Module code: EEEM077

Module Overview

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.

Module provider

SOL - Computer Science and Elec Eng

Module Leader

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: 94

Tutorial Hours: 4

Guided Learning: 30

Captured Content: 22

Module Availability

Semester 2

Prerequisites / Co-requisites


Module content

AR, VR and the Metaverse will take students through a wide range of topics that underpin Virtual Reality, Augment Reality and Metaverse technologies including: (i) the physics that describe light and sound as well as the human perception system that help us detect and interpret these physical phenomena; (ii) graphical systems, representation of geometry and content creation; (iii) hardware, sensors and algorithms that facilitate motion tracking and interaction; and (iv) block chain technology and its role within the metaverse. 
The material for lectures is broadly arranged as follows: 

  • Introduction into AR/VR and Metaverse.

  • The Geometry of Virtual worlds.

  • Light Optics and Human Vision.

  • Rendering and Shading.

  • Motion and Displays.

  • Interaction.

  • Tracking.

  • Sound, Audio and Human Hearing.

  • Content Capture and Representation.

  • Blockchain and NFTs.

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Coursework 20
Examination Online Examination Online (4 hours within 24 hour window) 80

Alternative Assessment


Assessment Strategy

The assessment strategy for this module is designed to provide students with the opportunity to demonstrate the following:

  1. Coursework: Video recordings and code of selected lab exercises (20% weighting). 

  2. Online exam (80% weighting).

Formative assessment and feedback:
Students will receive formative assessment/feedback through multiple choice questions associated with the course material, and during tutorial sessions.

Module aims

  • 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.

Learning outcomes

Attributes Developed
001 To understand the premises and current landscape of the metaverse, as well as the underlying hardware and software technologies. KCT
002 To gain deep knowledge of the theory, hardware and software of Virtual and Augmented Reality (VR and AR). KT
003 To develop a strong understanding of the state-of-the-art, the role of VR and AR in the modern world, and open challenges. KCT
004 To acquire practical skills of creating and navigating virtual worlds and interacting with virtual worlds. KPT
005 To demonstrate an ability to independently evaluate open problems, business opportunities, and areas of possible research. CT

Attributes Developed

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: 

  • Equip students with an understanding of the fundamental concepts related to virtual and augmented reality and the Metaverse.

  • Teach them the basic principles behind Unity3D that will allow them to implement the concepts introduced in the course material.

  • Give them a strong understanding of the state-of-art technologies and associated challenges.

  • Reinforce the students’ understanding of the impact of AR/VR in the modern world, developing their vision and in-depth understanding of challenges and opportunities.

The learning and teaching methods include the following:

  • Captured Content.

  • Guided Learning (Labs, Additional Material).

  • Tutorials.

  • Self-Study.

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.

Reading list
Upon accessing the reading list, please search for the module using the module code: EEEM077

Other information

We are committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:
Digital capabilities:  Students will develop programming (C#) skills and gain practical skills in creating a virtual world and implementing navigation and interaction in a virtual world. They will acquire an understanding of hardware and software platforms required to create virtual and augmented reality applications.
Employability: This module provides transferable skills in advance programming, hardware and problem solving which are appreciated by employers in both electronic engineering and computer science communities.
Resourcefulness and Resilience: Through this module, students will not only acquire technical skills, but will also strengthen their ability to identify business opportunities and embrace new technologies in an era of rapidly evolving digital capabilities and virtual environments that are finding their way into various industries.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
People-Centred Artificial Intelligence (Online) MSc 2 Compulsory 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 2025/6 academic year.