This module focuses on the possibilities and challenges of interaction beyond the desktop. Exploring the 'mixed reality continuum' - a spectrum of emerging computing applications that runs from virtual reality (in which a user is immersed into a computer-generated virtual world) at one extreme, to ubiquitous computing (in which digital materials appear embedded into the everyday physical world - often referred to as the 'Internet of Things') at the other. In the middle of this continuum lie augmented reality and locative media in which the digital appears to be overlaid upon the physical world in different ways.
You will gain knowledge and hands-on experience of design and development with key technologies along this continuum, including working with both ubiquitous computing based sensor systems and locative media. You will learn about the Human-Computer Interaction challenges that need to be considered when creating mixed reality applications along with strategies for addressing them, so as to create compelling and reliable user experiences.
This module will provide students with a thorough understanding of the growth of IT and human computer systems. To examine the concepts and methods available for the analysis, design and evaluation of computer-based interfaces through hardware, software, task and systems design.
Advanced Methods in Human Factors and Human-Computer Interaction (spring)
- working as a human factors engineer/HCI professional
- predictive evaluation techniques (eg GOMs, Fitts Law)
- psychophysical methods
- verbal protocol analysis
- qualitative approaches and methodologies
- eye-tracking methodologies
- ethical considerations in human factors research
- capturing and analysing human physiological data
Individual Project: Human-Computer Interaction
You will undertake a project which is relevant to human-computer interaction, developing your skills in research, such as:
- planning research activities
- empirical investigation
- literature review
- critical reflection
- oral and written communication
- individual learning
- time management.
Collaboration with business, industry, and other outside bodies is encouraged.
This module introduces you to the theory and practice of design ethnography.
You will cover a range of topics including:
- origins and evolution of ethnography
- foundations and nature of the ethnomethodological approach
- ethnographic analysis
- its relationship to systems design
- the perceived problems with the approach
Studying Human Performance (autumn)
This module aims to give a broad review of the measurement techniques which can be used in ergonomic analysis and evaluation of systems or products, together with an understanding of the need for experimental design and control in order to obtain valid and meaningful results. It also provides a theoretical basis for techniques which may be practised during laboratory work and exercises in other human factors modules.
The module covers:
- Introduction to experimental design; experimental controls; selection and recruitment of subjects; user trials; ethical considerations
- Observational methods: direct and indirect observation; recording techniques; measurement of behaviour; activity sampling
- Subjective measurements: ranking methods, rating scales, application in interviews and questionnaires
- Task analysis: task description; tabular and hierarchical task analysis; applications
- Introduction to SPSS
- Descriptive statistics
- Statistical analysis: Types of data; Normal distribution; Non-parametric tests; Parametric 2 samples tests, Correlation and regression, Chi Square, ANOVA
Collaboration and Communication Technologies
In this module, you will consider the design of collaboration and communication technologies used in a variety of different contexts including workplace, domestic and leisure environments. You will consider the basic principles of such technologies, explore the technologies from a social perspective, consider their impact on human behaviour and critically reflect on their design from a human-centred perspective.
Fundamentals of Information Visualisation
Information Visualisation is the process of extracting knowledge from complex data, and presenting it to a user in a manner that this appropriate to their needs. This module provides a foundational understanding of some important issues in information visualisation design. You will learn about the differences between scientific and creative approaches to constructing visualisations, and consider some important challenges such as the representation of ambiguous or time-based data. You will also learn about psychological theories that help explain how humans process information, and consider their relevance to the design of effective visualisations.
If you want to learn how to design and implement your own interactive information visualisation, you should also take the linked module G53IVP (Information Visualisation Project). Together, these two modules form an integrated 20 credit programme of study.
This module covers the history, development and state-of-the-art in computer games and technological entertainment.
You will gain an appreciation of the range of gaming applications available and be able to chart their emergence as a prevalent form of entertainment. You will study the fundamental principles of theoretical game design and how these can be applied to a variety of modern computer games.
In addition, you will study the development of games as complex software systems. Specific software design issues to be considered will include the software architecture of games, and the technical issues associated with networked and multiplayer games.
Finally, you will use appropriate software environments to individually develop a number of games to explore relevant theoretical design and practical implementation concepts.
Information Visualisation Project
In this module you will gain practical experience of how to design and evaluate a distinctive interactive visualisation which presents information gathered from a complex and interesting data source.
You will gain experience in web-based technologies that enable the implementation of multi-layered and interactive information visualisations, supported through lab work that introduces specific features of these technologies.
Data Modelling and Analysis
This module will enable you to appreciate the range of data analysis problems that can be modelled computationally and a range of techniques that are suitable to analyse and solve those problems.
