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Design as a function is the driver of change so therefore the role of the designer is demanding and dynamic, with an ever-changing landscape of economics, politics, society, culture and values. Designers are challenged to problem solve, working towards the United Nation Global Sustainable Goals (SDGs) to provide strategic plans for competitive advantage leading to global prosperity. We ask an overarching question of how can design enable industry, communities and society as a whole to create a more resilient future.

“The 2030 Agenda for Sustainable Development adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for people and the planet, now and into the future. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries - developed and developing - in a global partnership. They recognize that ending poverty and other deprivations must go hand-in-hand with strategies that improve health and education, reduce inequality, and spur economic growth – all while tackling climate change and working to preserve our oceans and forests” (sdgs.un.org, 2023)

The Principles and Practices module explores the relevance and context of the role of a designer in relation to products and services. It explores the designer and their values, principles & processes in practice in relation to responsible design. It looks at different stakeholder perspectives involved in the design processes to examine the interaction and key values & principles a designer must hold to address progressive sustainable practice from a global perspective.

This would inform an approach to problem solving that takes a critical and purposeful direction that understands the human and the problem first. The module will delve into how a designer can harness these advanced skills to add value to the business environment and their own practice from a societal perspective. Decisions made in the design process towards this, advance the definition of sustainable practice to improve the three ‘Ps’ People, Planet and Profits (Tripe Bottom Line) .

You will be expected to develop and present constructive & critical thinking
in relation to your own direction and demonstrate understanding of the academic literature recommended on the module and beyond.

During the course of this module, you will explore the SDGs and delve into models of sustainable practice considering Triple Bottom Line, Circular economy and social practice. The module will cover advanced key concepts in design practices for Human centred design in industry and delve into depth on the theoretical literature related to Human Centre and inclusive practice. You will also be encouraged to discuss, engage and articulate on the wider political, social, environmental and technological shifts in society to position your ideas within your chosen sector in Design Management. This would inform an approach to problem solving that takes a critical and purposeful direction that understands the problem first.

Design as a function is the driver of change so therefore the role of the designer is demanding and dynamic, with an ever-changing landscape of economics, politics, society, culture and values. Designers are challenged to problem solve, working towards the United Nation Global Sustainable Goals (SDGs) to provide strategic plans for competitive advantage leading to global prosperity. We ask an overarching question of how can design enable industry, communities and society as a whole to create a more resilient future.

“The 2030 Agenda for Sustainable Development adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for people and the planet, now and into the future. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries - developed and developing - in a global partnership. They recognize that ending poverty and other deprivations must go hand-in-hand with strategies that improve health and education, reduce inequality, and spur economic growth – all while tackling climate change and working to preserve our oceans and forests” (sdgs.un.org, 2023)

The Principles and Practices module explores the relevance and context of the role of a designer in relation to products and services. It explores the designer and their values, principles & processes in practice in relation to responsible design. It looks at different stakeholder perspectives involved in the design processes to examine the interaction and key values & principles a designer must hold to address progressive sustainable practice from a global perspective.

This would inform an approach to problem solving that takes a critical and purposeful direction that understands the human and the problem first. The module will delve into how a designer can harness these advanced skills to add value to the business environment and their own practice from a societal perspective. Decisions made in the design process towards this, advance the definition of sustainable practice to improve the three ‘Ps’ People, Planet and Profits (Tripe Bottom Line) .

You will be expected to develop and present constructive & critical thinking
in relation to your own direction and demonstrate understanding of the academic literature recommended on the module and beyond.

During the course of this module, you will explore the SDGs and delve into models of sustainable practice considering Triple Bottom Line, Circular economy and social practice. The module will cover advanced key concepts in design practices for Human centred design in industry and delve into depth on the theoretical literature related to Human Centre and inclusive practice. You will also be encouraged to discuss, engage and articulate on the wider political, social, environmental and technological shifts in society to position your ideas within your chosen sector in Design Management. This would inform an approach to problem solving that takes a critical and purposeful direction that understands the problem first.

A well-designed experiment is an efficient way of learning about the world. Typically, an experiment may involve varying several factors and observing the value of a response at settings of combinations of values of these factors. The mathematical challenge is then to choose which settings to use in order to gain the maximum information from the resulting data.

Experiments are performed in all branches of science, engineering and industry. In recent years, traditional application areas such as agriculture, manufacturing, medicine and pharmaceutical science
have been joined by bioinformatics, genetics, drug discovery, finance and economics. Problems of increasing size and complexity from these new areas have led to the development of many new
methods for designing and analysing experiments. The aim of this module is to provide a grounding in the statistical and mathematical methods that underpin the design and analysis of experiments, before exploring a number of areas where recent and ongoing developments are taking place. Mathematical criteria for quantifying the information available from a given design will be defined and explored, and will underpin much of the material in the module.

