AR in the modern world, and open challenges.||KCPT||M2, M4|
|003||Demonstrate an ability to create virtual worlds.||KCT||M3|
|004||An ability to independently evaluate open problems, business opportunities, and areas of possible research.||CPT||M5, M16, M17|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to achieve the specified learning outcomes:
- To equip students with an understanding of the fundamental concepts related to virtual and augmented reality and the metaverse.
- Students learn the basic principles behind Unity3D that will allow them to implement the concepts introduced in lectures.
- Students obtain a strong overview of the state-of-art technologies and associated challenges.
- Through the personalized coursework, students reinforce their understanding of the impact of AR/VR in the modern world, developing their vision and in-depth understanding of challenges and opportunities.
Learning and teaching methods include the following.
- Class discussion integrated within lecture
- Designed in-class problems
- Assignment in the form of computer simulations and reports using high level software
- Timetabled revision classes which demonstrate the principles of the theory in quantitative worked examples and prepare students for the written examination.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: EEEM067
This module has a capped number and may not be available to exchange students. Please check with the International Engagement Office email: email@example.com
This module is designed to allow students to develop knowledge, skills and capabilities in the following areas:
Digital capabilities: Students will develop skills in coding, will gain practical skills in computer vision, which is a key digital technologies in electronic engineering and computer science.
Employability: This module provides transferable skills in advance programming, hardware and problem solving which are appreciated by employers in both electronic engineering and computer communities.
Resourcefulness and Resilience: This module develops student skills in computer vision methods they have learned in lecture material to solve practical problems designed in the tutorial questions, exams, and computer programming-based course works.
Programmes this module appears in
|Artificial Intelligence MSc||1||Optional||A weighted aggregate mark of 50% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.