UX Design I (Spring 2023)

Abstract

This course allows students to develop their knowledge of user experience (UX) design and research in the context of new-generation digital products, especially those infused with AI and machine learning technology (AI-infused products). This course presents a number of research-based approaches to user research and the iterative design of these intelligent digital products. 

Description

As a digital designer, the ability to adapt to new technological developments and changing societal demands is crucial. AI-infused products are one of the fastest-growing areas in UX research and design today. From personalized services and virtual assistants to self-driving cars, these products have become increasingly integrated into many aspects of our life, with the promise to transform the way people work, live, and play. What is the new design space opened up by this new technology? How do designers effectively work with these highly technical systems? Above all, how do UX designers place human values (such as trust, agency, and ethics) in the center of AI?

In this course, students will learn relevant design theories and UX methods and apply them to concept design and prototyping. While the course focuses on AI-infused products, no programming is required. The emphasis is on how to engage emergent technology, such as AI, as a design material. Students with a strong design background will learn how to adapt their design skills to the new context of AI-infused products. We also welcome students with technical backgrounds who are interested in users. 

Formal prerequisites

The course builds upon knowledge from the courses of the 1st semester of the KDDIT program and students should have completed those courses or obtained similar knowledge elsewhere. We also welcome students with technical background who are interested in users. 

This course is part 1 of the UX Design specialization. 

Intended learning outcomes

After the course, the student should be able to:

• Create innovative concepts for UX designs using relevant tools and technologies
• Design and evaluate different levels of prototypes, building upon established interface paradigms
• Apply relevant design theory and critically reflect on own design work

Learning activities

Lectures, exercises and project work.

Course literature

The course literature is published in the course page in LearnIT.

Student Activity Budget

Estimated distribution of learning activities for the typical student

• Preparation for lectures and exercises: 20%
• Lectures: 15%
• Exercises: 15%
• Project work, supervision included: 40%
• Exam with preparation: 10%

Ordinary exam

Exam type:
C: Submission of written work, External (7-point scale)
Exam variation:
C1G: Submission of written work for groups

reexam

Exam type:
C: Submission of written work, External (7-point scale)
Exam variation:
C1G: Submission of written work for groups

Time and date