A well-designed experiment is an efficient way of learning about the world. Typically, an experiment may involve varying several factors and observing the value of a response at settings of combinations of values of these factors. The mathematical challenge is then to choose which settings to use in order to gain the maximum information from the resulting data.

Experiments are performed in all branches of science, engineering and industry. In recent years, traditional application areas such as agriculture, manufacturing, medicine and pharmaceutical science
have been joined by bioinformatics, genetics, drug discovery, finance and economics. Problems of increasing size and complexity from these new areas have led to the development of many new
methods for designing and analysing experiments. The aim of this module is to provide a grounding in the statistical and mathematical methods that underpin the design and analysis of experiments, before exploring a number of areas where recent and ongoing developments are taking place. Mathematical criteria for quantifying the information available from a given design will be defined and explored, and will underpin much of the material in the module.

A well-designed experiment is an efficient way of learning about the world. Typically, an experiment may involve varying several factors and observing the value of a response at settings of combinations of values of these factors. The mathematical challenge is then to choose which settings to use in order to gain the maximum information from the resulting data.

Experiments are performed in all branches of science, engineering and industry. In recent years, traditional application areas such as agriculture, manufacturing, medicine and pharmaceutical science
have been joined by bioinformatics, genetics, drug discovery, finance and economics. Problems of increasing size and complexity from these new areas have led to the development of many new
methods for designing and analysing experiments. The aim of this module is to provide a grounding in the statistical and mathematical methods that underpin the design and analysis of experiments, before exploring a number of areas where recent and ongoing developments are taking place. Mathematical criteria for quantifying the information available from a given design will be defined and explored, and will underpin much of the material in the module.

A well-designed experiment is an efficient way of learning about the world. Typically, an experiment may involve varying several factors and observing the value of a response at settings of combinations of values of these factors. The mathematical challenge is then to choose which settings to use in order to gain the maximum information from the resulting data.

Experiments are performed in all branches of science, engineering and industry. In recent years, traditional application areas such as agriculture, manufacturing, medicine and pharmaceutical science
have been joined by bioinformatics, genetics, drug discovery, finance and economics. Problems of increasing size and complexity from these new areas have led to the development of many new
methods for designing and analysing experiments. The aim of this module is to provide a grounding in the statistical and mathematical methods that underpin the design and analysis of experiments, before exploring a number of areas where recent and ongoing developments are taking place. Mathematical criteria for quantifying the information available from a given design will be defined and explored, and will underpin much of the material in the module.

A well-designed experiment is an efficient way of learning about the world. Typically, an experiment may involve varying several factors and observing the value of a response at settings of combinations of values of these factors. The mathematical challenge is then to choose which settings to use in order to gain the maximum information from the resulting data.

Experiments are performed in all branches of science, engineering and industry. In recent years, traditional application areas such as agriculture, manufacturing, medicine and pharmaceutical science
have been joined by bioinformatics, genetics, drug discovery, finance and economics. Problems of increasing size and complexity from these new areas have led to the development of many new
methods for designing and analysing experiments. The aim of this module is to provide a grounding in the statistical and mathematical methods that underpin the design and analysis of experiments, before exploring a number of areas where recent and ongoing developments are taking place. Mathematical criteria for quantifying the information available from a given design will be defined and explored, and will underpin much of the material in the module.

A well-designed experiment is an efficient way of learning about the world. Typically, an experiment may involve varying several factors and observing the value of a response at settings of combinations of values of these factors. The mathematical challenge is then to choose which settings to use in order to gain the maximum information from the resulting data.

Experiments are performed in all branches of science, engineering and industry. In recent years, traditional application areas such as agriculture, manufacturing, medicine and pharmaceutical science
have been joined by bioinformatics, genetics, drug discovery, finance and economics. Problems of increasing size and complexity from these new areas have led to the development of many new
methods for designing and analysing experiments. The aim of this module is to provide a grounding in the statistical and mathematical methods that underpin the design and analysis of experiments, before exploring a number of areas where recent and ongoing developments are taking place. Mathematical criteria for quantifying the information available from a given design will be defined and explored, and will underpin much of the material in the module.

This studio module introduces Environmental and Spatial Design as a critical, responsive, and creative practice. Working across physical, interior, and spatial contexts, students engage with urgent real-world challenges through a structured sequence of design projects.

Emphasis is placed on research-informed investigation, creative problem-solving, and the development of a sustainable design mindset. Students work both collaboratively and independently, building fluency in visual communication, critical analysis, and reflective practice.

The module establishes the intellectual and creative foundations for postgraduate study in Environmental and Spatial Design, positioning design as a discipline capable of meaningful response to complex social, environmental, and spatial challenges.

This module equips you with core design research and evaluations tools. You will explore a range of design-research methods—visual, spatial, participatory, and digital—and learn how to frame research questions, apply research ethics, justify your approach, and assess the potential impacts of your work. You will develop a research question and plan to implement in the final project.