Course Catalogue

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This course equips students with the engineering design methods, tools, and strategies needed to lead human-centred innovation in AI-driven product and system development. Students will apply design thinking frameworks to open-ended engineering problems, integrating user research, prototyping, and iterative evaluation to develop design solutions that address diverse user needs across cultural and application contexts.

The course is structured in four phases over 12 weeks (2 hours per week):

Phase 1 (Weeks 1-3): Foundations of design thinking methodology and AI-driven innovation - lectures introducing design thinking frameworks, user-centred design principles, and engineering requirements analysis.

Phase 2 (Weeks 4-6): User research methods and contextual analysis - workshops on identifying user needs across diverse cultural and emotional contexts, including techniques for stakeholder mapping, persona development, and scenario-based design.

Phase 3 (Weeks 7-9): Concept development and prototyping - students apply rapid prototyping and iterative design methods to develop and test AI-driven product or system concepts.

Phase 4 (Weeks 10-12): Integration, evaluation and presentation - teams refine their design concepts based on user feedback, prepare design specifications, and deliver final presentations with guest speaker critiques.

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Written assignment (design portfolio and reflective report) 40%, participation in class workshops and design reviews (Practical skills assessment) 30%, oral presentation 30%.

This course aims to develop students' ability to apply design thinking methods and tools to engineering innovation in AI-driven product and system development. Students will learn to integrate user research, concept generation, prototyping, and iterative evaluation within a structured design process.

Throughout the course, students will focus on:

1. Design thinking frameworks and their application to open-ended engineering problems in AI-driven contexts

2. User-centred design methods, including techniques for identifying and analysing diverse user needs across cultural and application contexts

3. Concept development and rapid prototyping strategies for AI-enabled products and systems

4. Evaluation and testing methods for assessing design solutions against user requirements and engineering specifications

5. Collaborative design practice, including interdisciplinary teamwork and the communication of design rationale to technical and non-technical stakeholders

By the end of the course, students will be able to:

1. Apply design thinking frameworks to identify, define, and scope open-ended engineering problems in AI-driven product and system development

2. Conduct user research and contextual analysis to identify functional, emotional, and cultural requirements for design solutions

3. Generate and evaluate design concepts using structured methods including rapid prototyping, scenario testing, and design review

4. Develop engineering design specifications that integrate technical performance criteria with user experience requirements

5. Critically evaluate AI-driven design solutions against engineering, usability, and ethical criteria

6. Communicate and defend design rationale through technical presentations and written design reports within interdisciplinary team settings