Topics covered include:
- basic statistics
- types of data
- data visualisation techniques
- data modelling
- data pre-processing methods including data imputation
- forecasting methods
- clustering and classification methods (decision trees, naīve bayes classifiers, k-nearest neighbours)
- data simulation
- model interpretation techniques to aid decision support
Spending around four hours each week in lectures and computer classes, appropriate software (eg. R, Weka) will be used to illustrate the topics you'll cover.
Simulation and Optimisation for Decision Support
This module offers insight into the applications of selected methods of decision support. The foundations for applying these methods are derived from:
- operations research simulation
- social simulation
- data science
- automated scheduling
- decision analysis
Throughout the module, you will become more competent in choosing and implementing the appropriate method for the particular problem at hand. You will engage in a mixture of lectures, workshops, and computer classes.
This module aims to equip students with fundamental knowledge and skills regarding the physical characteristics of people (body size, strength, flexibility, etc.) and environments (lighting, thermal, sound, etc.) as they relate to the design of products, workplaces and tasks/jobs. You’ll spend two hours in lectures each week when studying this module.
Simulation, Virtual Reality and Advanced Human-Machine Interface (autumn)
For human factors/ergonomics work, simulation tools can enable designers, managers and end-users to experience products and systems in realistic, interactive environments. Such advancements have significant cost implications, enabling designs and their implications to be visualised early in the development life cycle. In addition, virtual/augmented reality and other advanced human-machine interfaces (HMIs) are being developed in many different industries to support different user needs.
This module will provide you with the knowledge and skills required to understand and utilise computers as human factors tools for understanding peoples’ interactions with new technology. Moreover, the module will consider HMIs that are increasingly common in modern life and frequently designed and evaluated using simulation techniques.
The module is a mix of practical and research-oriented content, and you will make extensive use of the simulation facilities and on-going research projects within the Human Factors Research Group and elsewhere in the University.
- virtual reality technologies/environments/interfaces
- augmented reality; fidelity and validity of simulators
- presence factors for simulation
- understanding and minimising simulator sickness
- multimodal interfaces including the use of natural language and gesture interfaces, computers and collaborative/social interfaces, accessibility, in-car interfaces
||Number of Weeks
||Number of sessions
||Duration of a session
||Report (approx. 3,000 words) on the use of simulation to aid in the design/evaluation of specific products
||Presentation arguing for the use of advanced Human-Machine Interface solutions in a specific design context
Software Engineering Management
This module is part of the software engineering theme.
This module covers the following topics:
- management of the introduction of new software or IT systems
- software project management practices
- practical experience of use of an Agile software development project management process
- practical experience of use of Test Driven Development, pair programming and various approaches to software management tools, including the use of software versioning, project management planning tools and continuous integration and deployment
Work Systems and Safety (spring)
This modules aims to give an understanding of systems approaches to the design and analysis of effective and safe work, primarily in the context of industrial systems but also in relation to major projects, public and social systems and digital systems.
It is vital that students learn that technical, human, organizational and economic factors must be addressed when understanding the operation and potential failure in existing systems, and in developing requirements, implementation and evaluation approaches for social and socio-technical systems, and for systems of systems.
In this module, particular attention will be paid to distributed (in time and space) systems and ones with elements of automated processes (all of which will have to interact with human and organisational elements at some point and time). The potential causes of accidents and of human error are explained, and an introduction given to methods of reporting and investigating accidents and techniques for analysing accidents and systems reliability which will lead to the design of safer organisations and work systems.
Topics covered include:
- risk and risk perception
- risk assessment and management
- accident models and accident causation
- causes of human error
- epidemiology, accident reporting and analysis
- accident prevention
- human reliability assessment
- safety climate and culture
- safety systems management
Method and Frequency of Class:
||Number of Weeks
||Number of sessions
||Duration of a session
Method of Assessment:
This module is an introduction to the design of human-AI interaction to ensure the AI-driven systems we build are beneficial and useful to people.
The module will cover practical design topics including methods and techniques such as natural language processing and human-robot interaction. The module will also consider societal and theoretical concerns of human-AI interaction, including the ethics of AI, responsible innovation, trust, accountability and explainable AI.
The practical component of the module will involve building AI-driven systems that drive conversational experiences, such as a text-based ‘chatbots’ and speech-controlled services/ ‘skills’, involving automatic speech recognition and natural language processing.
This module will give you a comprehensive overview of the principles of programming, including procedural logic, variables, flow control, input and output and the analysis and design of programs. Instruction will be provided in an object-oriented programming language.
Cognitive Ergonomics in Design
This module will provide you with a thorough understanding of cognitive ergonomics and the way in which the consideration of cognitive ergonomics can impact on human performance in the workplace.