Introduction to Product Design / UX Design 2500-EN-CS-E-13

During the course students work in teams and progress through the complete design process, organized into six modules:

1. Fundamentals (the discipline's core vocabulary, history, and process models);
2. Needs Analysis & User Research (usability audits, user interviews, and synthesis);
3. Strategy & Defining the Problem (value proposition and business model frameworks, competitive analysis, and problem framing);
4. Design & Modelling (information architecture, user flows, and rapid AI-assisted prototyping);
5. Build (visual design with AI, design systems, and developer collaboration);
6. Measure & Learn (usability testing, analytics, and iteration).

The group project involves submitting homework regularly throughout the semester.

The course assumes no prior experience with design, design software, or AI tools. It is intended as a foundation for students considering further study or work in product design, UX research, or related fields, and as a practical introduction for students in adjacent disciplines (e.g., computer science, business, or marketing) who wish to work more effectively alongside designers.

Learning outcomes

Knowledge

1. Student knows and understands the core concepts, terminology, and good practices of UX design, including foundational agile methodologies. (K_W03)
2. Student knows and understands the design process and the designer's role within a cross-functional product team, including the social and ethical implications of using AI tools in that process. (K_W03, K_W06)

Skills

1. Student is able to plan and conduct basic user research and synthesize findings into personas and evidence-based problem statements. (K_U01, K_U03, K_U04)
2. Student is able to apply strategic design frameworks and problem-framing techniques to identify business goals and user needs and translate them into a well-scoped design problem. (K_U02, K_U03)
3. Student is able to design and iteratively refine prototypes — including AI-assisted prototypes — while critically evaluating the accuracy and limitations of AI-generated design output. (K_U05, K_K07)
4. Student is able to plan and conduct a usability test, interpret its findings, and present research and design conclusions clearly to a non-specialist audience. (K_U03, K_U07, K_U11, K_U12)

Social Competences

1. Student is ready to collaborate effectively within a team, take on a leading role when needed, and responsibly fulfil design-related tasks with attention to deadlines and shared outcomes. (K_U14, K_U15, K_K06)
2. Student is ready to critically evaluate and continue developing their own knowledge and practice regarding the use of AI tools in design work, recognizing where automation supports versus undermines professional judgment. (K_K01, K_K07)

Assessment criteria

1. Assessment methods:
- Group project

2. Components of the final grade and their weights:
- Group project - 100%

3. Grading scale:
over 50%: 3
over 60%: 3+
over 70%: 4,
over 80%: 4+
over 90%: 5

Number of allowed absences: 2
Each further absence lowers the final grade by 0.5

Bibliography

Books:

- Weinschenk, S. (2020). 100 Things Every Designer Needs to Know About People (2nd ed.). New Riders.
- Norman, D. A. (2013). The Design of Everyday Things: Revised and Expanded Edition. Basic Books.
- Krug, S. (2014). Don't Make Me Think, Revisited: A Common Sense Approach to Web and Mobile Usability (3rd ed.). New Riders.
- Portigal, S. (2023). Interviewing Users: How to Uncover Compelling Insights (2nd ed.). Rosenfeld Media.
- Buley, L., & Natoli, J. (2023). The User Experience Team of One: A Research and Design Survival Guide (2nd ed.). Rosenfeld Media.
- Knapp, J., Zeratsky, J., & Kowitz, B. (2016). Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days. Simon & Schuster.
- Ries, E. (2011). The Lean Startup. Crown Business.
- Levy, J. (2021). UX Strategy: Product Strategy Techniques for Devising Innovative Digital Solutions (2nd ed.). O'Reilly.

Ongoing professional resources
Students are encouraged to follow at least one of these throughout the course:

- Nielsen Norman Group — https://www.nngroup.com/articles/
- Smashing Magazine — https://www.smashingmagazine.com/
- Interaction Design Foundation — https://www.interaction-design.org/literature
- UX Collective — https://uxdesign.cc/

Notes

Term 2026Z:

Students must respect the principles of academic integrity. Cheating and plagiarism (including copying work from other students, internet or other sources) are serious violations that are punishable and instructors are required to report all cases to the administration.

Generative AI is part of the design workflow in this course, and students are expected to use it.

Students can use AI freely for:
- divergent ideation, e.g. generating alternative problem framings or stress-testing an idea they have
- drafting and rewriting research instruments - e.g. interview guides - which then they review and adapt,
- synthesising their own notes,
- UI copy,
- mockups, prototypes & code,
- support in reading, e.g. explaining unfamiliar concepts, translating sources.
- critique of their own design decisions.

Students should never:
- use generated content without first checking its correctness,
- present AI output as empirical findings - invented quotes,
transcripts, survey responses or usability observations count as data fabrication, whatever produced them,
- upload identifiable participant data to an external AI service.

AI tools may support the team’s work but must not replace it. Deliverables generated wholesale, without the team's own analysis and design decisions, will not be accepted. Students must be able to justify every element of their submitted work.

Each team deliverable must include a brief note stating which AI tools were used, for what purpose, and what was subsequently changed. The extent of use does not affect the grade; absent or inaccurate disclosure does. Students bear full responsibility for all submitted work, including citations, code and content generated with AI assistance.

Students should have access to a laptop/PC and a modern desktop-class browser. All software used in the course is available free of charge in browser-based or student versions.